mcaf-testing

A testing workflow for adding or updating automated tests around a code change. TDD, or test-driven development, means writing a test that fails first, then changing the code until it passes.

In plain words
What is it for?
Use it for bug fixes, new features, or refactors to inspect the repository’s rules, derive test scenarios, run the build and tests, and record verification results.
Why use it?
It helps ensure tests describe documented behaviour, cover failures and edge cases, and provide evidence that the change works.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/managedcode/geminisharpsdk/mcaf-testing
Any agent
npx skills add managedcode/GeminiSharpSDK --skill mcaf-testing
Clone the repo
git clone --depth 1 https://github.com/managedcode/GeminiSharpSDK

Made for: Claude Code, Codex.

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 997 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00075 $0.00997
Opus 5 $0.00037 $0.00498
Sonnet 5 $0.00015 $0.00199
Haiku 4.5 $0.00007 $0.00100

Measured yesterday against content hash aa5400032d50, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcaf-testing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/skills/mcaf-testing/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MCAF: Testing

Outputs

  • New/updated automated tests that encode documented behaviour (happy path + negative + edge), with integration/API/UI preferred
  • For new behaviour and bugfixes: tests drive the change (TDD: reproduce/specify → test fails → implement → test passes)
  • Updated verification sections in relevant docs (docs/Features/*, docs/ADR/*) when needed (tests + commands must match reality)
  • Evidence of verification: commands run (build/test/coverage/analyze) + result + the report/artifact path written by the tool (when applicable)

Workflow

  1. Read AGENTS.md:
    • commands: build, test, format, analyze, and the repo’s coverage path (either a dedicated coverage command or a test command that generates coverage)
    • testing rules (levels, mocks policy, suites to run, containers, etc.)
  2. Start from the docs that define behaviour (no guessing):
    • docs/Features/* for user/system flows and business rules
    • docs/ADR/* for architectural decisions and invariants that must remain true
    • if the docs are missing/contradict, fix the docs first (or write a minimal spec + test plan in the task/PR)
    • follow AGENTS.md scoping rules (Architecture map → relevant docs → relevant module code; avoid repo-wide scanning)
  3. Follow AGENTS.md verification timing (optimize time + tokens):
    • run tests/coverage only when you have a reason (changed code/tests, bug reproduction, baseline confirmation)
    • start with the smallest scope (new/changed tests), then expand to required suites
  4. Define the scenarios you must prove (map them back to docs):
    • positive (happy path)
    • negative (validation/forbidden/unauthorized/error paths)
    • edge (limits, concurrency, retries/idempotency, time-sensitive behaviour)
    • for ADRs: test the invariants and the “must not happen” behaviours the decision relies on
  5. Choose the highest meaningful test level:
    • prefer integration/API/UI when the behaviour crosses boundaries
    • use unit tests only when logic is isolated and higher-level coverage is impractical
  6. Implement via a TDD loop (per scenario):
    • write the test first and make sure it fails for the right reason
    • implement the minimum change to make it pass
    • refactor safely (keep tests green)
  7. Write tests that assert outcomes (not “it runs”):
    • assert returned values/responses
    • assert DB state / emitted events / observable side effects
    • include negative and edge cases when relevant
  8. Keep tests stable (treat flakiness as a bug):
    • deterministic data/fixtures, no hidden dependencies
    • avoid sleep-based timing; prefer “wait until condition”/polling with a timeout
    • keep test setup/teardown reliable (reset state between tests)
  9. Coverage (follow AGENTS.md, optimize time/tokens):
    • run coverage only if it’s part of the repo’s required verification path or if you need it to find gaps
    • run coverage once per change (it is heavier than tests)
    • capture where the report/artifacts were written (path, summary) if generated
  10. If the repo has UI:
  • run UI/E2E tests
  • inspect screenshots/videos/traces produced by the runner for failures and obvious UI regressions
  1. Run verification in layers (as required by AGENTS.md):
  • new/changed tests first
  • then the related suite
  • then broader regressions if required
  • run analyze if required
  1. Keep docs and skills consistent:
  • ensure docs/Features/* and docs/ADR/* verification sections point to the real tests and real commands
  • if you change test/coverage commands or rules, update AGENTS.md and this skill in the same PR

Read the full file on GitHub · 68 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 68 lines · 75 tokens per session scan A aa5400032d50

Subscribe to this mod's changes

mcaf-testing is a skill published in the GitHub repository managedcode/GeminiSharpSDK (2 stars, last pushed 4mo ago), licensed MIT. It adds 75 tokens to every session and 997 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.