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.
git clone --depth 1 https://github.com/stackhawk/agent-skillsWrote 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/rules/stackhawk/agent-skills/stackhawk-optimize-metrics)<a href="https://agentmods.dev/rules/stackhawk/agent-skills/stackhawk-optimize-metrics"><img src="https://agentmods.dev/badge/rules/stackhawk/agent-skills/stackhawk-optimize-metrics/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/rules/stackhawk/agent-skills/stackhawk-optimize-metrics"><img src="https://agentmods.dev/badge/rules/stackhawk/agent-skills/stackhawk-optimize-metrics.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 | $0.00074 | $0.01154 |
| Opus 5.5 | $0.00030 | $0.00462 |
| Sonnet 5.5 | $0.00015 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00115 |
Grade A, and why
stackhawk-optimize-metrics 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scan Metrics → Refine Loop
After the trial scan, analyze its metrics and refine the config using real scan data.
This skill does NOT compute metrics — it consumes hawk op scan metrics.
Get the metrics
hawk op scan metrics <SCAN_ID> --format json
<SCAN_ID> is the trial scan's id (use the id returned by the trial scan; latest also works).
Output (MetricsJson):
{
"scan_id": "...",
"request_health": { "timeout": 0, "connection_failure": 0, "timeout_streak_max": 0 },
"scan_flags": ["timeout-prone"],
"paths": [
{
"method": "GET", "path": "/x", "total_requests": 100,
"status_counts": {"200": 90, "429": 10},
"class_2xx": 90, "class_3xx": 0, "class_4xx": 10, "class_5xx": 0,
"error_rate": 0.10,
"time": {"p50_bucket": 256, "p90_bucket": 4096, "max_bucket": 8192, "est_total_ms": 30000},
"flags": ["slow-path", "rate-limited"]
}
],
"operations": []
}
Useful read-only views (human framing): --sort {heaviest|slowest|erroring|most-requested},
--top N, --method <VERB>, --operations.
Flag → lever mapping
| Flag | Meaning | Lever | Tier | Goal |
|---|---|---|---|---|
rate-limited |
429s from target | lower hawk.scan.concurrentRequests |
auto | better+faster |
timeout-prone |
target overwhelmed/flaky (scan-level) | lower hawk.scan.concurrentRequests |
auto | reliability |
heavy-path |
path dominates est. scan time | app.excludePaths (or narrow includePaths) |
confirm | faster |
slow-path |
high p90 latency | app.excludePaths if low security value |
confirm | faster |
auth-wall |
>=50% 401/403 — route not actually tested | guide app.authentication.* (never fabricate creds) |
confirm / needs-input | better coverage |
server-erroring / error-prone |
app erroring under scan | surface for investigation; optionally app.excludePaths |
advisory / confirm | better findings |
Tiers
- auto = concurrency reductions ONLY (non-destructive, reversible, no coverage loss). Apply, then re-scan.
- confirm = anything that drops coverage (
app.excludePaths) or needs human input (app.authentication.*). Show the exact yml diff; apply only on explicit approval.
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 · 97 lines · 74 tokens per session scan A 75d7e1f7e9ee
stackhawk-optimize-metrics is a cursor rule published in the GitHub repository stackhawk/agent-skills (16 stars, last pushed 8d ago), licensed MIT. It adds 74 tokens to every session and 1,154 once invoked, about $0.0003 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 2026-08-30.
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