/reflect

name: reflect
description: Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.
disable-model-invocation: true

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.

| Lens | `model` | Prompt template | |---|---|---| | Judgment | your configured reflect-judgment model (default `claude-fable-5-thinking-max`) | `references/judgment-reviewer.md` | | Tooling | your configured reflect-tooling model (default `gpt-5.6-sol-max`) | `references/tooling-reviewer.md` | | Divergent | your configured reflect-judgment model (default `claude-fable-5-thinking-max`) | `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-fable-5-thinking-max`), 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.