reflect
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
Skill by jiangkoumo
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/jiangkoumo-reflect
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: writing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions: not checked yet.
What's inside
- Skill 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.
- License
- MIT
- Instructions
- 79 lines in SKILL.md · view on GitHub
Files (5)
- SKILL.md
- divergent-reviewer.md · references/
- judgment-reviewer.md · references/
- synthesizer.md · references/
- tooling-reviewer.md · references/
SKILL.md (first lines)
# 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 Pi session path the system prompt names. Do not glob across unrelated project sessions or `~/.cursor/projects/*/`. That crosses workspace boundaries and reads private chats from unrelated projects.
Read the active session file with `read`. When the host stores JSONL sessions in that shape, that covers the legacy flat (`<id>.jsonl`), current nested (`<id>/<id>.jsonl`), and subagent (`<parent>/subagents/<child>.jsonl`) layouts. For each candidate, read the first JSONL line. Take the file whose first entry contains the conversation's opening user prompt. If none matches, pass a tight digest of the session instead.
## 2. Spawn three reviewers in parallel
One message, three `subagent` calls in one parallel workflow, agent mode (`readonly: true`), one registered pstack agent each. Reviewers need MCP access to look up the tickets, chat threads, and observability traces the transcript references, and readonly strips MCPs, so the lead passes that evidence inline when those tools are unavailable.
Each reviewer and the synthesizer name a role line in `/setup-pstack` and a default. Set `model` to that line's value, or to the default if the rule or the line is missing. Leave `model` unset when the value is `inherit`, so that seat runs on the parent model. If the host rejects a configured model slug, use the default and say so. If it rejects the default, use the closest valid configured model slug of the same family from its error message. Never treat an alias entry as a rejected model or apply either fallback to it. Pick each subagent's thinking for the job, per the Subagents section of the **poteto-mode** skill.
| Lens | Role line | Prompt template |
|---|---|---|
| Judgment | `judgment` | [judgment-reviewer.md](references/judgment-reviewer.md) |
| Tooling | `verification` | [tooling-reviewer.md](references/tooling-reviewer.md) |
| Divergent | `strongest` | [divergent-reviewer.md](references/divergent-reviewer.md) |
Pass each template verbatim, substituting the transcript path or digest where marked. Reviewers return findings in the `subagent` response body.
## 3. Synthesize
One `subagent` call, `subagent_type` read-only, `model` from the `judgment` role line, agent mode (`readonly: true`). It spot-verifies citations through MCP where available, and readonly strips MCPs. Pass [synthesizer.md](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.
Never edit skills directly in a package installation directory or cache. Before requesting approval, show the persistent destination for each skill: project-local `.pi/skills/<skill>/` or global `~/.pi/agent/skills/<skill>/`. Include that destination in the proposed edit so the user approves both the content and its location. After approval, copy the installed skill's entire directory to the approved destination and edit that copy. If the skill already lives at the approved persistent destination, edit it there after approval. When maintaining a source repository with generated skills, edit its source template and regenerate instead of editing its generated Markdown. Never automatically open a PR, push, or submit changes to a remote repository.
Pi keeps the first discovered skill when names collide. After copying, run `/reload` and verify that the resolved `/skill:<name>` path is the approved copy; do not assume a project path overrides a package or user skill. Report a collision before claiming the edit is active. Propose either disabling the competing resource through the host's resource settings or using a distinct skill name and updating its local references, and obtain approval for that change. Check the copy's relative references as well: copying its directory does not bring along dependencies outside that directory. Keep the original installed skill untouched.
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 the Pi authoring-a-skill playbook and run its draft / test / iterate loop.
- `tune description: <skill path>` (the skill exists but didn't trigger when it should have): hand to the Pi authoring-a-skill playbook and run its description-optimization loop.
- `new skill via create-skill: <kebab-name>`: hand creation to the Pi authoring-a-skill playbook. 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: `<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.
## Pi adaptation
Adapted from Lauren Tan’s pstack v0.15.25, MIT, fixed revision f713f14203cd6420cec13cd7c55c32d598dbab68. Read the [Pi adapter](../../adapters/pi/harness.md) for host mappings.
Delegation requires current operator or applicable project authorization and a compatible pi-subagents integration. If unavailable or unauthorized, perform authorized stages locally, disclose self-review and missing independence, and report any required independent stage as open. Use only registered pstack.* agents. Models and thinking bind through /setup-pstack roles and user agentOverrides; never put model in a task item or on the outer subagent call. Report unavailable or identical configured models; do not silently substitute. Await native completion notices and collect every required result before synthesis.
Use read for file contents, grep/find/ls for search and directories, and ffgrep/fffind when available. Batch independent reads with codemode when available. Use edit/write only for authorized changes; bash executes programs and Git in an explicit working directory, never reads or searches files. Keep one writer per worktree and isolate candidate output paths. Read-only reviewers never receive bash, edit, write, or nested delegation. Loading this skill grants no new permission: push, PR creation, merge, external messages, and destructive operations require explicit authorization in the current session. Commit only when authorized.
Launch the three readers in one call, and keep `cwd` on the outer call when they must share a directory:
```js
subagent({ workflow: "parallel", args: { tasks: [
{ agent: "pstack.judgment-agent", task: "<references/judgment-reviewer.md with transcript or digest>" },
{ agent: "pstack.verifier", task: "<references/tooling-reviewer.md with transcript or digest>" },
{ agent: "pstack.strongest-agent", task: "<references/divergent-reviewer.md with transcript or digest>" }
] } })
```
Backlog filing is an external write. Prepare the backlog items locally and file only with explicit current-session authorization. Read-only synthesis returns proposed edits; the parent applies only the explicitly approved subset. Reviewing a worktree uses the outer `subagent` `cwd`, or an absolute path in the task text; `cwd` inside a task item is rejected.From jiangkoumo/pi-pstack, MIT.
More from jiangkoumo/pi-pstack
- 0.647score
poteto-help
jiangkoumo
Guides users through pstack setup, /skill:poteto-mode, and picking the skill, playbook, or principle for a task.
SkillAFreshness: A★ 27Claude Code +9 - 0.647score
statechart
jiangkoumo
Draw what an app's user sees as a Mermaid statechart from a TLA+ model.
SkillAFreshness: A★ 27Claude Code +9 - 0.637score
recall
jiangkoumo
Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a…
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
how
jiangkoumo
Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which…
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
architect
jiangkoumo
Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in.
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
interrogate
jiangkoumo
Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart".
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
poteto-mode
jiangkoumo
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work.
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
create-verification-skill
jiangkoumo
Generate a project-local verification skill that drives your app the way a user does — any language, framework, or platform.
SkillAFreshness: A★ 27Claude Code +9 - 0.620score
automate-me
jiangkoumo
Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how…
SkillAFreshness: A★ 27Claude Code +9 - 0.620score
benchmark-checklist
jiangkoumo
Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it.
SkillAFreshness: A★ 27Claude Code +9 - 0.620score
correct
jiangkoumo
Find the mistakes agents keep repeating in this repo and make each one impossible.
SkillAFreshness: A★ 27Claude Code +9 - 0.620score
ketchup
jiangkoumo
Catch the user up on what changed in this chat since their last message, in plain words and small visuals.
SkillAFreshness: A★ 27Claude Code +9
Signals
- Stars
- 27
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 21, 2026 (7 days ago)
- Last release
- Oct 24, 2026 (4 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/jiangkoumo/pi-pstack
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
- 0.769score
reflect
backnotprop
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 2.7KClaude Code +9 - 0.404score
reflect
dsebban
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 68Claude Code +9 - 0.398score
reflect
minghinmatthewlam
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 46Claude Code +9 - 0.389score
reflect
iap
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 27Claude Code +9 - 0.386score
reflect
n3m6
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 19Claude Code +9 - 0.383score
reflect
enitrat
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 15Claude Code +9 - 0.380score
reflect
peterpme
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillBFreshness: B★ 93Claude Code +9 - 0.372score
reflect
shrimpwtf
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillBFreshness: B★ 39Claude Code +9 - 0.365score
reflect
lucasheriques
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 3Claude Code +9 - 0.361score
reflect
olibyte
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: A★ 2Claude Code +9 - 0.357score
reflect
kkgogogo17
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillBFreshness: B★ 10Claude Code +9 - 0.339score
reflect
gutierrezje
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill.
SkillAFreshness: AClaude Code +9
More from jiangkoumo
- 0.650score
ego-decision-layer
jiangkoumo
多步线性浏览器任务(连续点击、翻页、搜索表单提交、导航跳转)的默认入口:用 `ego-decision-layer` 一条命令让决策层在单个 ego-browser 进程内闭环决策(默认 System One / Jev,可换本地 OpenAI 兼容后端;browser automation /…
SkillAFreshness: A★ 27Claude Code +9 - 0.647score
statechart
jiangkoumo
Draw what an app's user sees as a Mermaid statechart from a TLA+ model.
SkillAFreshness: A★ 27Claude Code +9 - 0.647score
poteto-help
jiangkoumo
Guides users through pstack setup, /skill:poteto-mode, and picking the skill, playbook, or principle for a task.
SkillAFreshness: A★ 27Claude Code +9 - 0.637score
recall
jiangkoumo
Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a…
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
architect
jiangkoumo
Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in.
SkillAFreshness: A★ 27Claude Code +9 - 0.622score
interrogate
jiangkoumo
Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart".
SkillAFreshness: A★ 27Claude Code +9
Cite this page
reflect skill. Agent Mart. https://agentmart.dev/skills/jiangkoumo-reflect (last updated 2026-10-24)