Memory System Sidecar
v1.0.0Operate, verify, rebuild, and debug the implemented MemoryLab long-term memory sidecar feeding active task and live context files.
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bysjinopenclaw@sjingh
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The skill is declared as an instruction-only operator for the repo's memory sidecar and all actions map to local repo operations (refresh, verify, rebuild). Small mismatch: the runtime commands invoke python3 and repo wrapper scripts but the registry metadata lists no required binaries; this is a minor documentation gap (python3 is implicitly required).
Instruction Scope
SKILL.md directs the agent to run three repository wrapper scripts and to inspect files under memory/, memory-system/, history/, and related docs. The instructions do not ask the agent to read or exfiltrate unrelated system files or environment variables and they point only to project-local artifacts.
Install Mechanism
There is no install spec (instruction-only) and the included shell scripts are small wrappers around repo-local Python tools. No downloads, external package installs, or archive extraction are present.
Credentials
The skill declares no required env vars, secrets, or config paths and the instructions do not reference credentials. This is proportional to the stated purpose. Note that runtime code (tests/eval/build_index) could itself access environment variables — review those files if you need to ensure no secrets are used.
Persistence & Privilege
always is false and the skill does not request modifications to other skills or system-wide config. It runs only when invoked and does not request permanent presence or elevated platform privileges.
Assessment
This skill appears coherent and limited to running repository-local refresh/verify/rebuild workflows. Before running it: (1) ensure you trust the repository code because the scripts invoke python3 unit tests and eval scripts which can execute arbitrary Python in the repo; (2) confirm python3 is available (registry metadata omitted this requirement); (3) inspect the referenced Python files (memory-system/ingest/build_index.py, memory-system/eval/run_eval.py, and the test modules) if you will run this in an environment with sensitive data or credentials — those files could make network calls or read env vars even though the skill doesn't request secrets. If you want tighter safety, run the scripts in an isolated environment (container/VM) or review the code prior to execution.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.