--- 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. Invoke when the user says "reflect" or "/reflect". Skip when the conversation is trivial, off-topic, or already covered by an existing skill the parent followed correctly. One-offs are not learnings. ## 1. Locate the active transcript Before fanning out, find this conversation's transcript in the active workspace's session directory. Do not glob across every project's directory. That crosses workspace boundaries and reads private chats from unrelated projects. Where the transcript lives depends on your harness: - **Cursor:** the `agent-transcripts/` directory the system prompt names. ```bash ls -t /*.jsonl /*/*.jsonl /*/subagents/*.jsonl 2>/dev/null | head -10 ``` That covers the legacy flat (`.jsonl`), current nested (`/.jsonl`), and subagent (`/subagents/.jsonl`) layouts. For each candidate, read the first JSONL line. Take the file whose `message.content[0].text` contains the conversation's opening user prompt. - **Claude Code:** `~/.claude/projects//.jsonl`, where `` is the workspace path with every character that isn't a letter or digit turned into "-". - **Pi:** `~/.pi/agent/sessions/----/*.jsonl`, where `` is the workspace path with the leading slash dropped and each "/" turned into "-". - **Codex:** `~/.codex/sessions/YYYY/MM/DD/rollout-*.jsonl`. Keep only files whose first line has `payload.cwd` equal to the workspace path. - **Other harnesses:** check the harness's session directory for this workspace. Outside Cursor, take the newest candidates first and confirm one by finding the conversation's opening user prompt in its first user message. If none matches, pass a tight digest of the session instead. ## 2. Spawn three reviewers in parallel One message, three `Task` calls, `subagent_type: generalPurpose`, agent mode (`readonly: false`). Reviewers need MCP access to look up the tickets, chat threads, and observability traces the transcript references, and readonly strips MCPs. **Other harnesses.** The spawns in this skill use Cursor's `Task` tool. In another harness, use its subagent tool: `Agent` in Claude Code (`subagent_type: general-purpose`), `task` in OpenCode (`subagent_type: general`), `spawn_agent` in Codex. Keep the prompt and the model. Drop parameters your tool doesn't have. If your harness has no subagent tool, as in Pi without an extension, run each role yourself, one after another. Each reviewer and the synthesizer name a role line in the pstack settings file (`~/.cursor/rules/pstack-models.mdc` in Cursor, `~/.agents/pstack-models.md` in other harnesses) and a default. Set `model` to that line's value, or to the default if the file or the line is missing. Leave `model` unset when the value is `auto` or `inherit-parent`. If your subagent tool rejects a slug, use the default and say so. If it rejects the default, use the closest valid slug of the same family from its error message or your harness's model list. | Lens | Role line | Default `model` | Prompt template | |---|---|---|---| | Judgment | `reflect judgment, divergent, synthesizer` | `claude-opus-5-5-xhigh` | `references/judgment-reviewer.md` | | Tooling | `reflect tooling` | `grok-4.7-xhigh-fast` | `references/tooling-reviewer.md` | | Divergent | `reflect judgment, divergent, synthesizer` | `claude-opus-5-5-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`, `model` from the `reflect judgment, divergent, synthesizer` line (default `claude-opus-5-5-xhigh`), agent mode (`readonly: false`). It spot-verifies citations through MCP, and readonly strips MCPs. Pass `references/synthesizer.md` verbatim, with each reviewer's full output inlined where marked. It returns an Accepted / Rejected / Backlog list. ## 4. Structural enforcement check Move any Accepted item that a lint rule, script, metadata flag, or runtime check would enforce more reliably to Backlog. See the **encode-lessons-in-structure** principle skill. ## 5. Apply Present the synthesizer's full Accepted / Rejected / Backlog output and wait for explicit approval before applying any Accepted edit. The user picks the subset and may redirect routings. Skill changes affect every future agent in the org. Do not auto-apply. File each Backlog item to your team's devex or backlog tracker without waiting. Only the Accepted list waits for approval. Follow each approved row's Routing exactly: - Trivial existing-skill edit (a one-line bullet, a tightened sentence, a stale fact corrected): the parent does it directly. - Substantive existing-skill edit (a new section, a new pattern table, more than ~10 lines): hand to your harness's skill-authoring skill and run its draft / test / iterate loop. That is `create-skill` in Cursor (built in) or Anthropic's `skill-creator`. If you have neither, follow the Agent Skills format at agentskills.io. "`create-skill`" below means whichever of these you use. - `tune description: ` (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: `: 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. ## 6. Summarize for the user Short list, no preamble: - Edits applied: ``. What changed, one line each. - New skills created: ``. One line each (rare). - Backlog filed to the devex tracker: `` (``). One line each. - Dropped: one line per rejected finding + reason from the synthesizer.