smoke-test
Run a work-item-scoped real entrypoint smoke test in provider-aware live or guaranteed offline mode, validate outputs and budgets, and emit standardized…
Skill by rafaie
Chalk Labs
Need help deploying smoke-test?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/rafaie-smoke-test
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: testing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/smoke-test
What's inside
- Skill name
smoke-test- Description
- Run a work-item-scoped real entrypoint smoke test in provider-aware live or guaranteed offline mode, validate outputs and budgets, and emit standardized evidence. Use for runnable-path verification or smoke failure reproduction.
- License
- Apache-2.0
- Instructions
- 58 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- files: referenced but missing: scripts/smoke.py
Files (2)
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
1) Resolve the smoke command. - Read `codex.toml` and use `[commands].smoke` when present. - If absent, use `uv run python scripts/smoke.py` when `scripts/smoke.py` exists. - If neither exists, fail as `config_error` and report the missing command/script. 2) Scope smoke to the requested work item when provided. - Prefer `--work-item <work-id>` for `scripts/smoke.py`. - Treat `--feature` as a deprecated compatibility alias only. 3) Run smoke using the real entrypoint path. - Smoke must execute a subprocess command path (CLI/module/script), not only import-level calls. - Use tiny fixture inputs under `tests/fixtures/smoke/` when available. - Pass the selected mode to the child as `SMOKE_MODE`; offline mode must not make provider network calls. - Select live mode only when credentials match a selected scenario provider, unless explicitly forced. 4) Enforce required artifact contract under `artifacts/smoke/<run-id>/` (or equivalent configured directory): - `summary.json` - `cases/<case_id>.json` - `stdout.txt` - `stderr.txt` - `timing.json` 5) Validate outputs. - Always validate the configured JSON Schema, not merely JSON shape. - Always evaluate configured declarative invariants (required paths, equality, membership, and numeric ranges). - Golden comparison is optional per scenario and must support explicit `--record` updates. - Require child usage telemetry when token or cost ceilings are configured, and fail closed when a configured budget cannot be verified. 6) Summarize every run: - command run - work item ID (`work_item`) when provided - fixture(s)/scenario(s) - exit code - artifact locations - wall-clock time - budget telemetry (`requests_used`, `time_budget_exceeded`, max request/time settings) - source identity (Git commit/dirty diff hash, registry hash, fixture hashes, generated time) - failure bucket counts 7) Classify failures into one primary bucket per case/run summary: - `config_error`, `fixture_error`, `auth`, `permission_error`, `network_error`, `timeout`, `rate_limit`, `quota_exceeded`, `provider_error`, `invalid_response`, `parse_error`, `schema_error`, `invariant_error`, `golden_mismatch`, `budget_exceeded`, `artifact_error`, `subprocess_error`, `internal_error` 8) Use this exit-code mapping: - `0` pass - `10` config/fixture/auth/permission failure - `12` artifact failure - `20` subprocess failure - `22` network failure - `23` timeout - `24` rate limit - `25` quota exceeded - `26` provider error - `30` invalid/parse error - `40` schema validation failure - `41` invariants failure - `50` golden mismatch - `55` budget exceeded - `60` internal/unclassified 9) If multiple failures occur, prioritize exit code in this order: - artifact -> config/fixture/auth/permission -> quota -> rate_limit -> network -> timeout -> provider -> subprocess -> invalid/parse -> schema -> invariant -> golden -> budget -> internal 10) Recommend next action: - deterministic smoke/runtime/packaging issues -> `debug-loop` - fixture/golden updates only when behavior change is intentional and documented
From rafaie/codex_home, Apache-2.0.
More from rafaie/codex_home
- 0.547score
implementation-phase
rafaie
Run test-plan, write-tests, and implement-feature as one implementation workflow.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
implement-feature
rafaie
Implement a documented work item AC by AC with scoped quick checks and smoke milestones.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
ship-feature
rafaie
Execute the final gate for an implemented work item: verify acceptance criteria, run full checks and applicable smoke, update architecture/docs/index, and…
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
qa-intake
rafaie
Clarify an ambiguous project or work item request from repository context, produce a verification-focused brief, and route to the correct SDLC skill.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
feature-kickoff
rafaie
Create and initialize a complete work item documentation folder from a backlog item or clarified brief.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
debug-loop
rafaie
Reproduce and fix a deterministic test, smoke, runtime, or packaging failure with a regression test and documented evidence.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
failure-triage
rafaie
Cluster many test, CI, or smoke failures by root signature and produce an ordered repair plan.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
session-start
rafaie
Start a repository work session by reconciling Git state, active work item docs, backlog, and recent verification evidence.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
architecture-updater
rafaie
Update high-level architecture documentation and diagrams from a work item, code diff, and ADRs.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
feature-slicer
rafaie
Slice a large stream or feature request into small, vertically valuable, independently testable work items.
SkillBFreshness: B★ 1Claude Code +9 - 0.539score
release-prep
rafaie
Prepare a multi-work-item release by running the canonical full gate, validating release smoke evidence, finalizing changelog/docs, and summarizing release…
SkillBFreshness: B★ 1Claude Code +9 - 0.539score
backlog-builder
rafaie
Convert a project brief into ordered streams and small shippable work items with stable IDs, acceptance criteria, risks, and dependencies.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 15, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/rafaie/codex_home
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from rafaie
- 0.547score
implementation-phase
rafaie
Run test-plan, write-tests, and implement-feature as one implementation workflow.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
qa-intake
rafaie
Clarify an ambiguous project or work item request from repository context, produce a verification-focused brief, and route to the correct SDLC skill.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
implement-feature
rafaie
Implement a documented work item AC by AC with scoped quick checks and smoke milestones.
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
ship-feature
rafaie
Execute the final gate for an implemented work item: verify acceptance criteria, run full checks and applicable smoke, update architecture/docs/index, and…
SkillBFreshness: B★ 1Claude Code +9 - 0.544score
feature-kickoff
rafaie
Create and initialize a complete work item documentation folder from a backlog item or clarified brief.
SkillBFreshness: B★ 1Claude Code +9 - 0.542score
feature-slicer
rafaie
Slice a large stream or feature request into small, vertically valuable, independently testable work items.
SkillBFreshness: B★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get smoke-test running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
smoke-test skill. Agent Mart. https://agentmart.dev/skills/rafaie-smoke-test (last updated 2026-10-24)