---
name: qa
description: "General-purpose QA verdict for any artifact type"
---

# /ouroboros:qa

Standalone quality assessment for any artifact — code, documents, API responses, test output, or custom content. Unlike `ooo evaluate` (3-stage formal verification pipeline), `ooo qa` is a fast single-pass verdict with actionable suggestions.

## Usage

```
ooo qa [file_path | artifact_text]
ooo qa                                     # evaluate recent execution output
/ouroboros:qa [file_path | artifact_text]   # plugin mode
```

**Trigger keywords:** "ooo qa", "qa check", "quality check"

## How It Works

The QA Judge evaluates an artifact against a quality bar and returns a structured verdict:

1. **Parse the Quality Bar** — What EXACTLY must be true to pass?
2. **Assess Dimensions** — Correctness, Completeness, Quality, Intent Alignment, Domain-Specific
3. **Render Verdict** — Score (0.0-1.0) with PASS / REVISE / FAIL
4. **Determine Loop Action** — `done` (pass), `continue` (revise), `escalate` (fail)

### Verdict Thresholds

| Score Range  | Verdict | Loop Action |
|--------------|---------|-------------|
| >= 0.80      | PASS    | done        |
| 0.40 - 0.79  | REVISE  | continue    |
| < 0.40       | FAIL    | escalate    |

## Instructions

When the user invokes this skill:

### Step 0: Determine execution mode

This skill works in two modes. Determine which one **before** attempting any tool calls:

- **MCP mode** — If the QA MCP tool is available (already exposed, or loadable via discovery), use it:
  ```
  tool discovery query: "+ouroboros qa"
  ```
  If found (typically named `mcp__plugin_ouroboros_ouroboros__ouroboros_qa`), proceed with **QA Steps** below.

- **Fallback mode** — Only if the QA MCP tool is genuinely absent (no Ouroboros MCP server) skip to the **Fallback** section; an empty discovery result for an already-exposed tool is expected — call it directly rather than falling back. This skill is designed to work without MCP setup.

### QA Steps (MCP mode)

1. **Determine the artifact to evaluate:**
   - If user provides a file path: Read the file with Read tool
   - If user provides inline text: Use that directly
   - If no artifact specified: Look for the most recent execution output in conversation context
   - Ask user if unclear what to evaluate

2. **Determine the quality bar:**
   - If a seed YAML is available in context: Extract acceptance criteria from it
   - If user specifies a quality bar: Use that
   - If neither: Ask the user "What does 'good' mean for this artifact?"

3. **Determine artifact type:**
   - `code` — source code files
   - `test_output` — test results, CI output
   - `document` — specs, docs, READMEs
   - `api_response` — API responses, JSON payloads
   - `screenshot` — visual artifacts
   - `custom` — anything else

3.5. **Acting verification — reproduce and OBSERVE before judging (do not skip for behaviour-bearing artifacts):**
   A text judge can be fooled by a hopeful log line. When the artifact actually
   *does* something (code, an app, an API, a UI) and the runtime exposes acting
   tools — **computer-use / browser, `Bash`/shell, file reads** — gather real
   evidence first, ideally via a dedicated verification sub-agent so the main
   session stays lean:
   - **Run it** — execute the command / start the app / hit the endpoint.
   - **Observe the actual effect** — the file written, the endpoint's response,
     the rendered UI (screenshot via computer-use) — NOT just exit text.
   - **Probe the applicable adversarial classes** (the QA tool lists them):
     `misleading_output` (claimed success vs. real effect), `hung_command`
     (bounded timeout?), `malformed_input`, `stale_state`, `dirty_worktree`, etc.
   - Capture commands run, outputs, and artifact paths as **evidence**.
   Pass that evidence into the judge as `reference` (and prefer the observed
   behaviour over the source text as the `artifact` when they disagree). If no
   acting tools are available, say so and judge on the text alone — but flag that
   behaviour was not observed.

4. **Call the `ouroboros_qa` MCP tool:**
   ```
   Tool: ouroboros_qa
   Arguments:
     artifact: <the content to evaluate>
     quality_bar: <what 'pass' means>
     artifact_type: "code"  (or other type)
     reference: <observed-behaviour evidence from step 3.5, plus any reference>
     pass_threshold: 0.80  (adjustable)
     seed_content: <seed YAML if available>
   ```

5. **Present results clearly:**
   - Show the score and verdict prominently
   - List dimension scores
   - Highlight specific differences found
   - Show actionable suggestions
   - End with next step guidance based on verdict:
     - **PASS (done)**: `Next: Your artifact meets the quality bar. Proceed with confidence.`
     - **REVISE (continue)**: `Next: Address the suggestions above, then run ooo qa again to re-check.`
     - **FAIL (escalate)**: `Next: Fundamental issues detected. Consider ooo interview to re-examine requirements, or ooo unstuck to challenge assumptions.`

### Iterative QA Loop

For iterative usage, track the `qa_session_id` and `iteration_history` from the response meta:

1. First call returns `qa_session_id` and `iteration_entry` in meta
2. On subsequent calls, pass `qa_session_id` and accumulated `iteration_history`
3. Continue until verdict is `pass` or `fail`

In fallback mode, generate a `qa-<uuid4_short>` session ID on the first run and maintain iteration count in conversation context to preserve the same iterative contract.

## Fallback (No MCP Server)

If the MCP server is not available, adopt the `ouroboros:qa-judge` agent role directly:

1. Read the canonical agent definition: `<project-root>/src/ouroboros/agents/qa-judge.md`
   (This is the same prompt used by the MCP QA tool, ensuring consistent verdicts.)
2. Follow the QA Judge framework to evaluate the artifact
3. Output the verdict in the standard format (must match MCP output shape):

```
QA Verdict [Iteration N]
========================
Session: qa-<id>
Score: X.XX / 1.00 [PASS/REVISE/FAIL]
Verdict: pass/revise/fail
Threshold: 0.80

Dimensions:
  Correctness:      X.XX
  Completeness:     X.XX
  Quality:          X.XX
  Intent Alignment: X.XX
  Domain-Specific:  X.XX

Differences:
  - <specific difference>

Suggestions:
  - <actionable fix>

Reasoning: <1-3 sentence summary>

Loop Action: done/continue/escalate
```

## Example

```
User: ooo qa src/main.py

QA Verdict [Iteration 1]
============================================================
Session: qa-a1b2c3d4
Score: 0.72 / 1.00 [REVISE]
Verdict: revise
Threshold: 0.80

Dimensions:
  Correctness:           0.85
  Completeness:          0.60
  Quality:               0.75
  Intent Alignment:      0.80
  Domain-Specific:       0.60

Differences:
  - Missing error handling for network timeout in fetch_data()
  - No input validation on user_id parameter
  - Type hints missing on 3 public functions

Suggestions:
  - Add try/except with TimeoutError in fetch_data() (line 42)
  - Add isinstance check for user_id at function entry
  - Add return type annotations to get_user(), fetch_data(), process_result()

Reasoning: Core logic is correct but lacks defensive programming
patterns expected for production code.

Loop Action: continue

Next: Address the suggestions above, then run `ooo qa` again to re-check.
```

## RFC #1392 State Breadcrumb Footer

Your final response MUST end with exactly one breadcrumb footer line:

```
◆ <current state> → next: <recommended action>
```

Derive `<current state>` from live session state via `ouroboros_session_status` when that MCP projection is available; otherwise derive it from this skill's actual outcome. Never use a linear `Step N of M` footer because Ouroboros is an evolutionary loop. When the next action is genuinely a choice, list 2-3 honest options in the `next:` clause. The breadcrumb line must be the last line of the response.
