Agent Memory Ops
v0.1.1Audit and maintain OpenClaw-style long-term memory. Use for MEMORY.md cleanup, daily-note digestion, duplicate detection, stale-memory review, and promoting...
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by@orime
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match what is present: SKILL.md and scripts/memory_ops.py implement scanning MEMORY.md and memory/*.md, deduping, digesting, and reporting. No unrelated binaries, credentials, or config paths are requested.
Instruction Scope
Instructions correctly tell the agent to run the included Python script from the workspace root. The script reads MEMORY.md and files under memory/*.md and prints markdown/JSON reports including extracted bullet text. This is within scope, but note that the tool reads and outputs content from local files (which may contain sensitive data). The script contains heuristics to filter likely secrets but uses pattern matching (heuristic), so it may miss some secrets or redact too little — review outputs before promoting content.
Install Mechanism
No install spec is provided (instruction-only skill) and the repository includes a Python script to run. Nothing is downloaded or written to disk by an installer; running the script executes only local code.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. The script likewise does not read environment variables or external credentials. Requested access is proportional to the stated task (reading local memory files).
Persistence & Privilege
always:false and default autonomous-invocation are set (normal). The skill does not request permanent system-wide privileges or modify other skills' configs per the provided files.
Assessment
This skill appears coherent and implements the advertised memory-audit functionality, but take these precautions before running it: 1) Inspect the full scripts/memory_ops.py file yourself (the prompt included a truncated view) to confirm there are no hidden network calls or surprising behavior. 2) Run the script locally in a safe/dev environment first — it reads and prints items from MEMORY.md and memory/*.md, so outputs could expose sensitive content. 3) Don't run it against repos containing live secrets; the secret-detection is heuristic and can miss things. 4) Back up MEMORY.md before applying any automated changes and manually review suggestions before promoting items into curated memory.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.