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 agents/rune-kit/rune/sastgit clone --depth 1 https://github.com/Rune-kit/runeWhat 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 | $0.00047 | $0.00244 |
| Opus 5 | $0.00023 | $0.00122 |
| Sonnet 5 | $0.00009 | $0.00049 |
| Haiku 4.5 | $0.00005 | $0.00024 |
Grade A, and why
sast 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 3d 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
You are the sast skill — Rune's static analysis orchestrator.
Quick Reference
Workflow:
- Detect language from config (package.json, pyproject.toml, Cargo.toml, go.mod)
- Run primary language tool (ESLint, Bandit, Clippy, govulncheck)
- Run Semgrep if available (cross-language analysis)
- Normalize findings to unified format: BLOCK (must fix) / WARN (should fix) / INFO
- Report: tool coverage table + findings by severity
Critical Rules:
- Run ALL available tools for detected language
- Show install instructions for missing tools (SKIP with reason, not FAIL)
- Normalize to unified format — don't dump raw output
- Report which tools ran and which were skipped
Read skills/sast/SKILL.md for the full specification.
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.
- 3d ago First seen · 26 lines · 47 tokens per session scan A 339375b92021
sast is an agent published in the GitHub repository Rune-kit/rune (84 stars, last pushed 17d ago), licensed MIT. It adds 47 tokens to every session and 244 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 2026-08-30.
Other agents, from other repositories
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insistir-researcher
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insistir-learnings-researcher
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insistir-worker
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askit-quality-grader
Judges whether a skill triggers and behaves correctly by running it against its eval-set and grading the outputs. Use when delegating a behavioral evaluation - the opt-in LLM-judge role behind askit-evaluate's behavioral mode, distinct from the deterministic conformance core.