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 yogsoth-ai/stress-test --skill mitigation-validationgit clone --depth 1 https://github.com/yogsoth-ai/stress-testWrote 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/yogsoth-ai/stress-test/mitigation-validation)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/mitigation-validation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/mitigation-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/yogsoth-ai/stress-test/mitigation-validation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/mitigation-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 | $0.00031 | $0.00551 |
| Opus 5.5 | $0.00012 | $0.00220 |
| Sonnet 5.5 | $0.00006 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
mitigation-validation 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mitigation Validation Tactic
Validate that proposed mitigations do not introduce new failure modes — a mini-FMEA on the mitigations themselves.
Orchestration
- Receive proposed mitigation measures from mitigation-design-sop
- failure-mode-extraction identifies potential failure modes of each mitigation:
- Could the prevention measure fail?
- Could the detection mechanism produce false negatives?
- Could the response plan create new problems?
- severity-scoring rates new failure modes
- If any new mode scores H-priority:
- Flag mitigation as risky
- mitigation-design-sop redesigns or adds safeguards
- Re-validate (max 2 iterations to prevent infinite loops)
- re-scoring confirms final S/O/D with validated mitigations
Iteration Control
- Max validation iterations: 2 (prevent infinite recursion)
- If still H-priority after 2 iterations: escalate to human review
- Document residual risk for accepted mitigations
Subagents Dispatched
- failure-mode-extraction (mitigation failure identification)
- severity-scoring (new risk assessment)
- mitigation-design-sop (redesign if needed)
- re-scoring (final confirmation)
Termination Conditions
- All mitigations validated as not introducing H-priority risks
- Max iterations reached (escalate with documentation)
- Residual risk accepted and documented
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| failure-mode-extraction | Extract structured failure mode list from raw scenarios or artifact analysis. Produces standardized failure mode records. |
| mitigation-design-sop | Design prevention, detection, and response measures for high-priority failure modes. Produces actionable countermeasure specifications. |
| re-scoring | Re-evaluate S/O/D scores after mitigation measures are in place. Validates that mitigations actually reduce risk as expected. |
| severity-scoring | Rate failure mode severity 1-10 based on end-effect impact. Follows AIAG-VDA severity scale calibrated for research artifacts. |
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.
- 1mo ago First seen · 69 lines · 31 tokens per session scan A b6593e0ed7db
mitigation-validation is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 551 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
python-code-quality
Code quality checks, linting, formatting, and type checking commands for the Agent Framework Python codebase. Use this when running checks, fixing lint errors, or troubleshooting CI failures.
backtest-diagnose
Diagnose failed or underperforming backtests, locate the root cause, and fix the issue.
oma-observability
Design or troubleshoot telemetry, SLOs, and incident diagnostics. Route to the relevant signal, system boundary, or vendor guide.
node-inspect-debugger
Debug Node.js via --inspect + Chrome DevTools Protocol CLI.
oma-debug
Diagnose a reproducible failure, fix its cause, and verify the regression. Use for crashes, incorrect behavior, and failing tests.
aiwg-doctor
Run a comprehensive health check on the AIWG installation and workspace with pass/fail diagnostics and remediation steps.