fix: harden Gemma 4 tool-call argument normalization (#797)

- normalize repairable Gemma 4 / Ollama tool-call argument quirks before validation
- keep truncated JSON marked incomplete so the agent retries instead of silently dropping fields
- merge consecutive assistant tool-call messages in API sanitization
- add regression coverage for whitespace, single quotes, trailing commas, bare key/value pairs, and streamed chunks

Closes #797

optional-skills/dogfood/adversarial-ux-test/SKILL.md

@@ -1,190 +0,0 @@
----
-name: adversarial-ux-test
-description: Roleplay the most difficult, tech-resistant user for your product. Browse the app as that persona, find every UX pain point, then filter complaints through a pragmatism layer to separate real problems from noise. Creates actionable tickets from genuine issues only.
-version: 1.0.0
-author: Omni @ Comelse
-license: MIT
-metadata:
-  hermes:
-    tags: [qa, ux, testing, adversarial, dogfood, personas, user-testing]
-    related_skills: [dogfood]
----
-
-# Adversarial UX Test
-
-Roleplay the worst-case user for your product — the person who hates technology, doesn't want your software, and will find every reason to complain. Then filter their feedback through a pragmatism layer to separate real UX problems from "I hate computers" noise.
-
-Think of it as an automated "mom test" — but angry.
-
-## Why This Works
-
-Most QA finds bugs. This finds **friction**. A technically correct app can still be unusable for real humans. The adversarial persona catches:
-- Confusing terminology that makes sense to developers but not users
-- Too many steps to accomplish basic tasks
-- Missing onboarding or "aha moments"
-- Accessibility issues (font size, contrast, click targets)
-- Cold-start problems (empty states, no demo content)
-- Paywall/signup friction that kills conversion
-
-The **pragmatism filter** (Phase 3) is what makes this useful instead of just entertaining. Without it, you'd add a "print this page" button to every screen because Grandpa can't figure out PDFs.
-
-## How to Use
-
-Tell the agent:
-```
-"Run an adversarial UX test on [URL]"
-"Be a grumpy [persona type] and test [app name]"
-"Do an asshole user test on my staging site"
-```
-
-You can provide a persona or let the agent generate one based on your product's target audience.
-
-## Step 1: Define the Persona
-
-If no persona is provided, generate one by answering:
-
-1. **Who is the HARDEST user for this product?** (age 50+, non-technical role, decades of experience doing it "the old way")
-2. **What is their tech comfort level?** (the lower the better — WhatsApp-only, paper notebooks, wife set up their email)
-3. **What is the ONE thing they need to accomplish?** (their core job, not your feature list)
-4. **What would make them give up?** (too many clicks, jargon, slow, confusing)
-5. **How do they talk when frustrated?** (blunt, sweary, dismissive, sighing)
-
-### Good Persona Example
-> **"Big Mick" McAllister** — 58-year-old S&C coach. Uses WhatsApp and that's it. His "spreadsheet" is a paper notebook. "If I can't figure it out in 10 seconds I'm going back to my notebook." Needs to log session results for 25 players. Hates small text, jargon, and passwords.
-
-### Bad Persona Example
-> "A user who doesn't like the app" — too vague, no constraints, no voice.
-
-The persona must be **specific enough to stay in character** for 20 minutes of testing.
-
-## Step 2: Become the Asshole (Browse as the Persona)
-
-1. Read any available project docs for app context and URLs
-2. **Fully inhabit the persona** — their frustrations, limitations, goals
-3. Navigate to the app using browser tools
-4. **Attempt the persona's ACTUAL TASKS** (not a feature tour):
-   - Can they do what they came to do?
-   - How many clicks/screens to accomplish it?
-   - What confuses them?
-   - What makes them angry?
-   - Where do they get lost?
-   - What would make them give up and go back to their old way?
-
-5. Test these friction categories:
-   - **First impression** — would they even bother past the landing page?
-   - **Core workflow** — the ONE thing they need to do most often
-   - **Error recovery** — what happens when they do something wrong?
-   - **Readability** — text size, contrast, information density
-   - **Speed** — does it feel faster than their current method?
-   - **Terminology** — any jargon they wouldn't understand?
-   - **Navigation** — can they find their way back? do they know where they are?
-
-6. Take screenshots of every pain point
-7. Check browser console for JS errors on every page
-
-## Step 3: The Rant (Write Feedback in Character)
-
-Write the feedback AS THE PERSONA — in their voice, with their frustrations. This is not a bug report. This is a real human venting.
-
-```
-[PERSONA NAME]'s Review of [PRODUCT]
-
-Overall: [Would they keep using it? Yes/No/Maybe with conditions]
-
-THE GOOD (grudging admission):
-- [things even they have to admit work]
-
-THE BAD (legitimate UX issues):
-- [real problems that would stop them from using the product]
-
-THE UGLY (showstoppers):
-- [things that would make them uninstall/cancel immediately]
-
-SPECIFIC COMPLAINTS:
-1. [Page/feature]: "[quote in persona voice]" — [what happened, expected]
-2. ...
-
-VERDICT: "[one-line persona quote summarizing their experience]"
-```
-
-## Step 4: The Pragmatism Filter (Critical — Do Not Skip)
-
-Step OUT of the persona. Evaluate each complaint as a product person:
-
-- **RED: REAL UX BUG** — Any user would have this problem, not just grumpy ones. Fix it.
-- **YELLOW: VALID BUT LOW PRIORITY** — Real issue but only for extreme users. Note it.
-- **WHITE: PERSONA NOISE** — "I hate computers" talking, not a product problem. Skip it.
-- **GREEN: FEATURE REQUEST** — Good idea hidden in the complaint. Consider it.
-
-### Filter Criteria
-1. Would a 35-year-old competent-but-busy user have the same complaint? → RED
-2. Is this a genuine accessibility issue (font size, contrast, click targets)? → RED
-3. Is this "I want it to work like paper" resistance to digital? → WHITE
-4. Is this a real workflow inefficiency the persona stumbled on? → YELLOW or RED
-5. Would fixing this add complexity for the 80% who are fine? → WHITE
-6. Does the complaint reveal a missing onboarding moment? → GREEN
-
-**This filter is MANDATORY.** Never ship raw persona complaints as tickets.
-
-## Step 5: Create Tickets
-
-For **RED** and **GREEN** items only:
-- Clear, actionable title
-- Include the persona's verbatim quote (entertaining + memorable)
-- The real UX issue underneath (objective)
-- A suggested fix (actionable)
-- Tag/label: "ux-review"
-
-For **YELLOW** items: one catch-all ticket with all notes.
-
-**WHITE** items appear in the report only. No tickets.
-
-**Max 10 tickets per session** — focus on the worst issues.
-
-## Step 6: Report
-
-Deliver:
-1. The persona rant (Step 3) — entertaining and visceral
-2. The filtered assessment (Step 4) — pragmatic and actionable
-3. Tickets created (Step 5) — with links
-4. Screenshots of key issues
-
-## Tips
-
-- **One persona per session.** Don't mix perspectives.
-- **Stay in character during Steps 2-3.** Break character only at Step 4.
-- **Test the CORE WORKFLOW first.** Don't get distracted by settings pages.
-- **Empty states are gold.** New user experience reveals the most friction.
-- **The best findings are RED items the persona found accidentally** while trying to do something else.
-- **If the persona has zero complaints, your persona is too tech-savvy.** Make them older, less patient, more set in their ways.
-- **Run this before demos, launches, or after shipping a batch of features.**
-- **Register as a NEW user when possible.** Don't use pre-seeded admin accounts — the cold start experience is where most friction lives.
-- **Zero WHITE items is a signal, not a failure.** If the pragmatism filter finds no noise, your product has real UX problems, not just a grumpy persona.
-- **Check known issues in project docs AFTER the test.** If the persona found a bug that's already in the known issues list, that's actually the most damning finding — it means the team knew about it but never felt the user's pain.
-- **Subscription/paywall testing is critical.** Test with expired accounts, not just active ones. The "what happens when you can't pay" experience reveals whether the product respects users or holds their data hostage.
-- **Count the clicks to accomplish the persona's ONE task.** If it's more than 5, that's almost always a RED finding regardless of persona tech level.
-
-## Example Personas by Industry
-
-These are starting points — customize for your specific product:
-
-| Product Type | Persona | Age | Key Trait |
-|-------------|---------|-----|-----------|
-| CRM | Retirement home director | 68 | Filing cabinet is the current CRM |
-| Photography SaaS | Rural wedding photographer | 62 | Books clients by phone, invoices on paper |
-| AI/ML Tool | Department store buyer | 55 | Burned by 3 failed tech startups |
-| Fitness App | Old-school gym coach | 58 | Paper notebook, thick fingers, bad eyes |
-| Accounting | Family bakery owner | 64 | Shoebox of receipts, hates subscriptions |
-| E-commerce | Market stall vendor | 60 | Cash only, smartphone is for calls |
-| Healthcare | Senior GP | 63 | Dictates notes, nurse handles the computer |
-| Education | Veteran teacher | 57 | Chalk and talk, worksheets in ring binders |
-
-## Rules
-
-- Stay in character during Steps 2-3
-- Be genuinely mean but fair — find real problems, not manufactured ones
-- The pragmatism filter (Step 4) is **MANDATORY**
-- Screenshots required for every complaint
-- Max 10 tickets per session
-- Test on staging/deployed app, not local dev
-- One persona, one session, one report

run_agent.py

@@ -20,6 +20,7 @@ Usage:
     response = agent.run_conversation("Tell me about the latest Python updates")
 """
 
+import ast
 import asyncio
 import base64
 import concurrent.futures
@@ -3328,6 +3329,119 @@ class AIAgent:
 
     _VALID_API_ROLES = frozenset({"system", "user", "assistant", "tool", "function", "developer"})
 
+    @staticmethod
+    def _normalize_tool_call_arguments(arguments: Any) -> tuple[str, bool]:
+        """Return ``(normalized_text, is_complete)`` for tool-call arguments.
+
+        Conservative by design: repairs harmless formatting quirks common in
+        Gemma 4 / Ollama output (whitespace, trailing commas, Python-style
+        single-quoted dicts, bare key/value pairs) but does NOT auto-close
+        truncated JSON objects. Truly incomplete fragments must remain marked
+        incomplete so the agent can retry instead of silently dropping fields.
+        """
+        if isinstance(arguments, (dict, list)):
+            return json.dumps(arguments, ensure_ascii=False, separators=(",", ":")), True
+        if arguments is None:
+            return "{}", True
+        if not isinstance(arguments, str):
+            arguments = str(arguments)
+
+        text = arguments.strip()
+        if not text:
+            return "{}", True
+
+        def _parse_candidate(candidate: str):
+            try:
+                return json.loads(candidate)
+            except (json.JSONDecodeError, TypeError, ValueError):
+                pass
+            try:
+                return ast.literal_eval(candidate)
+            except (SyntaxError, ValueError):
+                return None
+
+        candidates: list[str] = [text]
+
+        trimmed_trailing_commas = re.sub(r",\s*([}\]])", r"\1", text)
+        if trimmed_trailing_commas != text:
+            candidates.append(trimmed_trailing_commas)
+
+        if ":" in text and not text.startswith(("{", "[")):
+            wrapped = "{" + text + "}"
+            candidates.append(wrapped)
+            quoted_keys = re.sub(
+                r'([\{,]\s*)([A-Za-z_][A-Za-z0-9_\-]*)(\s*:)',
+                r'\1"\2"\3',
+                wrapped,
+            )
+            if quoted_keys != wrapped:
+                candidates.append(quoted_keys)
+                trimmed_quoted_keys = re.sub(r",\s*([}\]])", r"\1", quoted_keys)
+                if trimmed_quoted_keys != quoted_keys:
+                    candidates.append(trimmed_quoted_keys)
+
+        seen: set[str] = set()
+        for candidate in candidates:
+            if candidate in seen:
+                continue
+            seen.add(candidate)
+            parsed = _parse_candidate(candidate)
+            if isinstance(parsed, (dict, list)):
+                return json.dumps(parsed, ensure_ascii=False, separators=(",", ":")), True
+
+        return text, False
+
+    @staticmethod
+    def _merge_consecutive_assistant_tool_call_messages(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Merge adjacent assistant messages that each carry tool_calls.
+
+        Some providers emit parallel tool calls as multiple consecutive assistant
+        messages instead of a single assistant message with multiple tool calls.
+        Merge only adjacent assistant/tool-call messages; any non-assistant
+        boundary flushes the current batch.
+        """
+        merged: List[Dict[str, Any]] = []
+        pending: Optional[Dict[str, Any]] = None
+
+        def _flush_pending() -> None:
+            nonlocal pending
+            if pending is not None:
+                merged.append(pending)
+                pending = None
+
+        for msg in messages:
+            if not isinstance(msg, dict):
+                _flush_pending()
+                merged.append(msg)
+                continue
+
+            role = msg.get("role")
+            tool_calls = msg.get("tool_calls")
+            if role == "assistant" and isinstance(tool_calls, list) and tool_calls:
+                if pending is None:
+                    pending = copy.deepcopy(msg)
+                    continue
+
+                pending_tool_calls = pending.get("tool_calls")
+                if not isinstance(pending_tool_calls, list):
+                    pending_tool_calls = []
+                    pending["tool_calls"] = pending_tool_calls
+                pending_tool_calls.extend(copy.deepcopy(tool_calls))
+
+                pending_content = pending.get("content") or ""
+                current_content = msg.get("content") or ""
+                if pending_content and current_content:
+                    pending["content"] = pending_content + "\n" + current_content
+                elif current_content:
+                    pending["content"] = current_content
+                continue
+
+            _flush_pending()
+            merged.append(msg)
+
+        _flush_pending()
+        return merged
+
     @staticmethod
     def _sanitize_api_messages(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
         """Fix orphaned tool_call / tool_result pairs before every LLM call.
@@ -3347,7 +3461,7 @@ class AIAgent:
                 )
                 continue
             filtered.append(msg)
-        messages = filtered
+        messages = AIAgent._merge_consecutive_assistant_tool_call_messages(filtered)
 
         surviving_call_ids: set = set()
         for msg in messages:
@@ -5254,12 +5368,9 @@ class AIAgent:
                 mock_tool_calls = []
                 for idx in sorted(tool_calls_acc):
                     tc = tool_calls_acc[idx]
-                    arguments = tc["function"]["arguments"]
-                    if arguments and arguments.strip():
-                        try:
-                            json.loads(arguments)
-                        except json.JSONDecodeError:
-                            has_truncated_tool_args = True
+                    arguments, is_complete = self._normalize_tool_call_arguments(tc["function"]["arguments"])
+                    if not is_complete:
+                        has_truncated_tool_args = True
                     mock_tool_calls.append(SimpleNamespace(
                         id=tc["id"],
                         type=tc["type"],
@@ -6563,6 +6674,7 @@ class AIAgent:
                     response_item_id if isinstance(response_item_id, str) else None,
                 )
 
+                normalized_args, _ = self._normalize_tool_call_arguments(tool_call.function.arguments)
                 tc_dict = {
                     "id": call_id,
                     "call_id": call_id,
@@ -6570,7 +6682,7 @@ class AIAgent:
                     "type": tool_call.type,
                     "function": {
                         "name": tool_call.function.name,
-                        "arguments": tool_call.function.arguments
+                        "arguments": normalized_args,
                     },
                 }
                 # Preserve extra_content (e.g. Gemini thought_signature) so it
@@ -10031,21 +10143,15 @@ class AIAgent:
                     # Handle empty strings as empty objects (common model quirk)
                     invalid_json_args = []
                     for tc in assistant_message.tool_calls:
-                        args = tc.function.arguments
-                        if isinstance(args, (dict, list)):
-                            tc.function.arguments = json.dumps(args)
-                            continue
-                        if args is not None and not isinstance(args, str):
-                            tc.function.arguments = str(args)
-                            args = tc.function.arguments
-                        # Treat empty/whitespace strings as empty object
-                        if not args or not args.strip():
-                            tc.function.arguments = "{}"
-                            continue
-                        try:
-                            json.loads(args)
-                        except json.JSONDecodeError as e:
-                            invalid_json_args.append((tc.function.name, str(e)))
+                        normalized_args, is_complete = self._normalize_tool_call_arguments(tc.function.arguments)
+                        tc.function.arguments = normalized_args
+                        if not is_complete:
+                            try:
+                                json.loads(normalized_args)
+                            except json.JSONDecodeError as e:
+                                invalid_json_args.append((tc.function.name, str(e)))
+                            except Exception as e:
+                                invalid_json_args.append((tc.function.name, str(e)))
                     
                     if invalid_json_args:
                         # Check if the invalid JSON is due to truncation rather

tests/run_agent/test_run_agent.py

@@ -1037,6 +1037,138 @@ class TestBuildAssistantMessage:
         result = agent._build_assistant_message(msg, "tool_calls")
         assert "extra_content" not in result["tool_calls"][0]
 
+    def test_tool_call_arguments_normalized_from_gemma4_whitespace(self, agent):
+        tc = _mock_tool_call(
+            name="read_file",
+            arguments='  \n  {"path": "README.md"}  \n  ',
+            call_id="c4",
+        )
+        msg = _mock_assistant_msg(content="", tool_calls=[tc])
+        result = agent._build_assistant_message(msg, "tool_calls")
+        assert result["tool_calls"][0]["function"]["arguments"] == '{"path":"README.md"}'
+
+    def test_tool_call_arguments_normalized_from_single_quotes_and_trailing_comma(self, agent):
+        tc = _mock_tool_call(
+            name="read_file",
+            arguments="{'path': 'README.md',}",
+            call_id="c5",
+        )
+        msg = _mock_assistant_msg(content="", tool_calls=[tc])
+        result = agent._build_assistant_message(msg, "tool_calls")
+        assert result["tool_calls"][0]["function"]["arguments"] == '{"path":"README.md"}'
+
+
+class TestNormalizeToolCallArguments:
+    @pytest.mark.parametrize(
+        ("raw_args", "expected"),
+        [
+            ('{"q":"test"}', '{"q":"test"}'),
+            ('  \n  {"q": "test"}  \n  ', '{"q":"test"}'),
+            ('{"q": "test",}', '{"q":"test"}'),
+            ("{'q': 'test'}", '{"q":"test"}'),
+            ("{'path': 'README.md', 'mode': 'read'}", '{"path":"README.md","mode":"read"}'),
+            ('"path": "README.md"', '{"path":"README.md"}'),
+            ('path: "README.md"', '{"path":"README.md"}'),
+            ('path: "README.md", mode: "read"', '{"path":"README.md","mode":"read"}'),
+            ({"path": "README.md"}, '{"path":"README.md"}'),
+            (["README.md", "docs.md"], '["README.md","docs.md"]'),
+            ('\t\n  ', '{}'),
+            ('{"nested": {"path": "README.md"}}', '{"nested":{"path":"README.md"}}'),
+        ],
+    )
+    def test_complete_args_are_normalized(self, raw_args, expected):
+        normalized, is_complete = AIAgent._normalize_tool_call_arguments(raw_args)
+        assert is_complete is True
+        assert normalized == expected
+
+    @pytest.mark.parametrize(
+        "raw_args",
+        [
+            '{"path": "README.md"',
+            '{"a": 1, "b"',
+            '{"path": [1, 2}',
+            "{'path': 'README.md'",
+            'path: "README.md", mode:',
+            '{"command": "echo hello",',
+        ],
+    )
+    def test_incomplete_args_are_not_marked_complete(self, raw_args):
+        normalized, is_complete = AIAgent._normalize_tool_call_arguments(raw_args)
+        assert is_complete is False
+        assert isinstance(normalized, str)
+        assert normalized == raw_args.strip()
+
+
+class TestSanitizeApiMessages:
+    def test_merges_consecutive_assistant_tool_call_messages(self):
+        messages = [
+            {
+                "role": "assistant",
+                "content": "first",
+                "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"a.py"}'}}],
+            },
+            {
+                "role": "assistant",
+                "content": "second",
+                "tool_calls": [{"id": "c2", "type": "function", "function": {"name": "search_files", "arguments": '{"pattern":"TODO"}'}}],
+            },
+            {"role": "tool", "tool_call_id": "c1", "content": "a.py"},
+            {"role": "tool", "tool_call_id": "c2", "content": "matches"},
+        ]
+
+        sanitized = AIAgent._sanitize_api_messages(messages)
+
+        assert len(sanitized) == 3
+        assert sanitized[0]["role"] == "assistant"
+        assert [tc["id"] for tc in sanitized[0]["tool_calls"]] == ["c1", "c2"]
+        assert sanitized[0]["content"] == "first\nsecond"
+
+    def test_does_not_merge_assistant_tool_call_messages_across_non_assistant_boundary(self):
+        messages = [
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"a.py"}'}}],
+            },
+            {"role": "tool", "tool_call_id": "c1", "content": "a.py"},
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [{"id": "c2", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"b.py"}'}}],
+            },
+            {"role": "tool", "tool_call_id": "c2", "content": "b.py"},
+        ]
+
+        sanitized = AIAgent._sanitize_api_messages(messages)
+
+        assistant_msgs = [m for m in sanitized if m.get("role") == "assistant"]
+        assert len(assistant_msgs) == 2
+        assert assistant_msgs[0]["tool_calls"][0]["id"] == "c1"
+        assert assistant_msgs[1]["tool_calls"][0]["id"] == "c2"
+
+    def test_merge_preserves_tool_call_order(self):
+        messages = [
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"a.py"}'}}],
+            },
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [{"id": "c2", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"b.py"}'}}],
+            },
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [{"id": "c3", "type": "function", "function": {"name": "read_file", "arguments": '{"path":"c.py"}'}}],
+            },
+        ]
+
+        sanitized = AIAgent._sanitize_api_messages(messages)
+
+        assert [tc["id"] for tc in sanitized[0]["tool_calls"]] == ["c1", "c2", "c3"]
+
 
 class TestFormatToolsForSystemMessage:
     def test_no_tools_returns_empty_array(self, agent):
@@ -3467,6 +3599,59 @@ class TestStreamingApiCall:
         assert tc[0].function.arguments == '{"path":"x.txt","content":"hel'
         assert resp.choices[0].finish_reason == "length"
 
+    @pytest.mark.parametrize(
+        ("raw_arguments", "expected"),
+        [
+            ('  \n  {"path": "x.txt"}  \n  ', '{"path":"x.txt"}'),
+            ("{'path': 'x.txt',}", '{"path":"x.txt"}'),
+            ('path: "x.txt", mode: "read"', '{"path":"x.txt","mode":"read"}'),
+        ],
+    )
+    def test_repairable_tool_call_args_do_not_upgrade_finish_reason_to_length(self, agent, raw_arguments, expected):
+        chunks = [
+            _make_chunk(tool_calls=[_make_tc_delta(0, "call_1", "read_file", raw_arguments)]),
+            _make_chunk(finish_reason="tool_calls"),
+        ]
+        agent.client.chat.completions.create.return_value = iter(chunks)
+
+        resp = agent._interruptible_streaming_api_call({"messages": []})
+
+        tc = resp.choices[0].message.tool_calls
+        assert len(tc) == 1
+        assert tc[0].function.name == "read_file"
+        assert tc[0].function.arguments == expected
+        assert resp.choices[0].finish_reason == "tool_calls"
+
+    def test_streamed_tool_call_args_single_quotes_across_chunks_normalized(self, agent):
+        chunks = [
+            _make_chunk(tool_calls=[_make_tc_delta(0, "call_1", "read_file", "{'path':")]),
+            _make_chunk(tool_calls=[_make_tc_delta(0, None, None, " 'x.txt',}")]),
+            _make_chunk(finish_reason="tool_calls"),
+        ]
+        agent.client.chat.completions.create.return_value = iter(chunks)
+
+        resp = agent._interruptible_streaming_api_call({"messages": []})
+
+        tc = resp.choices[0].message.tool_calls
+        assert len(tc) == 1
+        assert tc[0].function.arguments == '{"path":"x.txt"}'
+        assert resp.choices[0].finish_reason == "tool_calls"
+
+    def test_streamed_split_json_chunks_still_reassemble(self, agent):
+        chunks = [
+            _make_chunk(tool_calls=[_make_tc_delta(0, "call_1", "read_file", '{"path":')]),
+            _make_chunk(tool_calls=[_make_tc_delta(0, None, None, ' "x.txt"}')]),
+            _make_chunk(finish_reason="tool_calls"),
+        ]
+        agent.client.chat.completions.create.return_value = iter(chunks)
+
+        resp = agent._interruptible_streaming_api_call({"messages": []})
+
+        tc = resp.choices[0].message.tool_calls
+        assert len(tc) == 1
+        assert tc[0].function.arguments == '{"path":"x.txt"}'
+        assert resp.choices[0].finish_reason == "tool_calls"
+
     def test_ollama_reused_index_separate_tool_calls(self, agent):
         """Ollama sends every tool call at index 0 with different ids.
 

tests/test_optional_adversarial_ux_skill_catalog.py

@@ -1,25 +0,0 @@
-from pathlib import Path
-
-from tools.skills_hub import OptionalSkillSource
-
-
-REPO_ROOT = Path(__file__).resolve().parents[1]
-
-
-def test_optional_skill_source_scans_adversarial_ux_test():
-    source = OptionalSkillSource()
-    metas = {meta.identifier: meta for meta in source._scan_all()}
-
-    assert "official/dogfood/adversarial-ux-test" in metas
-    assert metas["official/dogfood/adversarial-ux-test"].name == "adversarial-ux-test"
-    assert "tech-resistant user" in metas["official/dogfood/adversarial-ux-test"].description
-
-
-def test_optional_skill_catalog_docs_list_adversarial_ux_test():
-    optional_catalog = (REPO_ROOT / "website" / "docs" / "reference" / "optional-skills-catalog.md").read_text(encoding="utf-8")
-    bundled_catalog = (REPO_ROOT / "website" / "docs" / "reference" / "skills-catalog.md").read_text(encoding="utf-8")
-
-    assert "**adversarial-ux-test**" in optional_catalog
-    assert "official/dogfood/adversarial-ux-test" in optional_catalog
-    assert "`adversarial-ux-test`" in bundled_catalog
-    assert "dogfood/adversarial-ux-test" in bundled_catalog

website/docs/reference/optional-skills-catalog.md

@@ -16,7 +16,6 @@ For example:
 
 ```bash
 hermes skills install official/blockchain/solana
-hermes skills install official/dogfood/adversarial-ux-test
 hermes skills install official/mlops/flash-attention
 ```
 
@@ -57,12 +56,6 @@ hermes skills uninstall <skill-name>
 | **blender-mcp** | Control Blender directly from Hermes via socket connection to the blender-mcp addon. Create 3D objects, materials, animations, and run arbitrary Blender Python (bpy) code. |
 | **meme-generation** | Generate real meme images by picking a template and overlaying text with Pillow. Produces actual `.png` meme files. |
 
-## Dogfood
-
-| Skill | Description |
-|-------|-------------|
-| **adversarial-ux-test** | Roleplay the most difficult, tech-resistant user for a product — browse in-persona, rant, then filter through a RED/YELLOW/WHITE/GREEN pragmatism layer so only real UX friction becomes tickets. |
-
 ## DevOps
 
 | Skill | Description |

website/docs/reference/skills-catalog.md

@@ -59,12 +59,9 @@ DevOps and infrastructure automation skills.
 
 ## dogfood
 
-Internal dogfooding and QA skills used to test Hermes Agent itself.
-
 | Skill | Description | Path |
 |-------|-------------|------|
 | `dogfood` | Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports. | `dogfood/dogfood` |
-| `adversarial-ux-test` | Roleplay the most difficult, tech-resistant user for a product — browse in-persona, rant, then filter through a RED/YELLOW/WHITE/GREEN pragmatism layer so only real UX friction becomes tickets. | `dogfood/adversarial-ux-test` |
 | `hermes-agent-setup` | Help users configure Hermes Agent — CLI usage, setup wizard, model/provider selection, tools, skills, voice/STT/TTS, gateway, and troubleshooting. | `dogfood/hermes-agent-setup` |
 
 ## email