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v2.0.0

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@eddieran eddieran released this 26 Feb 11:03
· 42 commits to main since this release

Procedural Memory — Skills That Adapt to You

skillpm v2.0.0 introduces a cognitive memory subsystem that makes skill management self-adaptive. Skills strengthen with use, decay with disuse, and adapt to your project context — so agents always see the most relevant skills.

Highlights

  • 6-layer architecture: observation → context → scoring → feedback → consolidation → adaptive injection
  • 4-factor activation scoring: Score = 0.35×Recency + 0.25×Frequency + 0.25×ContextMatch + 0.15×Feedback
  • Context-aware: auto-detects project type (Go, Node, Python, Rust, Java, Ruby), frameworks, and task signals
  • Adaptive injection: skillpm inject --adaptive injects only the working-memory subset
  • 14 new CLI commands under skillpm memory
  • Zero new dependencies — built on stdlib + existing go-toml/v2
  • CPU < 5% overhead — benchmarked with regression detection

New Commands

skillpm memory enable/disable        # toggle the subsystem
skillpm memory observe               # record skill usage events
skillpm memory scores                # show activation scores
skillpm memory working-set           # skills in working memory
skillpm memory explain <skill>       # detailed score breakdown
skillpm memory rate <skill> +1/0/-1  # explicit feedback
skillpm memory consolidate           # recompute & promote/demote
skillpm memory recommend             # archival suggestions
skillpm memory set-adaptive on/off   # default adaptive mode
skillpm inject --agent claude --adaptive  # smart injection

Quick Start

skillpm memory enable
skillpm memory observe
skillpm memory scores
skillpm inject --agent claude --adaptive

Stats

  • 7 new internal packages (internal/memory/*)
  • +5,400 lines of Go code
  • ~131 unit tests across all memory packages (>80% coverage)
  • 4 E2E test functions
  • Benchmark suite with CI regression detection

Docs

Full Changelog

https://github.com/eddieran/skillpm/blob/main/CHANGELOG.md