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 agentmods add skills/stackhawk/agent-skills/stackhawk-data-seednpx skills add stackhawk/agent-skills --skill stackhawk-data-seedgit clone --depth 1 https://github.com/stackhawk/agent-skillsWhat 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 | $0.00159 | $0.02427 |
| Opus 5 | $0.00079 | $0.01213 |
| Sonnet 5 | $0.00032 | $0.00485 |
| Haiku 4.5 | $0.00016 | $0.00243 |
Grade A, and why
stackhawk-data-seed 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 2d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
StackHawk Data Seed Skill
This skill produces checked-in, reproducible seed-data artifacts for a target repo so authenticated HawkScan finds non-empty results. The hawk perch seed command provides the deterministic steps — a static repo pre-flight (storage + upstream detection), a manifest validator, and an artifact finalizer. This skill supplies the reasoning between them: it reads the pre-flight's digest and designs the minimum seed manifest. It works the same across every agent that can run a subprocess and read its output.
It does NOT run the artifacts, start the environment, or write stackhawk.yml — those belong to the human, the user's tooling, and the hawkscan skill respectively.
When to Run
Invoke explicitly when:
- User says "set up data for HawkScan" / "seed this repo" / "my scan has no data to hit."
- Configuring HawkScan against a repo for the first time and the app needs authenticated routes to scan.
- A previous
data-seed/exists but the data shape changed (new entity types, new upstream service).
Do NOT run autonomously after code changes — this is a setup tool, not a per-commit safety net.
Phase 0: Preflight
0.1 — Confirm working directory
The user must invoke from inside the target repo (the repo HawkScan will scan):
test -d .git || echo "NOT-A-REPO"
pwd
If not a git repo, ask the user to cd to the target repo and re-invoke.
0.2 — Confirm hawk supports the seed flow (capability gate)
This skill drives the caller-driven hawk perch seed subcommands (validate and finalize). Probe for them directly:
# Identify the driving skill for CLI usage telemetry (read by hawk/hawkop).
export _STACKHAWK_SKILL=stackhawk-data-seed
if hawk perch seed validate --help >/dev/null 2>&1 && hawk perch seed finalize --help >/dev/null 2>&1; then
echo "SEED-FLOW-OK"
else
echo "SEED-FLOW-UNSUPPORTED"
fi
hawk version 2>/dev/null || hawk --version 2>/dev/null # for the message only; never gates
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.
- 2d ago First seen · 189 lines · 159 tokens per session scan A e782413abcd8
stackhawk-data-seed is a skill published in the GitHub repository stackhawk/agent-skills (15 stars, last pushed 12d ago), licensed MIT. It adds 159 tokens to every session and 2,427 once invoked, about $0.0008 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 2026-08-30.
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