Agent Skills: Kaizen Improvement

Transform transcript analysis findings into actionable improvements. Triggers on "generate hooks from findings", "improve agent", "fix anti-pattern", "kaizen improvement", "generate hook proposals", or "create improvement plan". Provides templates for hook generation, agent prompt refinement, skill patches, CLAUDE.md updates, and script automation from analysis data.

UncategorizedID: Jamie-BitFlight/claude_skills/kaizen-improvement

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pnpm dlx add-skill https://github.com/Jamie-BitFlight/claude_skills/tree/HEAD/plugins/agentskill-kaizen/skills/kaizen-improvement

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plugins/agentskill-kaizen/skills/kaizen-improvement/SKILL.md

Skill Metadata

Name
kaizen-improvement
Description
Transform transcript analysis findings into actionable improvements. Triggers on "generate hooks from findings", "improve agent", "fix anti-pattern", "kaizen improvement", "generate hook proposals", or "create improvement plan". Provides templates for hook generation, agent prompt refinement, skill patches, CLAUDE.md updates, and script automation from analysis data.

Kaizen Improvement

Transform analysis findings from .planning/kaizen/ into actionable improvements — hooks, agent patches, skill refinements, CLAUDE.md updates, and automation scripts.

Prerequisite: Analysis findings must exist in .planning/kaizen/ (generated by the transcript-analysis skill).

Improvement Types

Five categories of output, each with a delegation template:

  1. Hook generation — PreToolUse deny/redirect, SubagentStart context injection, Stop quality gates
  2. Agent prompt refinement — surgical fixes to agent system prompts via @subagent-refactorer
  3. Skill patches — add missing knowledge to skills via /plugin-creator:skill-creator
  4. CLAUDE.md updates — project-wide behavioral rules
  5. Script automation — replace repeated manual workflows with scripts or skills

For detailed templates and examples, see Improvement Templates.

For the Autonomous Refinement Loop (ARL) knowledge base — Layer 3 implementation details, prerequisites, and research synthesis — see ARL Knowledge.

Workflow

flowchart TD
    Start([Read analysis findings]) --> Parse[Extract anti-patterns with frequency and evidence]
    Parse --> Score[Score by frequency × impact]
    Score --> Top[Select top findings]
    Top --> Type{Improvement type?}
    Type -->|Repeated tool misuse| Hook[Generate hook — deny/redirect]
    Type -->|Agent behavior issue| Agent[Generate agent patch instruction set]
    Type -->|Knowledge gap| Skill[Generate skill patch instruction set]
    Type -->|Project-wide issue| Claude[Generate CLAUDE.md addition]
    Type -->|Manual workflow| Script[Generate automation proposal]
    Hook --> Output[Write to .planning/kaizen/improvements/]
    Agent --> Output
    Skill --> Output
    Claude --> Output
    Script --> Output
    Output --> Install{--install flag?}
    Install -->|Yes| Apply[Write hooks to settings, apply patches]
    Install -->|No| Draft[Leave as proposals for review]

Hook Generation

Read findings → generate hook configuration + optional script. For patterns mapped to each anti-pattern type, guidelines, and examples, see Hook Patterns.

Delegation Protocol

Improvements are instruction sets for specialist agents, not direct edits. Follow outcome-focused delegation:

  • Describe the problem with evidence (session IDs, tool calls, frequency)
  • State the desired outcome
  • Let the specialist agent determine the implementation approach
  • Never prescribe specific code changes in the delegation prompt

Output Modes

Draft mode (default)

Write all proposals to .planning/kaizen/improvements/ as markdown files. Each file contains:

  • Finding summary with evidence
  • Proposed improvement
  • Delegation prompt for the appropriate specialist agent
  • Priority score

Install mode (--install flag)

For hooks only — write directly to .claude/settings.json or hooks/hooks.json. Other improvement types always produce delegation prompts (never direct edits).

Priority Scoring

Rank improvements by:

  1. Frequency × Impact — occurrences across sessions × cost per occurrence
  2. Automation potential — hooks > scripts > documentation
  3. Blast radius — project-wide > single-agent > single-session
  4. Implementation cost — hook (minutes) < CLAUDE.md (minutes) < skill (hours) < agent (days)