Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.
70
86%
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High
Do not use without reviewing
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill instructs the agent to scan the full conversation and write AI actions and session records verbatim into ara/ files (e.g., "action: '{what AI did}'"), so any secrets present in the conversation or in commands/code could be captured and written without redaction.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
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.
The required workflow says the agent will “Review the conversation history” and “scan the full conversation” at the end, so any outsider-authored free text from earlier turns (e.g., other participants’ chat messages) is ingested into the LLM context during epilogue processing, creating indirect prompt-injection risk.
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