Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
Recall
v1.0.0Load context from past sessions. Three modes: temporal (what did I work on yesterday/last week), topic (semantic search across sessions and notes), and graph...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
high confidencePurpose & Capability
The name/description (recall past sessions) aligns with instructions to read memory/*.md, memory/chat-log-*.jsonl, SESSION-STATE.md and synthesize a timeline. Reading those files is appropriate for the stated purpose. However, the SKILL.md references generating an HTML graph via python3 ${CLAUDE_SKILL_DIR}/scripts/generate-graph.py even though this is an instruction-only skill with no code files — that is an incoherence (the graph functionality as documented cannot run from this package as provided).
Instruction Scope
Runtime steps explicitly instruct the agent to run shell commands (ls, cat, grep) over workspace paths and to read 'any notes in the workspace' and SESSION-STATE.md. That general file-reading scope is expected for a recall skill, but it also means the agent will read arbitrary workspace files (which may contain secrets). The SKILL.md uses ambiguous path patterns (ls ~/[workspace]/memory/...) and an environment-like variable ${CLAUDE_SKILL_DIR} — these are underspecified and could lead to the agent searching unexpected locations. The graph step points to a script path that does not exist in the package, so the instruction set assumes external code that isn't provided.
Install Mechanism
There is no install spec and no code files, so nothing is written to disk by the skill itself. This is low install risk. The README mentions an optional third-party tool (@qmd/cli) that a user may install; installing that would introduce external code but is optional and documented.
Credentials
The skill declares no required environment variables, binaries, or credentials, which is proportional to its stated task. One minor inconsistency: instructions reference ${CLAUDE_SKILL_DIR} (an environment-like variable) but it is not declared or required — the agent may assume it exists in runtime, which is not guaranteed.
Persistence & Privilege
The skill does not request permanent presence (always:false) and is user-invocable. It does instruct the agent to read and write files in the user's workspace (e.g., outputting memory/recall-graph-YYYY-MM-DD.html), which is normal for this kind of skill but worth noting because it modifies workspace contents.
What to consider before installing
This skill appears to do what it claims (scan your workspace memory files and synthesize a timeline), but there are a few red flags you should consider before installing or enabling it:
- Missing graph script: The SKILL.md calls python3 ${CLAUDE_SKILL_DIR}/scripts/generate-graph.py to build the visualization, but the package contains no scripts. If you need the graph feature you must supply that script or confirm where the agent should get it.
- Broad file access: The skill's runtime instructions tell the agent to read memory/, SESSION-STATE.md, and 'any notes in the workspace' with shell commands (cat/grep). That will give the skill access to any files in those paths, which may include secrets or sensitive data. Consider running the skill only in a restricted/isolated workspace or reviewing files you keep under memory/ first.
- Ambiguous paths and variables: The use of ~/[workspace], ${CLAUDE_SKILL_DIR}, and other underspecified locations could cause the agent to search unexpected directories. Confirm how your agent resolves those variables or edit the SKILL.md to use explicit, safe paths.
- Optional dependencies: The doc suggests installing @qmd/cli for semantic search — installing global npm packages runs third-party code. Only install such tools from trusted sources.
Recommendations:
1) Ask the skill author (or the publisher) for the missing graph script or remove/disable graph-related instructions.
2) Test the skill in a disposable or sanitized workspace (no secrets) first to observe exactly what files it reads/writes.
3) If you do not want automatic scanning of your entire workspace, avoid giving the agent autonomous invocation or restrict the skill's use to manual, user-invoked runs.
4) Consider adding an explicit allowlist of memory/ file paths in the SKILL.md before enabling it in a production workspace.
Given the clear mismatch (documented functionality that depends on non-existent code and underspecified path handling), treat this package with caution until those inconsistencies are resolved.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
