qa-team

Determine the base branch. If the user provided $ARGUMENTS, use that as the base branch. Otherwise, default to master.

Create a run directory outside the repository (session scratchpad or mktemp -d — never inside the repo), then collect context into it:

RUN_DIR="$(mktemp -d "${TMPDIR:-/tmp}/qa-team-XXXXXX")"
mkdir -p "$RUN_DIR/personas" "$RUN_DIR/claimed"
git diff <base>...HEAD --name-only > "$RUN_DIR/files.txt"
git log <base>...HEAD --oneline > "$RUN_DIR/commits.txt"
git diff <base>...HEAD > "$RUN_DIR/diff.patch"

The run directory holds the persona queue, the claim script, and the generated launch scripts (Step 3); the diff is baked into the shared agent prompt by the build script, without passing through the model (see Step 3 for why). Keep diff.patch on disk — the build script reads it, and oversized diffs fall back to it at review time.

If there are no changes, inform the user and stop.

Categorize changed files to determine which agents are relevant:

Always run at least 4 specialist agents. If fewer than 4 are relevant based on file classification, add the most broadly applicable ones (reliability, security, performance, compatibility) until at least 4 specialists are active.

Always launch both generalist agents (generalist-a and generalist-b) regardless of file classification. They review all changes.

Why this protocol exists: every agent request carries a large fixed prefix (system prompt, tools, project context, and the user prompt) that is prompt-cached only when the prompt is byte-identical across agents. Prompt caching is strict-prefix based: one divergent character anywhere in the prompt forces the entire prefix — tens of thousands of tokens — to be re-ingested at full price by every agent. Four rules follow:

1. Every agent gets the same prompt, byte for byte — including the full diff. The diff inside the identical prompt is part of the shared cached prefix, so followers ingest it at cache-read prices instead of each re-paying write prices for a file-read tool result.
2. The launch scripts are built by a shipped build tool, never typed by the orchestrator. scripts/build_launch_scripts.js JSON-encodes the prompt (diff included) into two Workflow script files, so the diff never passes through the model as output tokens and the two scripts' prompts cannot drift apart by a stray byte.
3. Per-agent divergence (the persona) arrives via a tool result, not the prompt. Each agent's first action is to run a claim script that atomically assigns it a persona. Tool results come after the shared prefix, so they don't break the cache. Never deliver the persona as a follow-up message to a completed agent — resuming a finished agent rebuilds its request from scratch and misses the cache entirely.
4. Stagger the launch. The first reviewer launches alone; its persona claim appearing in claimed/ is the signal that its first request finished and the shared prefix is cached. Only then do the remaining reviewers launch in parallel and read it. A simultaneous cold launch makes every agent write the prefix instead of reading it (measured: two agents launched together each wrote the full ~42k tokens).

CRITICAL — Agent independence: Each agent must operate in total isolation. Do NOT include any of the following in the shared prompt or in any persona file:

• Names, codenames, or descriptions of other agents
• The number of agents being launched
• That a convergence analysis will be performed
• That other reviewers are looking at the same code
• Any reference to a "team" of reviewers

Each agent believes it is the sole reviewer. This ensures fully independent findings. (The persona queue on disk necessarily contains the other personas; the shared prompt forbids agents from inspecting the run directory, which preserves independence in practice.)

Write one file per selected agent to $RUN_DIR/personas/, named with a numeric prefix so claim order is deterministic (01-generalist-a.md, 02-generalist-b.md, 03-security.md, 04-database.md, ...). The generalists come first because they run in every review, so reviewer 1 — the agent that warms the shared cache — is always the same persona regardless of which specialists the diff selects. The number of persona files must equal the number of reviewers you will launch — the build script derives the launch count from this directory.

For each specialist (security, database, reliability, performance, frontend, compatibility, data-integrity, copy), the file contains:

Your assigned review focus: {FOCUS_AREA}

## Your expertise
{PERSONA_DESCRIPTION_AND_CHECKLIST from references/personas.md — this agent's section only}

## Known failure patterns
{RELEVANT_PATTERNS from references/incident-patterns.md — only patterns matching
this agent's focus area. Omit this entire section for the copy persona.}

Always include both generalist personas. Generalist A (fresh-eyes senior engineer):

Your assigned review focus: general correctness and safety

You are a senior software engineer reviewing this code change for the first time.
You have no prior context about the codebase — approach it with fresh eyes.

Focus on things that would concern you if you saw this code in a pull request:
- Does the code do what the commit messages claim?
- Are there obvious bugs, logic errors, or edge cases?
- Is error handling adequate? What happens when things fail?
- Are there race conditions or concurrency issues?
- Is the code readable and maintainable?
- Are there any "that looks wrong" moments?

Do NOT focus on style, formatting, or minor nits. Focus on correctness and safety.
This focus has no formal checklist — omit the Checklist Coverage section from your review.

Generalist B (adversarial tester):

Your assigned review focus: breakability

You are a QA engineer who tries to break things. Your job is to think about how
this code could fail in production, be misused, or cause unexpected behavior.

Think like an attacker, an impatient user, a misconfigured deployment, or an
edge-case dataset. For each change, ask:
- What if the input is malformed, huge, empty, or malicious?
- What if the external service is slow, down, or returns garbage?
- What if two requests hit this code at the same time?
- What if this runs against a database with millions of rows?
- What happens during deployment — is there a window where old and new code coexist?
- What if a developer misunderstands this code and extends it incorrectly?

Do NOT focus on style or readability. Focus on breakability.
This focus has no formal checklist — omit the Checklist Coverage section from your review.

Both live in this skill's scripts/ directory — copy the claim script into the run directory, then build the two Workflow launch scripts from the run directory's contents:

SKILL_DIR="<this skill's base directory>"
cp "$SKILL_DIR/scripts/claim_persona.sh" "$RUN_DIR/"
node "$SKILL_DIR/scripts/build_launch_scripts.js" "$RUN_DIR"

claim_persona.sh atomically hands each caller the next unclaimed persona (mv is atomic, so concurrent agents each win a distinct one). build_launch_scripts.js JSON-encodes the shared review prompt — claim instruction, changed files, commit messages, and the full diff (or a read-from-disk instruction when the diff exceeds ~200 KB) — into $RUN_DIR/launch_first.js and $RUN_DIR/launch_rest.js, sizing the parallel fan-out from the persona count. The prompt text itself lives in the build script; do not re-type or edit the generated files.

1. Invoke the Workflow tool with {scriptPath: "$RUN_DIR/launch_first.js"}. It launches reviewer 1 alone, in the background.

2. Poll for reviewer 1's persona claim — the signal that its first request completed (~15 seconds in) and the shared prefix (diff included) is cached:

   Copy

   timeout 120 bash -c 'until [ -n "$(ls -A '"$RUN_DIR"'/claimed)" ]; do sleep 1; done'

   Do NOT wait for the first workflow run to complete — reviewer 1 keeps reviewing while the rest launch, so all reviewers run concurrently apart from this brief warm-up window. If the poll times out, first check whether the launch_first run errored, then continue and note in the final report that the run proceeded uncached — a cache miss costs money, not correctness, but it should be attributable.

3. Invoke the Workflow tool with {scriptPath: "$RUN_DIR/launch_rest.js"}. It launches the remaining reviewers in parallel; each reads the cached prefix reviewer 1 wrote.

4. Both workflow runs return { reviews: [...] } as they complete — collect both for Step 4. Failed reviewers appear as explicit REVIEWER FAILED: ... sentinel entries, never as silently missing reviews.

5. Reconcile before synthesizing: personas/ must be empty and the number of collected reviews (sentinels included) must equal the persona count. On a mismatch, name the unclaimed or unreviewed personas in the report — or relaunch a single agent for the leftovers — rather than presenting partial coverage as a complete review. (Known limitation: a claim is not idempotent — an agent that reruns the claim consumes a second persona and starves a later reviewer; the reconciliation step is what catches this.)

After the report is written, best-effort clean up the run directory (rm -rf "$RUN_DIR") — it contains the full diff on disk and has no further use.

Fallback: if the Workflow tool is unavailable, launch agents directly with the Agent tool using one shared prompt that references the run-dir files instead of embedding the diff (Read $RUN_DIR/diff.patch etc. — hand-typing the diff N times costs more than the cache saves). Launch the first agent, run the same claimed/ poll as above, then launch the rest in a single message in parallel.

After all agents complete, compile their findings into a unified report.

Check if multiple agents flagged the same file or concern. Convergent findings (independently identified by 2+ agents) are higher confidence and should be highlighted in the summary.

Compute an overall risk score:

• CRITICAL: Any agent returned Risk Level CRITICAL -> overall CRITICAL
• HIGH: 2+ agents returned Risk Level HIGH, or 1 HIGH + 2 MEDIUM agents -> overall HIGH
• MEDIUM: 1 agent returned Risk Level HIGH, or 3+ agents returned Risk Level MEDIUM -> overall MEDIUM
• LOW: Only LOW/NONE agent risk levels -> overall LOW

Map overall risk to a verdict:

• ✅ APPROVE — Overall LOW risk, no actionable findings
• 💬 APPROVE WITH NITS — MEDIUM risk, minor suggestions that won't block merge
• ⚠️ REQUEST CHANGES — HIGH risk, specific fixes needed before merge
• 🚫 BLOCKED — CRITICAL risk, blocking security/data issues found

Write the report to QAREPORT.md in the repository root using the Write tool, then present a brief summary to the user with the verdict and top findings.

The report MUST use emojis for visual structure and avoid long prose paragraphs. Keep everything scannable — tables, checklists, and short bullet points.

# 🔍 QA Team Review Report

| Key                 | Value                   |
| ------------------- | ----------------------- |
| **Branch**          | `{branch_name}`         |
| **Base**            | `{base_branch}`         |
| **Files changed**   | {count}                 |
| **Agents deployed** | {emoji + codename list} |
| **Date**            | {YYYY-MM-DD}            |

---

## 📋 Summary

{2-4 bullet points: what was changed and why. No long paragraphs.}

### Key findings

- {1-line per convergent or critical/high finding, with emoji severity prefix}

---

## 🏁 Verdict

> {emoji} **{APPROVE / APPROVE WITH NITS / REQUEST CHANGES / BLOCKED}**

{1-2 sentences explaining the verdict. Reference the top blocking items if not approving.}

---

## 👥 Agent summaries

| Agent             | Risk                 | Summary                           |
| ----------------- | -------------------- | --------------------------------- |
| 🔒 security       | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🗄️ database       | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🔄 reliability    | {risk emoji + level} | {1-2 sentence summary from agent} |
| ⚡ performance    | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🎨 frontend       | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🔗 compatibility  | {risk emoji + level} | {1-2 sentence summary from agent} |
| 📊 data-integrity | {risk emoji + level} | {1-2 sentence summary from agent} |
| ✏️ copy           | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🧑‍💻 generalist-a   | {risk emoji + level} | {1-2 sentence summary from agent} |
| 🕵️ generalist-b   | {risk emoji + level} | {1-2 sentence summary from agent} |

(Only include rows for agents that were deployed.)

**Note:** ✏️ copy findings are always non-blocking nits. 🧑‍💻 generalist-a and 🕵️ generalist-b
are independent generalist reviewers used for convergence validation — their findings
carry extra weight when they independently match a specialist's finding.

Risk emojis: 🔴 CRITICAL, 🟠 HIGH, 🟡 MEDIUM, 🟢 LOW, ⚪ NONE

---

## 📝 Findings

Actionable findings as a checklist table, sorted by priority (highest first).

Each row is a checklist item. The `Status` column starts as `⬜ Open`.
Use convergence markers when 2+ agents flagged the same issue.

| #   | Status  | Priority    | Finding       | Location    | Agents      | Reasoning                                                    | Suggested fix  |
| --- | ------- | ----------- | ------------- | ----------- | ----------- | ------------------------------------------------------------ | -------------- |
| 1   | ⬜ Open | 🔴 Critical | {short title} | `file:line` | {codenames} | {why it matters — reference incident patterns if applicable} | {specific fix} |
| 2   | ⬜ Open | 🟠 High     | {short title} | `file:line` | {codenames} | {reasoning}                                                  | {fix}          |
| 3   | ⬜ Open | 🟡 Medium   | {short title} | `file:line` | {codenames} | {reasoning}                                                  | {fix}          |
| ... | ...     | ...         | ...           | ...         | ...         | ...                                                          | ...            |
| N   | ⬜ Open | 🟢 Low      | {short title} | `file:line` | {codenames} | {reasoning}                                                  | {fix}          |

Priority mapping:

- 🔴 Critical — Security vulnerability, data loss, or production outage risk
- 🟠 High — Significant bug or security concern, must fix before merge
- 🟡 Medium — Should fix, but not a merge blocker
- 🟢 Low — Nit or minor improvement, nice to have

Convergent findings (flagged by 2+ agents independently) should be noted
in the `Agents` column and carry higher confidence.

• references/personas.md -- Full persona descriptions, context, and review checklists for specialist agents (not used for generalists — their persona files are defined inline in Step 3a)

• references/incident-patterns.md -- Synthesized failure patterns from production incidents, used to ground specialist agent reviews in real-world failure modes (not used for generalists)