Catalog
Yeachan-Heo/reflect

After a long task, a three-reviewer panel audits the session transcript — tooling, judgment, missed alternatives — and proposes concrete skill edits. Findings feed skillify. For banking marathon-session lessons.

v1.0LATEST
NewUpdated Nov 8, 2026

Reflect

Long sessions teach things nobody writes down. This skill audits the session transcript with independent reviewers and converts the findings into proposed edits to OMC's own skills — before the lessons evaporate.

When to use

  • a marathon session just ended (or is ending) and went well or badly in ways worth banking
  • the user asks "what did we learn", "bank this session", or says reflect

When not to use

  • routine sessions with nothing anomalous — reflection on nothing is noise
  • the user wants a summary of what happened — ketchup does that

Workflow

  1. Locate the transcript for this session and hand each reviewer the path, not a paste — reviewers read it themselves.
  2. Seat the panel: three read-only reviewers in one message, in the background, each with one lens:
    • tooling reviewer — which commands, skills, and agents helped or wasted time; what a script or skill should have existed
    • judgment reviewer — where calls were wrong, late, or unverifiable; which principle would have caught it
    • divergent reviewer — the alternative approaches never tried; what a fresh agent would have done differently Each returns at most three findings, each with transcript citations. Wait for every reviewer to reach a terminal state and collect its output before Step 3 — background dispatch returns before the reviewers finish, and synthesizing on a partial panel proposes misleading skill edits. A reviewer that times out is named as missing, not silently dropped.
  3. Synthesize: merge duplicates, drop unevidenced claims, rank by how often the lesson would recur. A lesson that applies once is a note; one that applies every session is a skill edit.
  4. Propose skill edits: for each surviving recurring lesson, the concrete edit — which skill file, which section, what wording — or a proposal for a new skill via skillify. Human-ruling wording stays verbatim (why skill epistemics).
  5. Report the findings and the proposed edits; apply an edit only with the user's go — reflection proposes, the user disposes.

Rules

  • Reviewers cite the transcript; a finding without a citation is dropped.
  • The panel never edits skills itself — proposals go to the user and then to skillify for execution.
  • Never edit a skill inside the installed plugin cache. Before the user approves an edit, show its destination — the repo's skills/<name>/ for a shipped skill, or the user's .claude/skills/<name>/ copy — and after approval edit that destination in place. Reflection never opens a PR or pushes.
  • Findings about the user's own choices are reported as observations, not corrections.
Files2
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Overall Score

78/100

Grade

B

Good

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

82

Quality

78

Clarity

79

Completeness

72

Summary

Reflect is a skill for auditing long-running agent sessions through a three-reviewer panel that examines tooling choices, judgment calls, and alternative approaches, then proposes concrete edits to skills based on recurring lessons. The skill guides the agent to seat reviewers, synthesize findings with citations, and report skill proposals to the user for approval rather than self-executing edits.

Detected Capabilities

transcript analysismulti-agent coordinationstructured panel reviewskill proposal generationfile path referenceuser approval gatingskill edit workflow coordination

Trigger Keywords

Phrases that agents use to match this skill to user intent.

bank session lessonsmarathon session auditskill proposalsession retrospectivetooling review panelreflect on session

Risk Signals

INFO

References github.com URLs in metadata and port credits

metadata.url, metadata.port-url
INFO

Skill proposes edits to user's local .claude/skills/ directory and shipped skill repos

Step 4, Rules section
INFO

No file write, deletion, or shell execution in the skill itself—delegation is gated by user approval

Rules section

Referenced Domains

External domains referenced in skill content, detected by static analysis.

github.com

Use Cases

  • Bank lessons from marathon debugging sessions
  • Identify missing or misused skills after complex workflows
  • Catch judgment failures and unverified decisions in agent reasoning
  • Discover simpler alternative approaches to problems solved inefficiently
  • Propose recurring skill improvements based on pattern analysis
  • Convert session transcripts into actionable skill enhancements

Quality Notes

  • Clear workflow with five numbered steps and explicit synchronization points (wait for every reviewer before synthesis)
  • Well-defined reviewer lenses in supporting file with concrete criteria and output format
  • Strong guardrail: skill never executes edits itself—all proposals go to user first
  • Explicit rule against editing skills in plugin cache; destinations shown before approval
  • Findings without citations are explicitly dropped, reducing noise
  • Supporting file provides structured output format for reviewer findings with EVIDENCE, RECURRENCE, and PROPOSED-EDIT fields
  • No error handling guidance for reviewer timeouts beyond naming the missing reviewer
  • Scope is clear (post-session reflection) but triggering conditions are somewhat subjective ('went well or badly in ways worth banking')
Model: claude-haiku-4-5-20251001Analyzed: Nov 8, 2026

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