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.
npx skills add paruff/uFawkesAI --skill smoke-testsgit clone --depth 1 https://github.com/paruff/uFawkesAIWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/paruff/ufawkesai/smoke-tests)<a href="https://agentmods.dev/skills/paruff/ufawkesai/smoke-tests"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/smoke-tests/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/paruff/ufawkesai/smoke-tests"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/smoke-tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.00447 |
| Opus 5 | $0.00015 | $0.00224 |
| Sonnet 5 | $0.00006 | $0.00089 |
| Haiku 4.5 | $0.00003 | $0.00045 |
Grade A, and why
deployment-smoke-tests 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 10d ago.
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.
What it actually says
Skill: Deployment Smoke Tests
Load trigger:
"load deployment-smoke-tests skill"> DORA: Cap 4 (CI/CD Automation) Token cost: Low
Purpose
Validate that the deployed application is healthy and functional.
Responsibilities
- Run API smoke tests
- Validate health endpoints
- Validate rollout status
Inputs
- Deployed environment
Outputs
smoke-tests.json
Smoke Test Targets
| Target | Endpoint | Expected |
|---|---|---|
| Health | /health |
200 OK |
| Readiness | /ready |
200 OK |
| Version | /version |
Current version |
| API | /api/v1/status |
200 OK |
Validation Rules
- Health endpoint returns 200
- Readiness endpoint returns 200
- Version endpoint returns correct version
- API endpoints respond correctly
- Response time < 500ms
Output Format
{
"skill": "deployment-smoke-tests",
"status": "pass | fail",
"tests": [
{ "endpoint": "/health", "status": 200, "time_ms": 50 },
{ "endpoint": "/ready", "status": 200, "time_ms": 45 },
{ "endpoint": "/version", "status": 200, "body": "1.3.0", "time_ms": 30 }
],
"total_tests": 3,
"passed": 3,
"failed": 0
}
Success Criteria
- Healthy deployment
- All smoke tests pass
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.
- 10d ago First seen · 72 lines · 31 tokens per session scan A 414792214277
deployment-smoke-tests is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 17d ago), licensed MIT. It adds 31 tokens to every session and 447 once invoked, about $0.0002 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.
Other skills, from other repositories
template-formal
Strongly-typed multiagent ant-robot colony exemplar — ADTs, session-typed protocols, affine-discipline resource handles, storage-as-functor framing, Active-Inference-flavored decision loop, mypy-as-oracle negative controls.
template-reproducibility-audit
Deterministic reproducibility audit — fixed seeds, regenerate-from-clean, double-run diff before Zenodo/arXiv/release. USE WHEN outputs drift between runs, "worked on my machine", need regenerate-from-clean proof, or pre-release reproducibility check — even without naming docs/prompts.
template-test-creation
Create pytest suites under the no-mocks policy — real data, temp files, subprocess, pytest-httpserver. USE WHEN adding tests, raising coverage, testing new src/ module, or user forbids mocks.
infrastructure-benchmark
Deterministic benchmark harnesses for public template exemplars. Use when scoring generated project outputs against benchmark manifests, refreshing the default template smoke manifest, checking publication-readiness rubrics, or adding bounded no-network readiness checks for public template outputs.
infrastructure-sia
Skill for the Self-Improvement Agent (SIA) harness contract. Use when validating task public/private layouts, generation artifact trees, evaluation runners, fixture replay loops, or opt-in live Meta→Target→Feedback cycles in template projects.
template-sia
SIA (Self-Improvement Agent) harness exemplar — Meta/Target/Feedback loops, public/private splits, fixture replay, fail-closed validation.