thrunt-review — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited thrunt-review (Agent Skill) and scored it 45/100 (orange). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 4 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 4 flagged
A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<objective> Invoke external AI CLIs (Gemini, the agent, Codex) to independently review phase plans. Produces a structured REVIEWS.md with per-reviewer feedback that can be fed back into planning via /hunt-plan --reviews.
Flow: Detect CLIs → Build review prompt → Invoke each CLI → Collect responses → Write REVIEWS.md </objective>
<execution_context> @.github/thrunt-god/workflows/review.md </execution_context>
<context> Phase number: extracted from $ARGUMENTS (required)
Flags:
--gemini — Include Gemini CLI review--claude — Include the agent CLI review (uses separate session)--codex — Include Codex CLI review--all — Include all available CLIs</context>
<process> Execute the review workflow from @.github/thrunt-god/workflows/review.md end-to-end. </process>
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.