wolfe-jam/faf-skills/wjttc-tester

Claude Code and agent skill by wolfe-jam/faf-skills

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Checking that the SKILL.md file is still in the repository.

First checks that a failing test still means a real failure, then runs the plan, reproduces and root-causes each failure, and writes a WJTTC report sorted by severity (Brake, Engine, Aero, Tyre, Pit) with a verdict. Use when someone wants tests run or a bug chased down: "run the tests and tell me what broke", "reproduce this bug", "can I trust our CI?". Runs and reports; wjttc-builder plans and writes the tests.

Install

npx vskill@latest install wolfe-jam/faf-skills/wjttc-tester

SKILL.md

yaml
v: 1
needs:
- "the project's test runner"
- "faf-cli on Node 22+ (not installed: run `npx faf-cli <command>` in place of `faf <command>`)"
reads: [the test plan, the tests, CI results, the code under test]
writes: ["the WJTTC report in ./wjttc-reports/ (or a path the user gives)"]
network: []
publishes: false
done_when: "every test has run, each failure is reproduced and root-caused, and the WJTTC report is saved with its verdict"
project: project.faf

<!-- faf:end -->

WJTTC Championship Tester

"We break things so others never have to know they were broken."

Apply championship-grade standards to software testing. When brakes must work, so must the code. This skill executes test plans and files reports — it is the driver, not the engineer. To plan and generate the suite, use wjttc-builder.

When to use this skill

  • Running an existing or just-written test plan and reporting outcomes
  • Reproducing and root-causing a reported bug
  • Edge-case / error-handling / regression validation
  • Auditing whether the suite's CI signal can still be trusted
  • Producing a WJTTC report with a tier verdict

The WJTTC five tiers

Triage every test by blast radius. The first three set severity; Tyre and Pit cover durability and the release gate.

TierMeaningExamples
BrakeLife-critical — failure is catastrophicdata loss, auth bypass, payment errors, destructive ops without confirm
EnginePerformance-critical — wrong results / poor UXAPI accuracy, data transforms, calculations, format compliance, perf
AeroPolish & edge cases — minor inconvenienceUI quirks, rare message formatting, optional-feature edges, docs
TyreDurability under load — degradation over timestress/volume, concurrency, memory growth, large inputs
PitRelease gate — the stop that lets you gosmoke/regression suite, CI green, the WJTTC report filed

Test Brake first. If the brakes don't work, nothing else matters.

Step 0 — Signal Integrity pre-audit (run BEFORE adding/running anything new)

Red CI is a contract: it must always mean "stop, look, fix." A suite with high coverage but flaky reds is less trustworthy than a smaller suite with zero false alarms — because the team has stopped reading the reds. Fix the signal before you add more tests.

Method — classify the last 30 days of CI failures:

BucketDefinitionVerdict
Real bugRed mapped to a real defect; fixed by a code change✓ Signal worked
FlakeTiming/network/concurrency noise; passed on rerun, no code change✗ Test design defect
InfraMissing secret, runner image change, upstream dep — not the code✗ Workflow design defect

Signal Integrity Score: SI = Real bugs / (Real bugs + Flakes + Infra) × 100

SI %VerdictAction
100%✪Maintain — exemplary signal
95–99%★ ChampionshipAnnotate any flake immediately
85–94%◇ AcceptableSchedule the flake-class fix this sprint
70–84%● ErodingStop adding tests — fix flakes first
<70%○ Dead signalBlock merges until signal restored

Eliminate on sight: hard absolute-time perf asserts on shared runners (expect(t).toBeLessThan(30)) → move to a non-gating workflow; network calls in the main suite → mock at the boundary; concurrency tests without explicit ordering; secret-dependent steps that hard-fail when missing → grey-skip.

The inverse rule: green CI that passes while something is broken is equally a violation. If a real bug shipped despite green, write the regression test BEFORE the fix lands.

The conversation is the real gate. CI is supporting infrastructure for the human + AI audit; flaky CI wastes the audit's bandwidth. Signal Integrity keeps CI worthy of the conversation.

Execution loop

  1. Scope — what should it do? happy path, edges, failure modes, perf targets, tier of each.
  2. Audit signal (Step 0) before trusting or extending the suite.
  3. Run each test: set up, prepare data, execute, observe actual vs expected, record pass/fail/blocked, capture evidence on failure.
  4. Reproduce every failure deterministically; root-cause it; note the fix.
  5. Tier coverage check — confirm every test is tiered:

``bash faf wjttc --path tests # audit tier coverage (vendor-neutral) faf wjttc --strict --json # CI gate: non-zero if any test is untiered ``

  1. Report — file the WJTTC report (below), then surface the tier verdict.

WJTTC report format

Save reports to `./wjttc-reports/` in the project under test (or a path the user specifies). Never write to an absolute/personal path. Name files YYYY-MM-DD-{project}-{feature}-tests.yaml.

yaml
---
# WJTTC Test Report
project: "project-name"
feature: "feature-being-tested"
date: "2026-06-26"
tier: "Engine" # Brake | Engine | Aero | Tyre | Pit
result: "PASS" # PASS | FAIL | BLOCKED
environment: "OS, runtime version, key deps"
---
## Summary
objective: What was tested
totals: { total: 25, passed: 23, failed: 2, blocked: 0, pass_rate: "92%" }
## Failures
- name: "Long-string handling"
tier: "Engine"
status: "FAIL"
steps: ["...", "..."]
expected: "Handle gracefully"
actual: "Crash"
error: "RangeError: ..."
root_cause: "Unbounded buffer"
fix: "Cap input length / stream"
## Edge cases
- { case: "Empty string", input: "''", expected: "error", actual: "error", status: "PASS" }
- { case: "Unicode", input: "🏎️", expected: "stored", actual: "stored", status: "PASS" }
## Performance
- { op: "file read", target: "<50ms", actual: "18ms", status: "PASS" }
- { op: "parse YAML", target: "<50ms", actual: "12ms", status: "PASS" }
## Bugs found
- id: 1
title: "..."
severity: "Brake" # tier doubles as severity
reproducibility: "Always"
impact: "Who is affected, how serious"
fix: "..."
## Coverage
tested: ["happy path", "edges", "error handling", "perf"]
not_tested: ["concurrent access", "files >100MB"]
## Verdict
tier: "◆ Silver" # from the tier table below
to_next: ["Fix 2 failing Engine tests", "Add Tyre concurrency tests"]

Tier verdict

Map the pass rate (or SI score) to the single canonical FAF tier ladder. No second ladder, no medals.

ScoreTierSymbol
100%Trophy✪
99%Gold★
95%Silver◆
85%Bronze◇
70%Green●
55%Yellow●
1%Red○
0%White♡

The FAF score is deterministic — same input, same score. A test report should be just as falsifiable: every verdict traces to a reproducible run. FAF doesn't lie.

WJTTC method notes

  • Test with real data, not just sanitized inputs — anonymized production data, messy inputs, production-like volume.
  • Document every failure so it can be reproduced: what failed, how to repro, why it matters, how to fix.
  • Tier before you test — severity is the tier, so triage first; faf wjttc enforces that nothing ships untiered.
  • Wire it into CI with TAF receipts so the report is part of the record, not a one-off:

``bash faf taf setup --write # create .github/workflows/taf.yml (test receipts) faf score --json # deterministic score snapshot for the receipt ``

Quick checklist (before release)

  • [ ] Signal Integrity audited (SI ≥ 85%)
  • [ ] Brake tests pass — zero tolerance
  • [ ] Edges + error handling tested
  • [ ] Tyre: behaves under load / concurrency
  • [ ] faf wjttc --strict green — every test tiered
  • [ ] Regression (Pit) suite passes
  • [ ] WJTTC report filed in ./wjttc-reports/
  • [ ] Pass rate ≥ 85% (◇ Bronze, production-ready)

Resources

  • Website: https://faf.one · Skills Site: https://skills.faf.one
  • faf-cli: https://github.com/Wolfe-Jam/faf-cli
  • Sibling skill: wjttc-builder (plan + generate the suite)

Made by wolfejam.dev — "We break things so others never have to know they were broken."

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
4
7-day trend score
8

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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