memory-mining

memory-mining is a Memory stores & recall skill for AI agents, published by neomjs in the neo repository on GitHub. Skillspace rates memory-mining C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Authoritative protocol for querying the Memory Core before diagnosing regressions or proposing non-trivial architectural claims. Prevents re-derivation of prior reasoning by surfacing cross-session, cross-harness context via semantic search. Triggers: Use this skill when (1) the user reports a regression symptom ("used to work", "suddenly broken", surprise validation failures, schema mismatches, "additionalProperties" rejections), OR (2) you are about to propose an architectural claim, roadmap, or comparison against external work where prior sessions may have already mapped the territory, OR (3) you are about to begin an implementation or a PR-review — a cheap 3–10-call prior-art sweep before the first design sentence or review verdict.

Grade

C

Quality

74 / 100

Safety

Passed

GitHub stars

3,234

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it looks written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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