reflect
Skill9 starsChanged 37 days agoMITView on GitHub
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.
178 other projects use a version of this, 51 of them edited.
Adopted by
Most recently taken up by
- RohiRIK/skillstheir own version, first seen Nov 15, 2026
- sammyjoyce/prime-pstackedited, first seen Nov 15, 2026
- pronvis/skillsedited, first seen Nov 15, 2026
- upamune/skillsedited, first seen Nov 15, 2026
- feytox/skillstheir own version, first seen Nov 15, 2026
- Yeachan-Heo/oh-my-claude-sisyphustheir own version, first seen Nov 8, 2026
Other versions178 projects use a version of this.
Word for word · 0
None found.
Edited · 51
- backnotprop/pstack★ 3.8k43% same
- jtaroreh/agystack★ 12834% same
- uzairansaruzi/p3-stack★ 12638% same
- dsebban/skills★ 7138% same
- creedants/pstack-t3★ 1839% same
- Scino/fstack★ 1835% same
- mariusflorescu/pstack-t3★ 1341% same
- caidanw/skills★ 1152% same
- adjohn/pstack★ 948% same
- kkgogogo17/pi-pstack★ 935% same
41 more not listed
Wrote their own version · 127
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- github/gh-aw★ 5.6ksame name
- github/squad★ 3.4ksame name
- rilldata/rill★ 3ksame name
- microsoft/waza★ 1.5ksame name
- llama-farm/llamafarm★ 837same name
- haddock-development/claude-reflect-system★ 373same name
- egregore-labs/egregore★ 293same name
- akitaonrails/my-skills★ 283same name
117 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 169 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 54
Follow each approved row's Routing exactly:
- Very specific: line 61
If your environment ships a SKILL.md validator, run it on every touched skill before declaring done.
“Common” is measured: kept by at least 6 in 10 of the 169 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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
The parent finds its own transcript file before fanning out: the newest session in this workspace's transcript store. Call the Skill tool with pstack-harness to locate it. Do not read other workspaces' transcript stores. 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 -10That 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 message.content[0].text 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 spawns with no persona, each on the model set below and with full tool access. Reviewers need MCP access to look up the tickets, chat threads, and observability traces the transcript references, and a read-only mode can remove MCP tools. Call the Skill tool with pstack-harness for the spawn. Its Spawn a role section resolves the role and builds this CLI's spawn call.
Each reviewer and the synthesizer name a role line in the pstack models config and a default. Call the Skill tool with pstack-harness to resolve its model, effort, and agent type. Its Spawn a role section also covers a missing config, inherit-parent, and a rejected value.
| Lens | Role line | Default model | Prompt template |
| Judgment | reflect judgment, divergent, synthesizer | opus | references/judgment-reviewer.md |
| Tooling | reflect tooling | opus | references/tooling-reviewer.md |
| Divergent | reflect judgment, divergent, synthesizer | opus | 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 spawn with no persona, on the model from the reflect judgment, divergent, synthesizer line (default opus), with full tool access. It spot-verifies citations through MCP, and a read-only mode can remove MCP tools. 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. Call the Skill tool with principle-encode-lessons-in-structure.
For each such item, name the owning repository, an implementation owner, and the existing check it extends or replaces. Portable checks belong in the shared tooling that owns them. Keep task-specific checks in the consumer repository. Reuse an existing check when it already covers the failure.
Close the item only after a valid control passes, the original violation fails, and authoritative CI runs the replacement. Identify the redundant model inspection or prose obligation that can then be removed. Retain behavior checks the replacement cannot cover. Changes to acceptance criteria require review separately from the repair, so an agent cannot make its own failure pass by weakening the check.
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 ordinary Backlog item to your team's devex or backlog tracker without waiting. Security, privacy, auth, data, and permission-boundary findings are the exception. Keep those findings private and report them to the operator directly. Never post or link them in a public tracker, issue, PR, or comment. 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): follow the authoring guidance in
../poteto-mode/playbooks/authoring-a-skill.mdand run a draft / test / iterate loop. tune description: <skill path>(the skill exists but didn't trigger when it should have): rewrite the description per../poteto-mode/playbooks/authoring-a-skill.mdand run a description-optimization loop (test phrasings that should and should not trigger it).new skill: <kebab-name>: create it per../poteto-mode/playbooks/authoring-a-skill.md. 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

