agentleFS
AgentShekelAgentShekel/agentic-workflow/skills/post-deploy-qa/SKILL.md

post-deploy-qa

Skill4 starsChanged 29 days agoMITView on GitHub

[METHODOLOGY] Post-deploy verification (execute AVP from tech-spec on live environment, verify acceptance criteria from user-spec + tech-spec, pick up deferred criteria from pre-deploy QA report) using MCP tools (Telegram MCP, Playwright, curl, bash). Preloaded by post-deploy-qa agent.

1 other project uses a version of this, 1 of them edited.

Adopted by

Most recently taken up by

The file

Show its rules and text

We split this skill into the rules it gives an agent

13 rules. About 0 are common, 9 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈9

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If tech-spec has no AVP section — still proceed with acceptance criteria verification.

    line 22
  2. Distinctive:

    Read AVP section — it lists verification steps with expected outcomes and MCP tools to use

    line 32
  3. Distinctive:

    Use the specified MCP tool (Telegram MCP, Playwright, curl, bash, etc.)

    line 34
  4. Very specific:

    If MCP tool is unavailable — mark step as not_verifiable, continue with remaining steps

    line 38
  5. Very specific:

    Checkpoint: All AVP steps executed or marked not_verifiable.

    line 40
  6. Distinctive:

    Verify all acceptance criteria from user-spec and tech-spec on live environment.

    line 44
  7. Very specific:

    Read pre-deploy QA report (logs/working/qa-report.json) — check deferredToPostDeploy section

    line 46
  8. Very specific:

    Checkpoint: All acceptance criteria verified, or marked blocked with manual verification plan.

    line 56
  9. Distinctive:

    When Playwright MCP is available and the feature has UI components:

    line 115
  10. Distinctive:

    Verify key elements exist and contain expected content

    line 121
  11. Distinctive:

    Verify layout doesn't break at each size

    line 131
  12. Distinctive:

    Every finding includes concrete reproduction: steps, expected vs actual, tool output.

    line 137
  13. Distinctive:

    If all MCP tools are unavailable — report that automated verification is not possible, suggest manual steps.

    line 138

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Post-deploy QA

Input Requirements

Read before starting:

  • user-spec.md — acceptance criteria
  • tech-spec.md — Agent Verification Plan (AVP) section + technical acceptance criteria
  • decisions.md — deviations from plan (if exists)
  • Pre-deploy QA report (logs/working/qa-report.json) — check deferredToPostDeploy section for criteria that could not be verified pre-deploy
  • Confirmation that deploy is complete and environment is live

If tech-spec has no AVP section — still proceed with acceptance criteria verification.

Verification Methodology

Two verification directions (both required):

1. Agent Verification Plan (AVP)

Execute each step from AVP section in tech-spec:

  1. Read AVP section — it lists verification steps with expected outcomes and MCP tools to use
  2. For each step:
    • Use the specified MCP tool (Telegram MCP, Playwright, curl, bash, etc.)
    • Perform the described action on live environment
    • Compare result with expected outcome
    • Record: tool used, step performed, result
  3. If MCP tool is unavailable — mark step as not_verifiable, continue with remaining steps

Checkpoint: All AVP steps executed or marked not_verifiable. Proceed to acceptance criteria.

2. Acceptance Criteria Verification

Verify all acceptance criteria from user-spec and tech-spec on live environment. This catches criteria that pre-deploy QA could not verify without a live system.

  1. Read pre-deploy QA report (logs/working/qa-report.json) — check deferredToPostDeploy section
  2. For each deferred criterion — follow the verification steps specified in the pre-deploy report
  3. Also re-check all acceptance criteria from user-spec and tech-spec against live behavior
  4. For each criterion:
    • passed — verified on live environment, evidence provided
    • failed — live behavior does not meet the criterion
    • blocked — cannot verify due to external conditions (no data, third-party service down). Provide a concrete manual verification plan for the user: what to check, when, how

A blocked criterion requires user follow-up before the feature can count as fully verified.

Checkpoint: All acceptance criteria verified, or marked blocked with manual verification plan.

Severity Classification

  • critical — verification step failed, live functionality broken, data integrity at risk
  • major — works but with significant issues visible in production
  • minor — cosmetic, non-functional discrepancies

Output Format

Return findings as JSON. Reason: orchestrator parses this to decide pass/fail and log findings.

{
  "status": "passed | failed",
  "summary": {
    "totalSteps": 0,
    "passed": 0,
    "failed": 0,
    "blocked": 0,
    "notVerifiable": 0,
    "criticals": 0,
    "majors": 0,
    "minors": 0
  },
  "agentVerification": [
    {
      "step": "Send /start to bot",
      "tool": "telegram_mcp",
      "status": "passed | failed | not_verifiable",
      "details": "Bot responded with welcome message"
    }
  ],
  "acceptanceCriteria": [
    {
      "id": "US-5",
      "criterion": "Titles generated with correct declensions",
      "source": "user-spec | tech-spec | deferred-from-pre-deploy",
      "status": "passed | failed | blocked",
      "evidence": "Checked live output, title 'В компании X работает...' uses correct declension",
      "manualVerificationPlan": "Only if blocked — what the user should check, when, how"
    }
  ],
  "findings": [
    {
      "severity": "critical | major | minor",
      "title": "Bot does not respond to /start",
      "expected": "Welcome message within 3 seconds",
      "actual": "No response after 10 seconds",
      "reproduction": "Steps to reproduce..."
    }
  ]
}

Status decision: passed if zero criticals, failed if one or more criticals.

Playwright Integration

When Playwright MCP is available and the feature has UI components:

  1. Structured smoke tests — for each user-facing acceptance criterion:
    • browser_navigate to the relevant page
    • browser_snapshot to capture DOM state
    • browser_take_screenshot for visual evidence
    • Verify key elements exist and contain expected content
  2. Interactive flow verification — for multi-step user flows:
    • browser_fill_form for input fields
    • browser_click for buttons/links
    • browser_wait_for for async operations
    • Capture before/after screenshots
  3. Responsive checks (if applicable):
    • browser_resize to test breakpoints (mobile: 375px, tablet: 768px, desktop: 1280px)
    • Verify layout doesn't break at each size
  4. Evidence collection: Save screenshots to logs/working/screenshots/ with descriptive names. Reference in the QA report JSON.

Guidelines

  • Every finding includes concrete reproduction: steps, expected vs actual, tool output.
  • If all MCP tools are unavailable — report that automated verification is not possible, suggest manual steps.
  • Empty findings array = clean verification.

Final Check

Before finishing, verify:

  • All AVP steps executed or marked not_verifiable
  • All deferred criteria from pre-deploy QA report addressed
  • All acceptance criteria from user-spec and tech-spec verified on live environment
  • Every blocked criterion has a manual verification plan (what to check, when, how)
  • Output JSON is valid, status reflects critical count

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.