hmem-search
hmem-search is a Memory stores & recall skill for AI agents, published by Bumblebiber in the hmem repository on GitHub. Skillspace rates hmem-search D (65/100) and it passed the safety scan; the rating is based on static analysis only.
Search hmem memory for things referenced without an ID. Trigger when user refers to past conversations ("letzte Woche", "gestern", "remember when", "we talked about"), mentions proper names unknown this session, uses definite articles assuming shared context ("der Bug mit X", "the issue we had"), or seems to assume you know something. If you think "the user assumes I know this" — search first, ask second. Combines full-text search with time window from phrasing. Trigger on casual/vague references. Do NOT trigger for explicit ID lookups like "read P0048".
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 20
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 95 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.