hierarchical-implicit-intent-memory
hierarchical-implicit-intent-memory is a Memory stores & recall skill for AI agents, published by iLearn-Lab in the ACL26-PersonalAlign repository on GitHub. Skillspace rates hierarchical-implicit-intent-memory C (70/100) and it passed the safety scan; the rating is based on static analysis only.
Designs long-term user-centric memory for any agent using hierarchical implicit intent alignment (preference and routine), streaming updates, and dual filters (execution-like vs state-like). Use when building personalized agents, memory layers, user modeling, or adapting PersonalAlign/HIM-style ideas beyond GUI.
- Grade
- C
- Quality
- 70 / 100
- Safety
- Passed
- GitHub stars
- 21
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
- 81 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- 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
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