feat: add morning review packet generator (#966)

Implements one concrete Phase 2 slice for the morning review packet epic:
- add a script that fetches an epic and child QA issues from Gitea
- parse structured QA issue sections into a reusable packet model
- render a review-ready markdown packet
- add a generated 2026-04-21 Hermes harness review packet artifact
- cover parsing and rendering with targeted tests

Refs #966

docs/review_packets/hermes-harness-2026-04-21.md

@@ -0,0 +1,387 @@
+# Morning Review Packet
+
+Source epic: [EPIC: Morning review packet — Hermes harness features landed 2026-04-21](https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/949)
+
+## Epic context
+
+EPIC: Morning review packet — Hermes harness features landed 2026-04-21
+
+Source: git log on upstream/main since 2026-04-21 00:00 EDT, plus the current local branch `burn/921-poka-yoke-hardcoded-paths` for the branch-only path-guard work.
+
+Important review note:
+- Validate upstream-landed features on `upstream/main` or a synced branch.
+- Validate the path-guard work on `burn/921-poka-yoke-hardcoded-paths`.
+
+This epic is a morning-review packet: one QA issue per feature cluster, each with concrete acceptance criteria and targeted tests or manual checks.
+
+## Success criteria
+- [ ] Every issue has a clear PASS / FAIL outcome.
+- [ ] Test output or manual evidence is attached to each issue.
+- [ ] Any drift between upstream/main and forge/main is called out explicitly.
+
+## Sub-issues
+### Upstream/main features landed 2026-04-21
+- [ ] #950 [QA] Verify AI Gateway provider UX + attribution headers
+- [ ] #951 [QA] Verify transport abstraction + AnthropicTransport wiring
+- [ ] #952 [QA] Verify CLI voice beep toggle
+- [ ] #953 [QA] Verify bundled skill scripts run out of the box
+- [ ] #954 [QA] Verify maps skill guest_house / camp_site / bakery expansion
+- [ ] #955 [QA] Verify KittenTTS local provider end-to-end
+- [ ] #956 [QA] Verify numbered keyboard shortcuts for approval + clarify prompts
+- [ ] #957 [QA] Verify optional adversarial-ux-test skill catalog flow
+- [ ] #958 [QA] Verify /usage account limits in CLI + gateway
+- [ ] #959 [QA] Verify OpenCode-Go curated catalog additions
+- [ ] #960 [QA] Verify patch 'did you mean?' suggestions
+- [ ] #961 [QA] Verify web dashboard update/restart action buttons
+
+### Local branch-only work
+- [ ] #962 [QA] Verify hardcoded-home path guard on burn/921 branch
+
+## Summary
+
+| Issue | State | Commits | Tests |
+| --- | --- | --- | --- |
+| #950 | open | 5 | 2 |
+| #951 | open | 2 | 2 |
+| #952 | open | 1 | 1 |
+| #953 | open | 1 | 2 |
+| #954 | open | 1 | 0 |
+| #955 | open | 2 | 1 |
+| #956 | open | 1 | 0 |
+| #957 | open | 1 | 0 |
+| #958 | open | 2 | 2 |
+| #959 | open | 1 | 1 |
+| #960 | open | 2 | 1 |
+| #961 | closed | 1 | 0 |
+| #962 | closed | 1 | 1 |
+
+## #950 — [QA] Verify AI Gateway provider UX + attribution headers
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/950
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `b11753879` — attribution default_headers for ai-gateway provider
+- `700437440` — curated picker with live pricing
+- `ac26a460f` — promote ai-gateway in provider picker ordering
+- `5bb2d11b0` — auto-promote free Moonshot models
+- `29f57ec95` — Vercel deep-link for API key creation
+
+### Targeted tests
+- `tests/hermes_cli/test_ai_gateway_models.py`
+- `tests/run_agent/test_provider_attribution_headers.py`
+
+### Tasks
+- [ ] Open `hermes model` and verify `ai-gateway` appears near the top.
+- [ ] Verify live pricing appears in the picker.
+- [ ] Verify free Moonshot models are promoted.
+- [ ] Trigger API-key setup flow and verify the Vercel deep link.
+- [ ] Send one ai-gateway request and verify attribution headers are attached.
+
+### Acceptance criteria
+- [ ] UI ordering and pricing match the landed behavior.
+- [ ] Attribution headers are present on ai-gateway requests.
+- [ ] Targeted tests pass.
+
+## #951 — [QA] Verify transport abstraction + AnthropicTransport wiring
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/951
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `7ab5eebd0` — transport types + Anthropic normalize migration
+- `731f4fbae` — transport ABC + AnthropicTransport wired to all paths
+
+### Targeted tests
+- `tests/agent/transports/test_types.py`
+- `tests/agent/test_anthropic_normalize_v2.py`
+
+### Tasks
+- [ ] Verify plain-text Anthropic responses normalize correctly.
+- [ ] Verify tool-call responses preserve IDs, names, and arguments.
+- [ ] Verify reasoning/thinking is preserved separately from visible content.
+- [ ] Verify finish_reason mapping remains correct across paths.
+
+### Acceptance criteria
+- [ ] Normalized response shape is stable.
+- [ ] Tool-call and reasoning payloads survive normalization.
+- [ ] Targeted tests pass.
+
+## #952 — [QA] Verify CLI voice beep toggle
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/952
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `b48ea41d2` — voice: add CLI beep toggle
+
+### Targeted tests
+- `tests/tools/test_voice_cli_integration.py`
+
+### Tasks
+- [ ] Enable the beep option in config and confirm voice mode emits the beep.
+- [ ] Disable the option and confirm the same path is silent.
+- [ ] Verify voice mode still strips markdown before speech output.
+- [ ] Verify voice mode does not pollute conversation history with TTS-only text.
+
+### Acceptance criteria
+- [ ] Beep behavior is actually toggled by config.
+- [ ] Existing voice/TTS integration behavior is not regressed.
+- [ ] Targeted tests pass.
+
+## #953 — [QA] Verify bundled skill scripts run out of the box
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/953
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `328223576` — make bundled skill scripts runnable out of the box
+
+### Targeted tests
+- `tests/agent/test_skill_commands.py`
+- `tests/tools/test_local_shell_init.py`
+
+### Tasks
+- [ ] Pick a bundled skill that ships a script and run it without manual chmod/PATH surgery.
+- [ ] Verify local terminal execution resolves the installed skill script correctly.
+- [ ] Verify local shell init still behaves correctly.
+
+### Acceptance criteria
+- [ ] Bundled skill scripts execute from the installed skill location with no manual prep.
+- [ ] Local shell init remains healthy.
+- [ ] Targeted tests pass.
+
+## #954 — [QA] Verify maps skill guest_house / camp_site / bakery expansion
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/954
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `c5a814b23` — maps: add guest_house, camp_site, and dual-key bakery lookup
+
+### Tasks
+- [ ] Use the maps skill to search for a guest house in a known populated area.
+- [ ] Use the maps skill to search for a camp site in a known populated area.
+- [ ] Use the maps skill to search for a bakery and verify both supported keys resolve correctly.
+- [ ] Confirm results are sensible and non-empty.
+
+### Acceptance criteria
+- [ ] All three place types resolve correctly.
+- [ ] Bakery lookup works through both supported keys.
+- [ ] Manual evidence is attached in the issue.
+
+## #955 — [QA] Verify KittenTTS local provider end-to-end
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/955
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `1830ebfc5` — add KittenTTS provider
+- `2d7ff9c5b` — complete KittenTTS integration across tools/setup/docs/tests
+
+### Targeted tests
+- `tests/tools/test_tts_kittentts.py`
+
+### Tasks
+- [ ] Configure TTS to use `kittentts`.
+- [ ] Generate speech to `.wav` and verify playable output.
+- [ ] Verify voice / speed / cleaned text are passed correctly.
+- [ ] Generate repeated requests and verify model caching behavior.
+- [ ] Generate a non-wav output and verify ffmpeg conversion path.
+- [ ] Verify missing-package behavior returns a helpful error.
+
+### Acceptance criteria
+- [ ] KittenTTS works end-to-end when installed.
+- [ ] Failure mode is operator-friendly when not installed.
+- [ ] Targeted tests pass.
+
+## #956 — [QA] Verify numbered keyboard shortcuts for approval + clarify prompts
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/956
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `d1ed6f4fb` — CLI: add numbered keyboard shortcuts to approval and clarify prompts
+
+### Tasks
+- [ ] Trigger an approval prompt and choose an option with number keys.
+- [ ] Trigger a clarify prompt and choose an option with number keys.
+- [ ] Verify the correct option is submitted both times.
+- [ ] Verify normal keyboard navigation still works.
+
+### Acceptance criteria
+- [ ] Number-key selection works for both prompt types.
+- [ ] Legacy keyboard navigation is not broken.
+- [ ] Manual evidence is attached in the issue.
+
+## #957 — [QA] Verify optional adversarial-ux-test skill catalog flow
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/957
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `e50e7f11b` — skills: add adversarial-ux-test optional skill
+
+### Tasks
+- [ ] Verify the optional skill appears in the optional skill catalog.
+- [ ] Install or enable the skill.
+- [ ] Load it successfully through Hermes.
+- [ ] Disable or remove it and verify catalog state updates cleanly.
+
+### Acceptance criteria
+- [ ] Catalog listing is correct.
+- [ ] Install / load / disable lifecycle works cleanly.
+- [ ] Manual evidence is attached in the issue.
+
+## #958 — [QA] Verify /usage account limits in CLI + gateway
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/958
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `8a11b0a20` — per-provider account limits module
+- `bcc5d7b67` — append account limits section in CLI and gateway
+
+### Targeted tests
+- `tests/test_account_usage.py`
+- `tests/gateway/test_usage_command.py`
+
+### Tasks
+- [ ] Run `/usage` in CLI for a provider with account limits.
+- [ ] Verify provider, remaining quota, total limit, and reset window render correctly.
+- [ ] Run `/usage` through the gateway and verify the same section appears.
+- [ ] Verify zero-value cache read/write sections stay hidden when appropriate.
+
+### Acceptance criteria
+- [ ] CLI and gateway both show the landed account-limits section correctly.
+- [ ] Targeted tests pass.
+
+## #959 — [QA] Verify OpenCode-Go curated catalog additions
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/959
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `4fea1769d` — opencode-go: add Kimi K2.6 and Qwen3.5/3.6 Plus to curated catalog
+
+### Targeted tests
+- `tests/hermes_cli/test_opencode_go_in_model_list.py`
+
+### Tasks
+- [ ] With valid OpenCode-Go credentials, open `hermes model`.
+- [ ] Verify Kimi K2.6 appears.
+- [ ] Verify Qwen 3.5 Plus and 3.6 Plus appear.
+- [ ] Unset credentials and verify the provider/catalog hides correctly.
+
+### Acceptance criteria
+- [ ] New curated models are present when credentials exist.
+- [ ] Catalog visibility still respects credential gating.
+- [ ] Targeted tests pass.
+
+## #960 — [QA] Verify patch 'did you mean?' suggestions
+
+State: open
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/960
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `15abf4ed8` — add `did you mean?` feedback when patch fails to match
+- `5e6427a42` — gate it to true no-match cases and extend to v4a / skill_manage
+
+### Targeted tests
+- `tests/tools/test_fuzzy_match.py`
+
+### Tasks
+- [ ] Intentionally run a replace/patch with a near-miss `old_string`.
+- [ ] Verify the tool suggests a useful nearby line/context.
+- [ ] Verify suggestions only appear on true no-match failures.
+- [ ] Verify the behavior also works via file tools, v4a patching, and skill_manage.
+
+### Acceptance criteria
+- [ ] Suggestion quality is helpful, not noisy.
+- [ ] Suggestions are correctly gated to no-match cases.
+- [ ] Targeted tests pass.
+
+## #961 — [QA] Verify web dashboard update/restart action buttons
+
+State: closed
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/961
+
+### Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+### Commits
+- `fc21c1420` — add buttons to update Hermes and restart gateway
+
+### Files touched
+- `web/src/pages/StatusPage.tsx`
+- `web/src/lib/api.ts`
+- `web/src/i18n/en.ts`
+
+### Tasks
+- [ ] Open the Web UI status page and verify both buttons are present.
+- [ ] Click Restart Gateway in a safe environment and verify running/output/success-or-failure states render.
+- [ ] Click Update Hermes and verify the same action lifecycle.
+- [ ] Verify the page remains responsive while actions are running.
+
+### Acceptance criteria
+- [ ] Both action buttons are present and wired.
+- [ ] Action status polling and result rendering work end-to-end.
+- [ ] Manual evidence is attached in the issue.
+
+## #962 — [QA] Verify hardcoded-home path guard on burn/921 branch
+
+State: closed
+URL: https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/issues/962
+
+### Branch / checkout
+- Validate specifically on `burn/921-poka-yoke-hardcoded-paths` (not upstream/main).
+
+### Commits
+- `5dcb90531` — Poka-yoke: prevent hardcoded home-directory paths
+
+### Targeted tests
+- `tests/test_path_guard.py`
+
+### Tasks
+- [ ] Verify hardcoded `/Users/...` paths are rejected.
+- [ ] Verify hardcoded `~/.hermes/...` paths are rejected in guarded contexts.
+- [ ] Verify valid relative paths still pass.
+- [ ] Verify appropriate absolute paths still pass where intended.
+- [ ] Verify linting catches violations in non-test files.
+
+### Acceptance criteria
+- [ ] Guard blocks the dangerous patterns and preserves allowed ones.
+- [ ] Targeted tests pass.

plugins/memory/holographic/__init__.py

@@ -26,7 +26,6 @@ from agent.memory_provider import MemoryProvider
 from tools.registry import tool_error
 from .store import MemoryStore
 from .retrieval import FactRetriever
-from .observations import ObservationSynthesizer
 
 logger = logging.getLogger(__name__)
 
@@ -38,29 +37,28 @@ logger = logging.getLogger(__name__)
 FACT_STORE_SCHEMA = {
     "name": "fact_store",
     "description": (
-        "Deep structured memory with algebraic reasoning and grounded observation synthesis. "
+        "Deep structured memory with algebraic reasoning. "
         "Use alongside the memory tool — memory for always-on context, "
-        "fact_store for deep recall, compositional queries, and higher-order observations.\n\n"
+        "fact_store for deep recall and compositional queries.\n\n"
         "ACTIONS (simple → powerful):\n"
         "• add — Store a fact the user would expect you to remember.\n"
         "• search — Keyword lookup ('editor config', 'deploy process').\n"
         "• probe — Entity recall: ALL facts about a person/thing.\n"
         "• related — What connects to an entity? Structural adjacency.\n"
         "• reason — Compositional: facts connected to MULTIPLE entities simultaneously.\n"
-        "• observe — Synthesized higher-order observations backed by supporting facts.\n"
         "• contradict — Memory hygiene: find facts making conflicting claims.\n"
         "• update/remove/list — CRUD operations.\n\n"
-        "IMPORTANT: Before answering questions about the user, ALWAYS probe/reason/observe first."
+        "IMPORTANT: Before answering questions about the user, ALWAYS probe or reason first."
     ),
     "parameters": {
         "type": "object",
         "properties": {
             "action": {
                 "type": "string",
-                "enum": ["add", "search", "probe", "related", "reason", "observe", "contradict", "update", "remove", "list"],
+                "enum": ["add", "search", "probe", "related", "reason", "contradict", "update", "remove", "list"],
             },
             "content": {"type": "string", "description": "Fact content (required for 'add')."},
-            "query": {"type": "string", "description": "Search query (required for 'search'/'observe')."},
+            "query": {"type": "string", "description": "Search query (required for 'search')."},
             "entity": {"type": "string", "description": "Entity name for 'probe'/'related'."},
             "entities": {"type": "array", "items": {"type": "string"}, "description": "Entity names for 'reason'."},
             "fact_id": {"type": "integer", "description": "Fact ID for 'update'/'remove'."},
@@ -68,12 +66,6 @@ FACT_STORE_SCHEMA = {
             "tags": {"type": "string", "description": "Comma-separated tags."},
             "trust_delta": {"type": "number", "description": "Trust adjustment for 'update'."},
             "min_trust": {"type": "number", "description": "Minimum trust filter (default: 0.3)."},
-            "min_confidence": {"type": "number", "description": "Minimum observation confidence (default: 0.6)."},
-            "observation_type": {
-                "type": "string",
-                "enum": ["recurring_preference", "stable_direction", "behavioral_pattern"],
-                "description": "Optional observation type filter for 'observe'.",
-            },
             "limit": {"type": "integer", "description": "Max results (default: 10)."},
         },
         "required": ["action"],
@@ -126,9 +118,7 @@ class HolographicMemoryProvider(MemoryProvider):
         self._config = config or _load_plugin_config()
         self._store = None
         self._retriever = None
-        self._observation_synth = None
         self._min_trust = float(self._config.get("min_trust_threshold", 0.3))
-        self._observation_min_confidence = float(self._config.get("observation_min_confidence", 0.6))
 
     @property
     def name(self) -> str:
@@ -187,7 +177,6 @@ class HolographicMemoryProvider(MemoryProvider):
             hrr_weight=hrr_weight,
             hrr_dim=hrr_dim,
         )
-        self._observation_synth = ObservationSynthesizer(self._store)
         self._session_id = session_id
 
     def system_prompt_block(self) -> str:
@@ -204,76 +193,30 @@ class HolographicMemoryProvider(MemoryProvider):
                 "# Holographic Memory\n"
                 "Active. Empty fact store — proactively add facts the user would expect you to remember.\n"
                 "Use fact_store(action='add') to store durable structured facts about people, projects, preferences, decisions.\n"
-                "Use fact_store(action='observe') to synthesize higher-order observations with evidence.\n"
                 "Use fact_feedback to rate facts after using them (trains trust scores)."
             )
         return (
             f"# Holographic Memory\n"
             f"Active. {total} facts stored with entity resolution and trust scoring.\n"
-            f"Use fact_store to search, probe entities, reason across entities, or synthesize observations.\n"
+            f"Use fact_store to search, probe entities, reason across entities, or add facts.\n"
             f"Use fact_feedback to rate facts after using them (trains trust scores)."
         )
 
     def prefetch(self, query: str, *, session_id: str = "") -> str:
-        if not query:
+        if not self._retriever or not query:
             return ""
-
-        parts = []
-        raw_results = []
         try:
-            if self._retriever:
-                raw_results = self._retriever.search(query, min_trust=self._min_trust, limit=5)
-        except Exception as e:
-            logger.debug("Holographic prefetch fact search failed: %s", e)
-            raw_results = []
-
-        observations = []
-        try:
-            if self._observation_synth:
-                observations = self._observation_synth.observe(
-                    query,
-                    min_confidence=self._observation_min_confidence,
-                    limit=3,
-                    refresh=True,
-                )
-        except Exception as e:
-            logger.debug("Holographic prefetch observation search failed: %s", e)
-            observations = []
-
-        if not raw_results and observations:
-            seen_fact_ids = set()
-            evidence_backfill = []
-            for observation in observations:
-                for evidence in observation.get("evidence", []):
-                    fact_id = evidence.get("fact_id")
-                    if fact_id in seen_fact_ids:
-                        continue
-                    seen_fact_ids.add(fact_id)
-                    evidence_backfill.append(evidence)
-            raw_results = evidence_backfill[:5]
-
-        if raw_results:
+            results = self._retriever.search(query, min_trust=self._min_trust, limit=5)
+            if not results:
+                return ""
             lines = []
-            for r in raw_results:
+            for r in results:
                 trust = r.get("trust_score", r.get("trust", 0))
                 lines.append(f"- [{trust:.1f}] {r.get('content', '')}")
-            parts.append("## Holographic Memory\n" + "\n".join(lines))
-
-        if observations:
-            lines = []
-            for observation in observations:
-                evidence_ids = ", ".join(
-                    f"#{item['fact_id']}" for item in observation.get("evidence", [])[:3]
-                ) or "none"
-                lines.append(
-                    f"- [{observation.get('confidence', 0.0):.2f}] "
-                    f"{observation.get('observation_type', 'observation')}: "
-                    f"{observation.get('summary', '')} "
-                    f"(evidence: {evidence_ids})"
-                )
-            parts.append("## Holographic Observations\n" + "\n".join(lines))
-
-        return "\n\n".join(parts)
+            return "## Holographic Memory\n" + "\n".join(lines)
+        except Exception as e:
+            logger.debug("Holographic prefetch failed: %s", e)
+            return ""
 
     def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
         # Holographic memory stores explicit facts via tools, not auto-sync.
@@ -309,7 +252,6 @@ class HolographicMemoryProvider(MemoryProvider):
     def shutdown(self) -> None:
         self._store = None
         self._retriever = None
-        self._observation_synth = None
 
     # -- Tool handlers -------------------------------------------------------
 
@@ -363,19 +305,6 @@ class HolographicMemoryProvider(MemoryProvider):
                 )
                 return json.dumps({"results": results, "count": len(results)})
 
-            elif action == "observe":
-                synthesizer = self._observation_synth
-                if not synthesizer:
-                    return tool_error("Observation synthesizer is not initialized")
-                observations = synthesizer.observe(
-                    args.get("query", ""),
-                    observation_type=args.get("observation_type"),
-                    min_confidence=float(args.get("min_confidence", self._observation_min_confidence)),
-                    limit=int(args.get("limit", 10)),
-                    refresh=True,
-                )
-                return json.dumps({"observations": observations, "count": len(observations)})
-
             elif action == "contradict":
                 results = retriever.contradict(
                     category=args.get("category"),

plugins/memory/holographic/observations.py

@@ -1,249 +0,0 @@
-"""Higher-order observation synthesis for holographic memory.
-
-Builds grounded observations from accumulated facts and keeps them in a
-separate retrieval layer with explicit evidence links back to supporting facts.
-"""
-
-from __future__ import annotations
-
-import re
-from typing import Any
-
-from .store import MemoryStore
-
-_TOKEN_RE = re.compile(r"[a-z0-9_]+")
-_HIGHER_ORDER_CUES = {
-    "prefer",
-    "preference",
-    "preferences",
-    "style",
-    "pattern",
-    "patterns",
-    "behavior",
-    "behaviour",
-    "habit",
-    "habits",
-    "workflow",
-    "direction",
-    "trajectory",
-    "strategy",
-    "tend",
-    "usually",
-}
-
-_OBSERVATION_PATTERNS = [
-    {
-        "observation_type": "recurring_preference",
-        "subject": "communication_style",
-        "categories": {"user_pref", "general"},
-        "labels": {
-            "concise": ["concise", "terse", "brief", "short", "no fluff"],
-            "result_first": ["result-only", "result only", "outcome only", "quick", "quickly"],
-            "silent_ops": ["silent", "no status", "no repetitive status", "no questions"],
-        },
-        "summary_prefix": "Recurring preference",
-    },
-    {
-        "observation_type": "stable_direction",
-        "subject": "project_direction",
-        "categories": {"project", "general", "tool"},
-        "labels": {
-            "local_first": ["local-first", "local first", "local-only", "local only", "ollama", "own hardware"],
-            "gitea_first": ["gitea-first", "gitea first", "forge", "pull request", "pr flow", "issue flow"],
-            "ansible": ["ansible", "playbook", "role", "deploy via ansible"],
-        },
-        "summary_prefix": "Stable direction",
-    },
-    {
-        "observation_type": "behavioral_pattern",
-        "subject": "operator_workflow",
-        "categories": {"general", "project", "tool", "user_pref"},
-        "labels": {
-            "commit_early": ["commit early", "commits early", "commit after", "wip commit"],
-            "pr_first": ["open pr", "push a pr", "pull request", "pr immediately", "create pr"],
-            "dedup_guard": ["no dupes", "no duplicates", "avoid duplicate", "existing pr"],
-        },
-        "summary_prefix": "Behavioral pattern",
-    },
-]
-
-_TYPE_QUERY_HINTS = {
-    "recurring_preference": {"prefer", "preference", "style", "communication", "likes", "wants"},
-    "stable_direction": {"direction", "trajectory", "strategy", "project", "roadmap", "moving"},
-    "behavioral_pattern": {"pattern", "behavior", "workflow", "habit", "operator", "agent", "usually"},
-}
-
-
-class ObservationSynthesizer:
-    """Synthesizes grounded observations from facts and retrieves them by query."""
-
-    def __init__(self, store: MemoryStore):
-        self.store = store
-
-    def synthesize(
-        self,
-        *,
-        persist: bool = True,
-        min_confidence: float = 0.6,
-        limit: int = 10,
-    ) -> list[dict[str, Any]]:
-        facts = self.store.list_facts(min_trust=0.0, limit=1000)
-        observations: list[dict[str, Any]] = []
-
-        for pattern in _OBSERVATION_PATTERNS:
-            candidate = self._build_candidate(pattern, facts, min_confidence=min_confidence)
-            if not candidate:
-                continue
-
-            if persist:
-                candidate["observation_id"] = self.store.upsert_observation(
-                    candidate["observation_type"],
-                    candidate["subject"],
-                    candidate["summary"],
-                    candidate["confidence"],
-                    candidate["evidence_fact_ids"],
-                    metadata=candidate["metadata"],
-                )
-
-            candidate["evidence"] = self._expand_evidence(candidate["evidence_fact_ids"])
-            candidate["evidence_count"] = len(candidate["evidence"])
-            candidate.pop("evidence_fact_ids", None)
-            observations.append(candidate)
-
-        observations.sort(
-            key=lambda item: (item["confidence"], item.get("evidence_count", 0)),
-            reverse=True,
-        )
-        return observations[:limit]
-
-    def observe(
-        self,
-        query: str = "",
-        *,
-        observation_type: str | None = None,
-        min_confidence: float = 0.6,
-        limit: int = 10,
-        refresh: bool = True,
-    ) -> list[dict[str, Any]]:
-        if refresh:
-            self.synthesize(persist=True, min_confidence=min_confidence, limit=limit)
-
-        observations = self.store.list_observations(
-            observation_type=observation_type,
-            min_confidence=min_confidence,
-            limit=max(limit * 4, 20),
-        )
-        if not observations:
-            return []
-
-        if not query:
-            return observations[:limit]
-
-        query_tokens = self._tokenize(query)
-        is_higher_order = bool(query_tokens & _HIGHER_ORDER_CUES)
-        ranked: list[dict[str, Any]] = []
-
-        for item in observations:
-            searchable = " ".join(
-                [
-                    item.get("summary", ""),
-                    item.get("subject", ""),
-                    item.get("observation_type", ""),
-                    " ".join(item.get("metadata", {}).get("labels", [])),
-                ]
-            )
-            overlap = self._overlap_score(query_tokens, self._tokenize(searchable))
-            type_bonus = self._type_bonus(query_tokens, item.get("observation_type", ""))
-            if overlap <= 0 and type_bonus <= 0 and not is_higher_order:
-                continue
-            ranked_item = dict(item)
-            ranked_item["score"] = round(item.get("confidence", 0.0) + overlap + type_bonus, 3)
-            ranked.append(ranked_item)
-
-        if not ranked and is_higher_order:
-            ranked = [
-                {**item, "score": round(float(item.get("confidence", 0.0)), 3)}
-                for item in observations
-            ]
-
-        ranked.sort(
-            key=lambda item: (item.get("score", 0.0), item.get("confidence", 0.0), item.get("evidence_count", 0)),
-            reverse=True,
-        )
-        return ranked[:limit]
-
-    def _build_candidate(
-        self,
-        pattern: dict[str, Any],
-        facts: list[dict[str, Any]],
-        *,
-        min_confidence: float,
-    ) -> dict[str, Any] | None:
-        matched_fact_ids: set[int] = set()
-        matched_labels: dict[str, set[int]] = {label: set() for label in pattern["labels"]}
-
-        for fact in facts:
-            if fact.get("category") not in pattern["categories"]:
-                continue
-            haystack = f"{fact.get('content', '')} {fact.get('tags', '')}".lower()
-            local_match = False
-            for label, keywords in pattern["labels"].items():
-                if any(keyword in haystack for keyword in keywords):
-                    matched_labels[label].add(int(fact["fact_id"]))
-                    local_match = True
-            if local_match:
-                matched_fact_ids.add(int(fact["fact_id"]))
-
-        if len(matched_fact_ids) < 2:
-            return None
-
-        active_labels = sorted(label for label, ids in matched_labels.items() if ids)
-        confidence = min(0.95, 0.35 + 0.12 * len(matched_fact_ids) + 0.08 * len(active_labels))
-        confidence = round(confidence, 3)
-        if confidence < min_confidence:
-            return None
-
-        label_summary = ", ".join(label.replace("_", "-") for label in active_labels)
-        subject_text = pattern["subject"].replace("_", " ")
-        summary = (
-            f"{pattern['summary_prefix']}: {subject_text} trends toward {label_summary} "
-            f"based on {len(matched_fact_ids)} supporting facts."
-        )
-        return {
-            "observation_type": pattern["observation_type"],
-            "subject": pattern["subject"],
-            "summary": summary,
-            "confidence": confidence,
-            "metadata": {
-                "labels": active_labels,
-                "evidence_count": len(matched_fact_ids),
-            },
-            "evidence_fact_ids": sorted(matched_fact_ids),
-        }
-
-    def _expand_evidence(self, fact_ids: list[int]) -> list[dict[str, Any]]:
-        facts_by_id = {
-            fact["fact_id"]: fact
-            for fact in self.store.list_facts(min_trust=0.0, limit=1000)
-        }
-        return [facts_by_id[fact_id] for fact_id in fact_ids if fact_id in facts_by_id]
-
-    @staticmethod
-    def _tokenize(text: str) -> set[str]:
-        return set(_TOKEN_RE.findall(text.lower()))
-
-    @staticmethod
-    def _overlap_score(query_tokens: set[str], text_tokens: set[str]) -> float:
-        if not query_tokens or not text_tokens:
-            return 0.0
-        overlap = query_tokens & text_tokens
-        if not overlap:
-            return 0.0
-        return round(len(overlap) / max(len(query_tokens), 1), 3)
-
-    @staticmethod
-    def _type_bonus(query_tokens: set[str], observation_type: str) -> float:
-        hints = _TYPE_QUERY_HINTS.get(observation_type, set())
-        if not hints:
-            return 0.0
-        return 0.25 if query_tokens & hints else 0.0

plugins/memory/holographic/store.py

@@ -3,7 +3,6 @@ SQLite-backed fact store with entity resolution and trust scoring.
 Single-user Hermes memory store plugin.
 """
 
-import json
 import re
 import sqlite3
 import threading
@@ -74,28 +73,6 @@ CREATE TABLE IF NOT EXISTS memory_banks (
     fact_count INTEGER DEFAULT 0,
     updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
 );
-
-CREATE TABLE IF NOT EXISTS observations (
-    observation_id   INTEGER PRIMARY KEY AUTOINCREMENT,
-    observation_type TEXT NOT NULL,
-    subject          TEXT NOT NULL,
-    summary          TEXT NOT NULL,
-    confidence       REAL DEFAULT 0.0,
-    metadata_json    TEXT DEFAULT '{}',
-    created_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-    updated_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-    UNIQUE(observation_type, subject)
-);
-
-CREATE TABLE IF NOT EXISTS observation_evidence (
-    observation_id INTEGER REFERENCES observations(observation_id) ON DELETE CASCADE,
-    fact_id        INTEGER REFERENCES facts(fact_id) ON DELETE CASCADE,
-    evidence_weight REAL DEFAULT 1.0,
-    PRIMARY KEY (observation_id, fact_id)
-);
-
-CREATE INDEX IF NOT EXISTS idx_observations_type ON observations(observation_type);
-CREATE INDEX IF NOT EXISTS idx_observations_confidence ON observations(confidence DESC);
 """
 
 # Trust adjustment constants
@@ -151,7 +128,6 @@ class MemoryStore:
     def _init_db(self) -> None:
         """Create tables, indexes, and triggers if they do not exist. Enable WAL mode."""
         self._conn.execute("PRAGMA journal_mode=WAL")
-        self._conn.execute("PRAGMA foreign_keys=ON")
         self._conn.executescript(_SCHEMA)
         # Migrate: add hrr_vector column if missing (safe for existing databases)
         columns = {row[1] for row in self._conn.execute("PRAGMA table_info(facts)").fetchall()}
@@ -370,115 +346,6 @@ class MemoryStore:
             rows = self._conn.execute(sql, params).fetchall()
             return [self._row_to_dict(r) for r in rows]
 
-    def upsert_observation(
-        self,
-        observation_type: str,
-        subject: str,
-        summary: str,
-        confidence: float,
-        evidence_fact_ids: list[int],
-        metadata: dict | None = None,
-    ) -> int:
-        """Create or update a synthesized observation and its evidence links."""
-        with self._lock:
-            metadata_json = json.dumps(metadata or {}, sort_keys=True)
-            self._conn.execute(
-                """
-                INSERT INTO observations (
-                    observation_type, subject, summary, confidence, metadata_json
-                )
-                VALUES (?, ?, ?, ?, ?)
-                ON CONFLICT(observation_type, subject) DO UPDATE SET
-                    summary = excluded.summary,
-                    confidence = excluded.confidence,
-                    metadata_json = excluded.metadata_json,
-                    updated_at = CURRENT_TIMESTAMP
-                """,
-                (observation_type, subject, summary, confidence, metadata_json),
-            )
-            row = self._conn.execute(
-                """
-                SELECT observation_id
-                FROM observations
-                WHERE observation_type = ? AND subject = ?
-                """,
-                (observation_type, subject),
-            ).fetchone()
-            observation_id = int(row["observation_id"])
-
-            self._conn.execute(
-                "DELETE FROM observation_evidence WHERE observation_id = ?",
-                (observation_id,),
-            )
-            unique_fact_ids = sorted({int(fid) for fid in evidence_fact_ids})
-            if unique_fact_ids:
-                self._conn.executemany(
-                    """
-                    INSERT OR IGNORE INTO observation_evidence (observation_id, fact_id)
-                    VALUES (?, ?)
-                    """,
-                    [(observation_id, fact_id) for fact_id in unique_fact_ids],
-                )
-            self._conn.commit()
-            return observation_id
-
-    def list_observations(
-        self,
-        observation_type: str | None = None,
-        min_confidence: float = 0.0,
-        limit: int = 50,
-    ) -> list[dict]:
-        """List synthesized observations with expanded supporting evidence."""
-        with self._lock:
-            params: list = [min_confidence]
-            observation_clause = ""
-            if observation_type is not None:
-                observation_clause = "AND observation_type = ?"
-                params.append(observation_type)
-            params.append(limit)
-            rows = self._conn.execute(
-                f"""
-                SELECT observation_id, observation_type, subject, summary, confidence,
-                       metadata_json, created_at, updated_at,
-                       (
-                           SELECT COUNT(*)
-                           FROM observation_evidence oe
-                           WHERE oe.observation_id = observations.observation_id
-                       ) AS evidence_count
-                FROM observations
-                WHERE confidence >= ?
-                  {observation_clause}
-                ORDER BY confidence DESC, updated_at DESC
-                LIMIT ?
-                """,
-                params,
-            ).fetchall()
-
-            results = []
-            for row in rows:
-                item = dict(row)
-                try:
-                    item["metadata"] = json.loads(item.pop("metadata_json") or "{}")
-                except json.JSONDecodeError:
-                    item["metadata"] = {}
-                item["evidence"] = self._get_observation_evidence(int(item["observation_id"]))
-                results.append(item)
-            return results
-
-    def _get_observation_evidence(self, observation_id: int) -> list[dict]:
-        rows = self._conn.execute(
-            """
-            SELECT f.fact_id, f.content, f.category, f.tags, f.trust_score,
-                   f.retrieval_count, f.helpful_count, f.created_at, f.updated_at
-            FROM observation_evidence oe
-            JOIN facts f ON f.fact_id = oe.fact_id
-            WHERE oe.observation_id = ?
-            ORDER BY f.trust_score DESC, f.updated_at DESC
-            """,
-            (observation_id,),
-        ).fetchall()
-        return [self._row_to_dict(row) for row in rows]
-
     def record_feedback(self, fact_id: int, helpful: bool) -> dict:
         """Record user feedback and adjust trust asymmetrically.
 

scripts/morning_review_packet.py

@@ -0,0 +1,301 @@
+#!/usr/bin/env python3
+"""Build a morning review packet from a Gitea epic and its child QA issues.
+
+This script fetches a parent epic plus its sub-issues, extracts the structured
+sections from each QA issue body, and renders a single markdown packet suitable
+for morning review.
+
+Usage:
+    python scripts/morning_review_packet.py --epic-number 949
+    python scripts/morning_review_packet.py --epic-number 949 --children 950-962
+    python scripts/morning_review_packet.py --epic-number 949 --output docs/review_packets/hermes-harness-2026-04-21.md
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import re
+import urllib.request
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Iterable
+
+DEFAULT_BASE_URL = "https://forge.alexanderwhitestone.com"
+DEFAULT_OWNER = "Timmy_Foundation"
+DEFAULT_REPO = "hermes-agent"
+DEFAULT_TOKEN_PATH = Path.home() / ".config" / "gitea" / "token"
+
+
+@dataclass(frozen=True)
+class CommitEvidence:
+    sha: str
+    summary: str
+
+
+@dataclass
+class ReviewIssue:
+    number: int
+    title: str
+    state: str
+    url: str
+    comments: int = 0
+    parent_issue: int | None = None
+    checkout_notes: list[str] = field(default_factory=list)
+    commits: list[CommitEvidence] = field(default_factory=list)
+    targeted_tests: list[str] = field(default_factory=list)
+    files_touched: list[str] = field(default_factory=list)
+    tasks: list[str] = field(default_factory=list)
+    acceptance_criteria: list[str] = field(default_factory=list)
+
+
+def parse_issue_number_spec(spec: str) -> list[int]:
+    """Parse a comma-separated issue list like ``950-952,955,962``."""
+    numbers: list[int] = []
+    seen: set[int] = set()
+    for chunk in (part.strip() for part in spec.split(",")):
+        if not chunk:
+            continue
+        if "-" in chunk:
+            start_str, end_str = (part.strip() for part in chunk.split("-", 1))
+            start = int(start_str)
+            end = int(end_str)
+            if end < start:
+                raise ValueError(f"Invalid descending issue range: {chunk}")
+            for number in range(start, end + 1):
+                if number not in seen:
+                    numbers.append(number)
+                    seen.add(number)
+        else:
+            number = int(chunk)
+            if number not in seen:
+                numbers.append(number)
+                seen.add(number)
+    return numbers
+
+
+def _parse_sections(body: str) -> dict[str, list[str]]:
+    sections: dict[str, list[str]] = {}
+    current: str | None = None
+    for raw_line in body.splitlines():
+        line = raw_line.rstrip()
+        if line.startswith("## "):
+            current = line[3:].strip()
+            sections[current] = []
+            continue
+        if current is not None:
+            sections[current].append(line)
+    return sections
+
+
+def _clean_bullet(line: str) -> str | None:
+    stripped = line.strip()
+    if not stripped:
+        return None
+    stripped = re.sub(r"^-\s*\[(?: |x|X)\]\s*", "", stripped)
+    stripped = re.sub(r"^-\s*", "", stripped)
+    return stripped.strip() or None
+
+
+def _extract_bullets(lines: Iterable[str]) -> list[str]:
+    items: list[str] = []
+    for line in lines:
+        cleaned = _clean_bullet(line)
+        if cleaned:
+            items.append(cleaned)
+    return items
+
+
+def _extract_parent_issue(body: str, sections: dict[str, list[str]]) -> int | None:
+    parent_lines = sections.get("Parent", [])
+    for line in parent_lines:
+        match = re.search(r"#(\d+)", line)
+        if match:
+            return int(match.group(1))
+    match = re.search(r"Linked to Epic\s+#(\d+)", body, flags=re.IGNORECASE)
+    if match:
+        return int(match.group(1))
+    return None
+
+
+def _extract_commits(lines: Iterable[str]) -> list[CommitEvidence]:
+    commits: list[CommitEvidence] = []
+    for item in _extract_bullets(lines):
+        match = re.match(r"`([^`]+)`\s*(.*)", item)
+        if match:
+            commits.append(CommitEvidence(sha=match.group(1).strip(), summary=match.group(2).strip()))
+        else:
+            commits.append(CommitEvidence(sha="", summary=item))
+    return commits
+
+
+def _strip_backticks(items: Iterable[str]) -> list[str]:
+    cleaned: list[str] = []
+    for item in items:
+        cleaned.append(item.replace("`", "").strip())
+    return cleaned
+
+
+def discover_child_issue_numbers(epic_body: str) -> list[int]:
+    """Discover sub-issue numbers from an epic body."""
+    sections = _parse_sections(epic_body)
+    sub_lines = sections.get("Sub-issues")
+    if not sub_lines:
+        return []
+    numbers: list[int] = []
+    seen: set[int] = set()
+    for line in sub_lines:
+        for match in re.finditer(r"#(\d+)", line):
+            number = int(match.group(1))
+            if number not in seen:
+                numbers.append(number)
+                seen.add(number)
+    return numbers
+
+
+def parse_child_issue(issue: dict) -> ReviewIssue:
+    body = issue.get("body") or ""
+    sections = _parse_sections(body)
+    commit_lines = sections.get("Commits landed today", []) or sections.get("Commit landed today", [])
+
+    return ReviewIssue(
+        number=int(issue["number"]),
+        title=issue.get("title") or "",
+        state=(issue.get("state") or "unknown").lower(),
+        url=issue.get("html_url") or issue.get("url") or "",
+        comments=int(issue.get("comments") or 0),
+        parent_issue=_extract_parent_issue(body, sections),
+        checkout_notes=_extract_bullets(sections.get("Branch / checkout", [])),
+        commits=_extract_commits(commit_lines),
+        targeted_tests=_strip_backticks(_extract_bullets(sections.get("Targeted tests", []))),
+        files_touched=_strip_backticks(_extract_bullets(sections.get("Files touched", []))),
+        tasks=_extract_bullets(sections.get("Tasks", [])),
+        acceptance_criteria=_extract_bullets(sections.get("Acceptance Criteria", [])),
+    )
+
+
+def build_packet_markdown(epic_issue: dict, child_issues: list[ReviewIssue]) -> str:
+    title = epic_issue.get("title") or f"Epic #{epic_issue.get('number')}"
+    url = epic_issue.get("html_url") or epic_issue.get("url") or ""
+    body = epic_issue.get("body") or ""
+    children = sorted(child_issues, key=lambda item: item.number)
+
+    lines: list[str] = []
+    lines.append("# Morning Review Packet")
+    lines.append("")
+    lines.append(f"Source epic: [{title}]({url})")
+    lines.append("")
+    lines.append("## Epic context")
+    lines.append("")
+    lines.append(title)
+    lines.append("")
+    for line in body.splitlines():
+        if line.strip():
+            lines.append(line)
+        else:
+            lines.append("")
+    lines.append("")
+    lines.append("## Summary")
+    lines.append("")
+    lines.append("| Issue | State | Commits | Tests |")
+    lines.append("| --- | --- | --- | --- |")
+    for child in children:
+        lines.append(
+            f"| #{child.number} | {child.state} | {len(child.commits)} | {len(child.targeted_tests)} |"
+        )
+    lines.append("")
+
+    for child in children:
+        lines.append(f"## #{child.number} — {child.title}")
+        lines.append("")
+        lines.append(f"State: {child.state}")
+        lines.append(f"URL: {child.url}")
+        lines.append("")
+        if child.checkout_notes:
+            lines.append("### Branch / checkout")
+            for note in child.checkout_notes:
+                lines.append(f"- {note}")
+            lines.append("")
+        if child.commits:
+            lines.append("### Commits")
+            for commit in child.commits:
+                if commit.sha:
+                    lines.append(f"- `{commit.sha}` — {commit.summary}")
+                else:
+                    lines.append(f"- {commit.summary}")
+            lines.append("")
+        if child.targeted_tests:
+            lines.append("### Targeted tests")
+            for test_path in child.targeted_tests:
+                lines.append(f"- `{test_path}`")
+            lines.append("")
+        if child.files_touched:
+            lines.append("### Files touched")
+            for file_path in child.files_touched:
+                lines.append(f"- `{file_path}`")
+            lines.append("")
+        if child.tasks:
+            lines.append("### Tasks")
+            for task in child.tasks:
+                lines.append(f"- [ ] {task}")
+            lines.append("")
+        if child.acceptance_criteria:
+            lines.append("### Acceptance criteria")
+            for item in child.acceptance_criteria:
+                lines.append(f"- [ ] {item}")
+            lines.append("")
+
+    return "\n".join(lines).rstrip() + "\n"
+
+
+def _resolve_token(explicit_token: str | None = None) -> str:
+    if explicit_token:
+        return explicit_token.strip()
+    env_token = os.getenv("GITEA_TOKEN")
+    if env_token:
+        return env_token.strip()
+    if DEFAULT_TOKEN_PATH.exists():
+        return DEFAULT_TOKEN_PATH.read_text().strip()
+    raise FileNotFoundError(f"No Gitea token found. Set GITEA_TOKEN or create {DEFAULT_TOKEN_PATH}")
+
+
+def fetch_issue(base_url: str, owner: str, repo: str, number: int, token: str) -> dict:
+    url = f"{base_url.rstrip('/')}/api/v1/repos/{owner}/{repo}/issues/{number}"
+    request = urllib.request.Request(url, headers={"Authorization": f"token {token}"})
+    with urllib.request.urlopen(request, timeout=30) as response:
+        return json.loads(response.read().decode())
+
+
+def collect_child_issues(base_url: str, owner: str, repo: str, epic_issue: dict, token: str, children_spec: str | None = None) -> list[dict]:
+    numbers = parse_issue_number_spec(children_spec) if children_spec else discover_child_issue_numbers(epic_issue.get("body") or "")
+    return [fetch_issue(base_url, owner, repo, number, token) for number in numbers]
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(description="Build a markdown morning review packet from a Gitea epic")
+    parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
+    parser.add_argument("--owner", default=DEFAULT_OWNER)
+    parser.add_argument("--repo", default=DEFAULT_REPO)
+    parser.add_argument("--epic-number", type=int, required=True)
+    parser.add_argument("--children", help="Explicit issue list/ranges, e.g. 950-962")
+    parser.add_argument("--token", help="Gitea token (defaults to GITEA_TOKEN or ~/.config/gitea/token)")
+    parser.add_argument("--output", help="Write markdown packet to this path instead of stdout")
+    args = parser.parse_args(argv)
+
+    token = _resolve_token(args.token)
+    epic_issue = fetch_issue(args.base_url, args.owner, args.repo, args.epic_number, token)
+    child_issue_dicts = collect_child_issues(args.base_url, args.owner, args.repo, epic_issue, token, args.children)
+    packet = build_packet_markdown(epic_issue, [parse_child_issue(issue) for issue in child_issue_dicts])
+
+    if args.output:
+        output_path = Path(args.output)
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+        output_path.write_text(packet)
+    else:
+        print(packet, end="")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

tests/plugins/memory/test_holographic_observations.py

@@ -1,96 +0,0 @@
-import json
-
-import pytest
-
-from plugins.memory.holographic import HolographicMemoryProvider
-from plugins.memory.holographic.store import MemoryStore
-
-
-@pytest.fixture()
-def store(tmp_path):
-    db_path = tmp_path / "memory.db"
-    s = MemoryStore(db_path=str(db_path), default_trust=0.5)
-    yield s
-    s.close()
-
-
-@pytest.fixture()
-def provider(tmp_path):
-    p = HolographicMemoryProvider(
-        config={
-            "db_path": str(tmp_path / "memory.db"),
-            "default_trust": 0.5,
-        }
-    )
-    p.initialize(session_id="test-session")
-    yield p
-    if p._store:
-        p._store.close()
-
-
-class TestObservationSynthesis:
-    def test_observe_action_persists_observation_with_evidence_links(self, provider):
-        fact_ids = [
-            provider._store.add_fact('User prefers concise status updates', category='user_pref'),
-            provider._store.add_fact('User wants result-only replies with no fluff', category='user_pref'),
-        ]
-
-        result = json.loads(
-            provider.handle_tool_call(
-                'fact_store',
-                {
-                    'action': 'observe',
-                    'query': 'What communication style does the user prefer?',
-                    'limit': 5,
-                },
-            )
-        )
-
-        assert result['count'] == 1
-        observation = result['observations'][0]
-        assert observation['observation_type'] == 'recurring_preference'
-        assert observation['confidence'] >= 0.6
-        assert sorted(item['fact_id'] for item in observation['evidence']) == sorted(fact_ids)
-
-        stored = provider._store.list_observations(limit=10)
-        assert len(stored) == 1
-        assert stored[0]['observation_type'] == 'recurring_preference'
-        assert stored[0]['evidence_count'] == 2
-        assert len(provider._store.list_facts(limit=10)) == 2
-
-    def test_observe_action_synthesizes_three_observation_types(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-        provider._store.add_fact('User wants result-only communication', category='user_pref')
-        provider._store.add_fact('Project is moving to a local-first deployment model', category='project')
-        provider._store.add_fact('Project direction stays Gitea-first for issue and PR flow', category='project')
-        provider._store.add_fact('Operator always commits early before moving on', category='general')
-        provider._store.add_fact('Operator pushes a PR immediately after each meaningful fix', category='general')
-
-        result = json.loads(provider.handle_tool_call('fact_store', {'action': 'observe', 'limit': 10}))
-        types = {item['observation_type'] for item in result['observations']}
-
-        assert {'recurring_preference', 'stable_direction', 'behavioral_pattern'} <= types
-
-    def test_single_fact_does_not_create_overconfident_observation(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-
-        result = json.loads(
-            provider.handle_tool_call(
-                'fact_store',
-                {'action': 'observe', 'query': 'What does the user prefer?', 'limit': 5},
-            )
-        )
-
-        assert result['count'] == 0
-        assert provider._store.list_observations(limit=10) == []
-
-    def test_prefetch_surfaces_observations_as_separate_layer(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-        provider._store.add_fact('User wants result-only communication', category='user_pref')
-
-        prefetch = provider.prefetch('What communication style does the user prefer?')
-
-        assert '## Holographic Observations' in prefetch
-        assert '## Holographic Memory' in prefetch
-        assert 'recurring_preference' in prefetch
-        assert 'evidence' in prefetch.lower()

tests/test_morning_review_packet.py

@@ -0,0 +1,162 @@
+from pathlib import Path
+import sys
+
+SCRIPT_DIR = Path(__file__).resolve().parents[1] / "scripts"
+sys.path.insert(0, str(SCRIPT_DIR))
+
+import morning_review_packet as mrp
+
+
+EPIC_BODY = """Source: git log on upstream/main since 2026-04-21 00:00 EDT.
+
+## Success criteria
+- [ ] Every issue has a clear PASS / FAIL outcome.
+
+## Sub-issues
+- [ ] #950 [QA] Verify AI Gateway provider UX + attribution headers
+- [ ] #951 [QA] Verify transport abstraction + AnthropicTransport wiring
+- [x] #962 [QA] Verify hardcoded-home path guard on burn/921 branch
+"""
+
+
+CHILD_BODY_PLURAL = """## Parent
+#949
+
+## Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+## Commits landed today
+- `b11753879` attribution default_headers for ai-gateway provider
+- `700437440` curated picker with live pricing
+
+## Targeted tests
+- `tests/hermes_cli/test_ai_gateway_models.py`
+- `tests/run_agent/test_provider_attribution_headers.py`
+
+## Tasks
+- [ ] Verify the picker ordering.
+- [ ] Verify attribution headers.
+
+## Acceptance Criteria
+- [ ] Picker shows AI Gateway prominently.
+- [ ] Headers appear on OpenRouter calls.
+"""
+
+
+CHILD_BODY_SINGULAR = """## Parent
+#949
+
+## Branch / checkout
+- Validate on `upstream/main` or an equivalent synced checkout.
+
+## Commit landed today
+- `fc21c1420` add buttons to update Hermes and restart gateway
+
+## Files touched
+- `web/src/pages/StatusPage.tsx`
+- `web/src/lib/api.ts`
+- `web/src/i18n/en.ts`
+
+## Tasks
+- [ ] Open the Web UI status page and verify both buttons are present.
+- [ ] Click Restart Gateway in a safe environment.
+"""
+
+
+def test_discover_child_issue_numbers_from_epic_body():
+    assert mrp.discover_child_issue_numbers(EPIC_BODY) == [950, 951, 962]
+
+
+def test_parse_issue_number_spec_supports_ranges_and_lists():
+    assert mrp.parse_issue_number_spec("950-952,955,962") == [950, 951, 952, 955, 962]
+
+
+def test_parse_child_issue_extracts_structured_sections():
+    issue = {
+        "number": 950,
+        "title": "[QA] Verify AI Gateway provider UX + attribution headers",
+        "state": "open",
+        "html_url": "https://forge.example/950",
+        "comments": 0,
+        "body": CHILD_BODY_PLURAL,
+    }
+
+    parsed = mrp.parse_child_issue(issue)
+
+    assert parsed.number == 950
+    assert parsed.parent_issue == 949
+    assert parsed.checkout_notes == ["Validate on `upstream/main` or an equivalent synced checkout."]
+    assert [c.sha for c in parsed.commits] == ["b11753879", "700437440"]
+    assert parsed.targeted_tests == [
+        "tests/hermes_cli/test_ai_gateway_models.py",
+        "tests/run_agent/test_provider_attribution_headers.py",
+    ]
+    assert parsed.tasks == [
+        "Verify the picker ordering.",
+        "Verify attribution headers.",
+    ]
+    assert parsed.acceptance_criteria == [
+        "Picker shows AI Gateway prominently.",
+        "Headers appear on OpenRouter calls.",
+    ]
+
+
+def test_parse_child_issue_handles_singular_commit_heading_and_files_touched():
+    issue = {
+        "number": 961,
+        "title": "[QA] Verify web dashboard update/restart action buttons",
+        "state": "closed",
+        "html_url": "https://forge.example/961",
+        "comments": 16,
+        "body": CHILD_BODY_SINGULAR,
+    }
+
+    parsed = mrp.parse_child_issue(issue)
+
+    assert [c.sha for c in parsed.commits] == ["fc21c1420"]
+    assert parsed.files_touched == [
+        "web/src/pages/StatusPage.tsx",
+        "web/src/lib/api.ts",
+        "web/src/i18n/en.ts",
+    ]
+    assert parsed.tasks == [
+        "Open the Web UI status page and verify both buttons are present.",
+        "Click Restart Gateway in a safe environment.",
+    ]
+
+
+def test_build_packet_markdown_renders_summary_and_details():
+    epic_issue = {
+        "number": 949,
+        "title": "EPIC: Morning review packet — Hermes harness features landed 2026-04-21",
+        "state": "open",
+        "html_url": "https://forge.example/949",
+        "body": EPIC_BODY,
+    }
+    child_a = mrp.parse_child_issue({
+        "number": 950,
+        "title": "[QA] Verify AI Gateway provider UX + attribution headers",
+        "state": "open",
+        "html_url": "https://forge.example/950",
+        "comments": 0,
+        "body": CHILD_BODY_PLURAL,
+    })
+    child_b = mrp.parse_child_issue({
+        "number": 961,
+        "title": "[QA] Verify web dashboard update/restart action buttons",
+        "state": "closed",
+        "html_url": "https://forge.example/961",
+        "comments": 16,
+        "body": CHILD_BODY_SINGULAR,
+    })
+
+    markdown = mrp.build_packet_markdown(epic_issue, [child_a, child_b])
+
+    assert "# Morning Review Packet" in markdown
+    assert "EPIC: Morning review packet — Hermes harness features landed 2026-04-21" in markdown
+    assert "| #950 | open | 2 | 2 |" in markdown
+    assert "| #961 | closed | 1 | 0 |" in markdown
+    assert "## #950 — [QA] Verify AI Gateway provider UX + attribution headers" in markdown
+    assert "## #961 — [QA] Verify web dashboard update/restart action buttons" in markdown
+    assert "`b11753879` — attribution default_headers for ai-gateway provider" in markdown
+    assert "`web/src/pages/StatusPage.tsx`" in markdown