Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
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77%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
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Advisory
Suggest reviewing before use
Fix and improve this skill with Tessl
tessl review fix ./skills/skill-comply/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Third-party content exposure detected (medium risk: 0.65). Outsider free text can enter the LLM context via the runtime-generated `tool_calls` string in `scripts/classifier.py`, which is built from `ObservationEvent.input`/`output` parsed from `claude -p` stream-json (i.e., tool call contents produced by the executed agent session, not authored by the operating user); this `tool_calls` is then interpolated into `prompts/classifier.md` and sent to `claude -p` for classification.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.