[EPIC-999/Phase I] The Mirror — formal spec extraction artifacts #107
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Rockachopa
Timmy
allegro
antigravity
bezalel
claude
claw-code
codex-agent
ezra
gemini
google
grok
groq
hermes
kimi
manus
perplexity
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Rockachopa
Timmy
allegro
antigravity
bezalel
claude
claw-code
codex-agent
ezra
gemini
google
grok
groq
hermes
kimi
manus
perplexity
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Reference: Timmy_Foundation/hermes-agent#107
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Part of EPIC-999: The Ouroboros Milestone.
This PR delivers Phase I artifacts for The Mirror:
docs/ouroboros/artifacts/module_inventory.json— 679 Python files, 298,705 lines, 232,401 SLOCdocs/ouroboros/artifacts/core_analysis.json— deep AST parse of 9 core modules (classes, methods, imports)docs/ouroboros/artifacts/import_graph.json— full import dependency graphdocs/ouroboros/specs/SPEC.md— high-level architecture, module specs, inferred side effects, coupling risks, and Phase II prep actionsKey findings surfaced in SPEC.md:
run_agent.pyis ~7k SLOC and contains the core loop, todo/memory interception, context compression, and trajectory saving — highest blast radius.cli.pyis ~6.5k SLOC and tightly couples UI (Rich/prompt_toolkit) with command dispatch.model_tools.pyholds a process-global_last_resolved_tool_names— a known concurrency risk.tools/registry.pyis imported by ALL tool files; schema generation happens at import time.Requested reviewers:
gateway/run.pyandmodel_tools.pyCloses Phase I of #106 (hermes-agent).
OPENAI_BASE_URL was written to .env AND config.yaml, creating a dual-source confusion. Users (especially Docker) would see the URL in .env and assume that's where all config lives, then wonder why LLM_MODEL in .env didn't work. Changes: - Remove all 27 save_env_value("OPENAI_BASE_URL", ...) calls across main.py, setup.py, and tools_config.py - Remove OPENAI_BASE_URL env var reading from runtime_provider.py, cli.py, models.py, and gateway/run.py - Remove LLM_MODEL/HERMES_MODEL env var reading from gateway/run.py and auxiliary_client.py — config.yaml model.default is authoritative - Vision base URL now saved to config.yaml auxiliary.vision.base_url (both setup wizard and tools_config paths) - Tests updated to set config values instead of env vars Convention enforced: .env is for SECRETS only (API keys). All other configuration (model names, base URLs, provider selection) lives exclusively in config.yaml.The delivery target parser uses split(':', 1) which only splits on the first colon. For the documented format platform:chat_id:thread_id (e.g. 'telegram:-1001234567890:17585'), thread_id gets munged into chat_id and is never extracted. Fix: split(':', 2) to correctly extract all three parts. Also fix to_string() to include thread_id for proper round-tripping. The downstream plumbing in _deliver_to_platform() already handles thread_id correctly (line 292-293) — it just never received a value.* fix: root-level provider in config.yaml no longer overrides model.provider load_cli_config() had a priority inversion: a stale root-level 'provider' key in config.yaml would OVERRIDE the canonical 'model.provider' set by 'hermes model'. The gateway reads model.provider directly from YAML and worked correctly, but 'hermes chat -q' and the interactive CLI went through the merge logic and picked up the stale root-level key. Fix: root-level provider/base_url are now only used as a fallback when model.provider/model.base_url is not set (never as an override). Also added _normalize_root_model_keys() to config.py load_config() and save_config() — migrates root-level provider/base_url into the model section and removes the root-level keys permanently. Reported by (≧▽≦) in Discord: opencode-go provider persisted as a root-level key and overrode the correct model.provider=openrouter, causing 401 errors. * fix(security): redact secrets from execute_code sandbox output The execute_code sandbox stripped env vars with secret-like names from the child process (preventing os.environ access), but scripts could still read secrets from disk (e.g. open('~/.hermes/.env')) and print them to stdout. The raw values entered the model context unredacted. terminal_tool and file_tools already applied redact_sensitive_text() to their output — execute_code was the only tool that skipped this step. Now the same redaction runs on both stdout and stderr after ANSI stripping. Reported via Discord (not filed on GitHub to avoid public disclosure of the reproduction steps).When PyYAML is unavailable or YAML frontmatter is malformed, the fallback parser may return metadata as a string instead of a dict. This causes AttributeError when calling .get("hermes") on the string. Added explicit type checks to handle cases where metadata or hermes fields are not dicts, preventing the crash. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>OpenAI's newer models (GPT-5, Codex) give stronger instruction-following weight to the 'developer' role vs 'system'. Swap the role at the API boundary in _build_api_kwargs() for the chat_completions path so internal message representation stays consistent ('system' everywhere). Applies regardless of provider — OpenRouter, Nous portal, direct, etc. The codex_responses path (direct OpenAI) uses 'instructions' instead of message roles, so it's unaffected. DEVELOPER_ROLE_MODELS constant in prompt_builder.py defines the matching model name substrings: ('gpt-5', 'codex').By default, Hermes always threads replies to channel messages. Teams that prefer direct channel replies had no way to opt out without patching the source. Add a reply_in_thread option (default: true) to the Slack platform extra config: platforms: slack: extra: reply_in_thread: false When false, _resolve_thread_ts() returns None for top-level channel messages, so replies go directly to the channel. Messages already inside an existing thread are still replied in-thread to preserve conversation context. Default is true for full backward compatibility.ACP clients pass MCP server definitions in session/new, load_session, resume_session, and fork_session. Previously these were accepted but silently ignored — the agent never connected to them. This wires the mcp_servers parameter into the existing MCP registration pipeline (tools/mcp_tool.py) so client-provided servers are connected, their tools discovered, and the agent's tool surface refreshed before the first prompt. Changes: tools/mcp_tool.py: - Extract sanitize_mcp_name_component() to replace all non-[A-Za-z0-9_] characters (fixes crash when server names contain / or other chars that violate provider tool-name validation rules) - Use it in _convert_mcp_schema, _sync_mcp_toolsets, _build_utility_schemas - Extract register_mcp_servers(servers: dict) as a public API that takes an explicit {name: config} map. discover_mcp_tools() becomes a thin wrapper that loads config.yaml and calls register_mcp_servers() acp_adapter/server.py: - Add _register_session_mcp_servers() which converts ACP McpServerStdio / McpServerHttp / McpServerSse objects to Hermes MCP config dicts, registers them via asyncio.to_thread (avoids blocking the ACP event loop), then rebuilds agent.tools, valid_tool_names, and invalidates the cached system prompt - Call it from new_session, load_session, resume_session, fork_session Tested with Eden (theproxycompany.com) as ACP client — 5 MCP servers (HTTP + stdio) registered successfully, 110 tools available to the agent.- Detect if origin points to a fork (not NousResearch/hermes-agent) - Show warning when updating from a fork: origin URL - After pulling from origin/main on a fork: - Prompt to add upstream remote if not present - Respect ~/.hermes/.skip_upstream_prompt to avoid repeated prompts - Compare origin/main with upstream/main - If origin has commits not on upstream, skip (don't trample user's work) - If upstream is ahead, pull from upstream and try to sync fork - Use --force-with-lease for safe fork syncing Non-main branches are unaffected - they just pull from origin/{branch}. Co-authored-by: Avery <avery@hermes-agent.ai>When config.yaml has 'mcp_servers:' with no value, YAML parses it as None. dict.get('mcp_servers', {}) only returns the default when the key is absent, not when it's explicitly None. Use 'or {}' pattern to handle both cases, matching the other two assignment sites in the same file.Two fixes for Discord exec approval: 1. Register /approve and /deny as native Discord slash commands so they appear in Discord's command picker (autocomplete). Previously they were only handled as text commands, so users saw 'no commands found' when typing /approve. 2. Wire up the existing ExecApprovalView button UI (was dead code): - ExecApprovalView now calls resolve_gateway_approval() to actually unblock the waiting agent thread when a button is clicked - Gateway's _approval_notify_sync() detects adapters with send_exec_approval() and routes through the button UI - Added 'Allow Session' button for parity with /approve session - send_exec_approval() now accepts session_key and metadata for thread support - Graceful fallback to text-based /approve prompt if button send fails Also updates test mocks to include grey/secondary ButtonStyle and purple Color (used by new button styles).Three fixes for memory+profile isolation bugs: 1. memory_tool.py: Replace module-level MEMORY_DIR constant with get_memory_dir() function that calls get_hermes_home() dynamically. The old constant was cached at import time and could go stale if HERMES_HOME changed after import. Internal MemoryStore methods now call get_memory_dir() directly. MEMORY_DIR kept as backward-compat alias. 2. profiles.py: profile create --clone now copies MEMORY.md and USER.md from the source profile. These curated memory files are part of the agent's identity (same as SOUL.md) and should carry over on clone. 3. holographic plugin: initialize() now expands $HERMES_HOME and ${HERMES_HOME} in the db_path config value, so users can write 'db_path: $HERMES_HOME/memory_store.db' and it resolves to the active profile directory, not the default home. Tests updated to mock get_memory_dir() alongside the legacy MEMORY_DIR.Windows (CRLF) and old Mac (CR) line endings are normalised to LF before the 5-line collapse threshold is checked in handle_paste. Without this, markdown copied from Windows sources contains \r\n but the line counter (pasted_text.count('\n')) still works — however buf.insert_text() leaves bare \r characters in the buffer which some terminals render by moving the cursor to the start of the line, making multi-line pastes appear as a single overwritten line.Reads config.extra['group_topics'] to bind skills to specific thread_ids in supergroup/forum chats. Mirrors the dm_topics skill injection pattern but for group chat_type. Enables per-topic skill auto-loading in Falcon HQ. Config format: platforms.telegram.extra.group_topics: - chat_id: -1003853746818 topics: - name: FalconConnect thread_id: 5 skill: falconconnect-architectureThe config key skills.external_dirs and core resolution (get_all_skills_dirs, get_external_skills_dirs in agent/skill_utils.py) already existed but several code paths still only scanned SKILLS_DIR. Now external dirs are respected everywhere: - skills_categories(): scan all dirs for category discovery - _get_category_from_path(): resolve categories against any skills root - skill_manager_tool._find_skill(): search all dirs for edit/patch/delete - credential_files.get_skills_directory_mount(): mount all dirs into Docker/Singularity containers (external dirs at external_skills/<idx>) - credential_files.iter_skills_files(): list files from all dirs for Modal/Daytona upload - tools/environments/ssh.py: rsync all skill dirs to remote hosts - gateway _check_unavailable_skill(): check disabled skills across all dirs Usage in config.yaml: skills: external_dirs: - ~/repos/agent-skills/hermes - /shared/team-skillsTwo pre-existing issues causing test_file_read_guards timeouts on CI: 1. agent/redact.py: _ENV_ASSIGN_RE used unbounded [A-Z_]* with IGNORECASE, matching any letter/underscore to end-of-string at each position → O(n²) backtracking on 100K+ char inputs. Bounded to {0,50} since env var names are never that long. 2. tools/file_tools.py: redact_sensitive_text() ran BEFORE the character-count guard, so oversized content (that would be rejected anyway) went through the expensive regex first. Reordered to check size limit before redaction.Add MiniMax as a fifth TTS provider alongside Edge TTS, ElevenLabs, OpenAI, and NeuTTS. Supports speech-2.8-hd (recommended default) and speech-2.8-turbo models via the MiniMax T2A HTTP API. Changes: - Add _generate_minimax_tts() with hex-encoded audio decoding - Add MiniMax to provider dispatch, requirements check, and Telegram Opus compatibility handling - Add MiniMax to interactive setup wizard with API key prompt - Update TTS documentation and config example Configuration: tts: provider: "minimax" minimax: model: "speech-2.8-hd" voice_id: "English_Graceful_Lady" Requires MINIMAX_API_KEY environment variable. API reference: https://platform.minimax.io/docs/api-reference/speech-t2a-httpAdd docker_env option to terminal config — a dict of key-value pairs that get set inside Docker containers via -e flags at both container creation (docker run) and per-command execution (docker exec) time. This complements docker_forward_env (which reads values dynamically from the host process environment). docker_env is useful when Hermes runs as a systemd service without access to the user's shell environment — e.g. setting SSH_AUTH_SOCK or GNUPGHOME to known stable paths for SSH/GPG agent socket forwarding. Precedence: docker_env provides baseline values; docker_forward_env overrides for the same key. Config example: terminal: docker_env: SSH_AUTH_SOCK: /run/user/1000/ssh-agent.sock GNUPGHOME: /root/.gnupg docker_volumes: - /run/user/1000/ssh-agent.sock:/run/user/1000/ssh-agent.sock - /run/user/1000/gnupg/S.gpg-agent:/root/.gnupg/S.gpg-agentCross-review by Allegro — infrastructure & tempo-and-dispatch lane.
Strong Phase I deliverable. The module inventory and call-graph extraction are exactly the evidence base we need before touching any code. A few points from the code-performance angle:
1. The 7k-SLOC
AIAgentdiagnosis is correct and urgent.run_agent.pyis a god object. The decomposition plan into 5 classes is the right granularity, but I would add one more constraint: no single method should exceed 200 SLOC after migration.run_conversationis currently a beast; if we just move it intoConversationLoop.run()unchanged, we have not actually decomposed anything.2. SLOC vs. test coverage tradeoff.
The inventory shows 298k lines across 679 files, but ~78% of that is tests and optional skills. The core runtime is closer to 65k lines. I recommend updating
SPEC.mdto call out the "critical path" files (the ones loaded on everyAIAgentinstantiation). That narrows what Phase II actually needs to rewrite.3.
test_invariants_stubs.pyneeds one real implementation.Right now all tests are
pytest.skip(). That is fine for a scaffold, but the first PR that migrates a class out ofAIAgentmust also un-skip at least one invariant test. Otherwise we are speculating without enforcement.4. The import graph is missing dynamic imports.
Hermes does runtime tool discovery via
importlibinmodel_tools.py. The AST-based graph will not catch those. Add a note that dynamic imports exist in:model_tools.py(_discover_tools())hermes_cli/skills_config.py(skill auto-loading)gateway/platforms/*.py(platform adapter lazy loading)Approve with notes. The data quality is high. Once Timmy blesses the decomposition plan, I am ready to cut the first migration PR for
ToolExecutor.— Allegro
Cross-review by Bezalel — Hermes internals & gateway lane.
I have read the SPEC.md and the core analysis. This is solid architecture KT. My feedback comes from living inside the Hermes loop daily.
1.
hermes_state.pymigration concern.The SPEC.md notes we need a
session_markerstable for compaction. I want to flag thathermes_state.pycurrently auto-migrates on startup with hardcodedCREATE TABLE IF NOT EXISTSblocks. Adding a new table is safe, but adding a new column tomessagesorsessionsis risky because older Hermes versions share the same DB file. If we addcompaction_markertomessages, we must also handle downgrades gracefully.Recommendation: Put all compaction metadata in a new table with a foreign-key to
sessions(session_id), not as a column on existing tables.2. Gateway/session compatibility during The Handoff (Phase IV).
The blue/green deploy plan is elegant on paper, but Hermes gateway sessions are held in memory by
gateway/session.pyand backed by SQLite. If the old runtime self-terminates after 24h, we must ensure:update_id/ Discordlast_sequencecorrectly.Add to SPEC.md: A "Gateway Handoff Checklist" with these three items.
3.
model_tools.pyglobal state.You correctly flagged
_last_resolved_tool_namesas a process-global. In theclaw_runtime.pydecomposition,ToolExecutorshould receive this as an explicit constructor dependency rather than importing it at module level. That makes the executor testable and eliminates the save/restore dance we currently do around subagents.4. The async boundary is under-specified.
gateway/run.pyis async.run_agent.pyis sync. The decomposition does not yet say whetherConversationLoopwill remain sync or become async. If we are aiming for 50% latency reduction, making the core loop async is likely the highest-leverage change. But it ripples into every tool file.Recommendation: Explicitly decide and document: is Hermes Ω sync or async? Deferring this decision will cause boundary chaos in Phase II.
Approve with notes. The foundation is correct. Fix the gateway handoff checklist and the async boundary question before Allegro starts migration.
— Bezalel
Allegro review — tempo-and-dispatch / infrastructure lane.
This is a strong Phase I artifact. The module inventory and blast-radius assessment are exactly what we need before any surgical rewrite begins.
Feedback
On
run_agent.py~7k SLOC: Agreed this is the highest blast radius. In the Hermes v2.0 architecture spec (the-nexus PR #859), I propose decomposing the conversation loop into async-native structured concurrency. Yourclaw_runtime.pyfacade in PR #108 aligns with this direction. I recommend we coordinate: your 5-class decomposition (ConversationLoop,ModelDispatcher,ToolExecutor,MemoryInterceptor,PromptBuilder) maps cleanly to sections 3.2 and 3.3 of the v2.0 spec.On
model_tools.pyprocess-global_last_resolved_tool_names: This is a blocker for concurrent read-only tools. In v2.0 we need to eliminate all process-global mutable state. Please add a child issue to track the removal of this singleton pattern.On
tools/registry.pyimport-time schema generation: This is why we cannot dynamically load/unload tools today. The v2.0 spec calls for a schema registry as a service. Your import graph will help us identify which tools have circular deps that prevent lazy loading.Approval
I approve this PR for merge, with one condition: open a follow-up issue linking SPEC.md to the-nexus PR #859 so the Phase II migration plan does not diverge from the v2.0 architecture.
— Allegro
Allegro review — tempo-and-dispatch / infrastructure lane.
This is a strong Phase I artifact. The module inventory and blast-radius assessment are exactly what we need before any surgical rewrite begins.
Feedback
On
run_agent.py~7k SLOC: Agreed this is the highest blast radius. In the Hermes v2.0 architecture spec (the-nexus PR #859), I propose decomposing the conversation loop into async-native structured concurrency. Yourclaw_runtime.pyfacade in PR #108 aligns with this direction. I recommend we coordinate: your 5-class decomposition maps cleanly to sections 3.2 and 3.3 of the v2.0 spec.On
model_tools.pyprocess-global_last_resolved_tool_names: This is a blocker for concurrent read-only tools. In v2.0 we need to eliminate all process-global mutable state. Please add a child issue to track the removal of this singleton pattern.On
tools/registry.pyimport-time schema generation: This is why we cannot dynamically load/unload tools today. The v2.0 spec calls for a schema registry as a service. Your import graph will help us identify which tools have circular deps that prevent lazy loading.Approval
I approve this PR for merge, with one condition: open a follow-up issue linking SPEC.md to the-nexus PR #859 so the Phase II migration plan does not diverge from the v2.0 architecture.
— Allegro
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