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 runtime-simulation-validationgit 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/runtime-simulation-validation)<a href="https://agentmods.dev/skills/paruff/ufawkesai/runtime-simulation-validation"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/runtime-simulation-validation/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/runtime-simulation-validation"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/runtime-simulation-validation.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 | $0.00027 | $0.00706 |
| Opus 5 | $0.00014 | $0.00353 |
| Sonnet 5 | $0.00005 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
runtime-simulation-validation scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `curl` / HTTP client for health check validation How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Runtime Simulation Validation
Load trigger:
"load runtime-simulation-validation skill"> DORA: Cap 5 (Small Batches / Shift Left on Quality) Token cost: Low
Purpose
Validate runtime behavior in a simulated environment.
Responsibilities
- Deploy build output to local/simulated environment
- Validate readiness and liveness probes
- Validate logs and metrics
- Detect runtime errors
Inputs
- Build output (code, manifests)
- Simulation environment (kind, minikube, Docker Compose, local server)
Outputs
runtime-simulation.jsonruntime-errors.txt
Validation Rules
Startup
- Application starts without errors
- Startup completes within timeout
- Liveness probe responds
- Readiness probe responds
Runtime
- No crash loops or restarts
- No OOM kills
- No unhandled exceptions in logs
- Graceful shutdown works
Logs
- No ERROR or FATAL messages in logs
- No stack traces in logs
- No sensitive data in logs
- Logging format consistent
Health Endpoints
-
/healthzreturns 200 -
/readyzreturns 200 (or 503 when not ready) -
/metricsreturns valid Prometheus format (if applicable)
Simulation Environments
| Environment | Tool | Use When |
|---|---|---|
| Kubernetes (local) | kind / minikube | K8s manifests to validate |
| Docker | Docker Compose | Multi-container apps |
| Standalone | Direct execution | Simple services |
| Mock server | WireMock / MockServer | External dependency simulation |
Tools
kubectlfor K8s simulationdocker-composefor multi-container simulationcurl/ HTTP client for health check validation- Log aggregator for log analysis
Output Format
{
"skill": "runtime-simulation-validation",
"status": "pass | fail",
"startup": {
"starts_successfully": true,
"startup_time_ms": 1200,
"liveness_probe": "healthy",
"readiness_probe": "ready"
},
"runtime": {
"crash_loops": 0,
"oom_kills": 0,
"unhandled_exceptions": 0
},
"logs": {
"error_count": 0,
"fatal_count": 0,
"sensitive_data_found": false
},
"health_endpoints": {
"/healthz": 200,
"/readyz": 200
},
"errors": []
}
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.
- 8d ago First seen · 118 lines · 27 tokens per session scan A 9d5a924e8ca5
runtime-simulation-validation is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 19d ago), licensed MIT. It adds 27 tokens to every session and 706 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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.