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Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Reflect

cursor/plugins
149 installs2.1k stars

Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.

Install to Claude Code

npx -y skills add cursor/plugins --skill reflect --agent claude-code

Installs into .claude/skills of the current project.

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On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
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AppSignal
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CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
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Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
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Files
SKILL.mdView on GitHub

Reflect

Mine the current conversation for durable learnings, then route them into skill edits.

When to invoke

  • The user said "reflect" or "/reflect".
  • A complex task (5+ tool calls) just landed cleanly and the recipe is worth keeping.
  • The agent hit dead ends, found the working path, and the path generalizes.
  • The user corrected the agent's approach mid-task.
  • A non-trivial workflow emerged that isn't captured anywhere.

Skip when the conversation is trivial, off-topic, or already covered by an existing skill the parent followed correctly. One-offs are not learnings.

Process

1. Locate the active transcript

The parent finds its own transcript file before fanning out. The system prompt names the active workspace's agent-transcripts/ directory; use that path. Do not glob across ~/.cursor/projects/*/. That crosses workspace boundaries and reads private chats from unrelated projects.

ls -t <agent-transcripts>/*.jsonl <agent-transcripts>/*/*.jsonl <agent-transcripts>/*/subagents/*.jsonl 2>/dev/null | head -10

Three transcript layouts: legacy flat (<id>.jsonl), current nested (<id>/<id>.jsonl), and subagent (<parent>/subagents/<child>.jsonl).

For each candidate, read the first JSONL line and check that message.content[0].text contains the conversation's opening user prompt. Take the matching path. If no path resolves, write a tight digest of the session and pass that instead.

2. Spawn three reviewers in parallel

One message, three Task calls, subagent_type: generalPurpose, explicit model: on each, agent mode (readonly: false). Reviewers need MCP access for context lookups (tickets, chat threads, observability traces referenced in the transcript); readonly strips MCPs. The prompt forbids file writes; the parent applies edits.

LensmodelPrompt template
Judgmentyour configured reflect-judgment model (default claude-opus-4-8-thinking-xhigh)references/judgment-reviewer.md
Toolingyour configured reflect-tooling model (default composer-2.5-fast)references/tooling-reviewer.md
Divergentyour configured reflect-judgment model (default claude-opus-4-8-thinking-xhigh)references/divergent-reviewer.md

Pass each template verbatim, substituting the transcript path or digest where marked. Reviewers return findings in the Task response body.

3. Synthesize

One Task call, subagent_type: generalPurpose, using your configured reflect-judgment model (default claude-opus-4-8-thinking-xhigh), agent mode (readonly: false). The synthesizer's quality check includes spot-verifying citations, which can require MCP access; readonly strips MCPs. Use references/synthesizer.md verbatim, with each reviewer's full output inlined where marked. The synthesizer returns a structured Accepted / Rejected / Backlog list.

4. Structural enforcement check

Sanity-check the synthesizer's Accepted list. For any item that would be enforced more reliably by a lint rule, script, metadata flag, or runtime check, move it from Accepted to Backlog. The synthesizer already applies this criterion; this is a final pass before edits land. See the encode-lessons-in-structure principle skill.

5. Apply

Before applying any Accepted edit, present the synthesizer's full Accepted/Rejected/Backlog output to the user and wait for explicit approval. The user picks which subset to apply and may redirect routings. Skill changes affect every future agent in the org; do not auto-apply.

Backlog items file to whatever devex / backlog tracker your team uses automatically. Those are tracker submissions, not skill edits. Only the Accepted list waits for approval.

For each approved Accepted item, follow the Routing field exactly:

  • Trivial existing-skill edit (a one-line bullet, a tightened sentence, a stale fact corrected): parent does directly.
  • Substantive existing-skill edit (a new section, a new pattern table, more than ~10 lines): hand to Cursor's built-in create-skill skill and run its draft / test / iterate loop.
  • tune description: <skill path> (the skill exists but didn't trigger when it should have): hand to create-skill and run its description-optimization loop.
  • new skill via create-skill: <kebab-name>: hand creation to create-skill. Do not invent the shape ad hoc.

If your environment ships a SKILL.md validator, run it on every touched skill before declaring done. Skip this step if it doesn't.

6. Summarize for the user

Short list, no preamble:

  • Edits applied: <skill path>. What changed, one line each.
  • New skills created: <skill path>. One line each (rare).
  • Backlog filed to the devex tracker: <issue title> (<tags>). One line each.
  • Dropped: one line per rejected finding + reason from the synthesizer.
Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
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Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
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Categories
Git & Pull RequestsCode Review & QualityAutomation & Workflows
First SeenJun 23, 2026
View on GitHub

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