retrospective
Skill1 starsChanged 18 days agoMITView on GitHub
Biweekly vault ritual — Notice, Decide, Build, to find one piece of leverage and ship it.
69 other projects use a version of this.
Adopted by
Most recently taken up by
- Adelie-Squad/solosquadtheir own version, first seen Nov 8, 2026
- sbfnk/skillstheir own version, first seen Nov 8, 2026
- AndyB840506/skillstheir own version, first seen Nov 8, 2026
- paureis/pau-skillstheir own version, first seen Nov 8, 2026
- AsiaOstrich/EngramGraphtheir own version, first seen Nov 8, 2026
- simonasrazm/skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use dev-story, team-level and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
lilangMaxSkilldev-story
Read a story file and implement it. Loads the full context (story, GDD requirement, ADR guidelines, control manifest), routes to the right programmer agent for the system and engine, implements the code and test, and confirms each acceptance criterion. The core implementation skill — run after /story-readiness, before /code-review and /story-done.
Also in 12 projects that use this
CoralGameSkillteam-level
Orchestrate level design team: level-designer + narrative-director + world-builder + art-director + systems-designer + qa-tester for complete area/level creation.
Also in 12 projects that use this
CoralGameSkillteam-narrative
Orchestrate the narrative team: coordinates narrative-director, writer, world-builder, and level-designer to create cohesive story content, world lore, and narrative-driven level design.
Also in 12 projects that use this
lilangMaxSkillcreate-stories
Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.
Also in 11 projects that use this
- +7 more from lilangMax
- +1 more from CoralGame
Other versions69 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 69
- Donchitos/Claude-Code-Game-Studios★ 27ksame name
- alibaba/MNN★ 16ksame name
- glebis/claude-skills★ 410same name
- pixel-cellar/Claude-Code-Game-Studios★ 324same name
- blacklanternsecurity/red-run★ 296same name
- striderZA/OpenCodeGameStudios★ 118same name
- The01Geek/prflow★ 99same name
- PAIR-code/deliberate-lab★ 97same name
- AsiaOstrich/universal-dev-standards★ 84same name
- tranhieutt/software_development_department★ 71same name
59 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.
In this repository43 other files it gives its agents.
- AGENTS.mdAGENTS.md
- core/AGENTS.mdAGENTS.md
- evals/AGENTS.mdAGENTS.md
- index/AGENTS.mdAGENTS.md
- mcp/AGENTS.mdAGENTS.md
- tools/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- architecture-reviewSkill
- audit-notesSkill
- challenge-planSkill
- change-impactSkill
- clarify-requestSkill
- connect-mcpSkill
- create-teamSkill
- daily-planSkill
- debug-issueSkill
- define-termsSkill
- design-specSkill
- end-of-day-summarySkill
- handover-notesSkill
- join-teamSkill
- merge-workSkill
- migrate-legacy-engineSkill
- personal-setupSkill
- quick-noteSkill
- register-projectsSkill
- repo-mapSkill
- resolve-conflictsSkill
- resume-workSkill
- review-changeSkill
- set-profileSkill
- setup-repoSkill
- story-mapSkill
- suggest-skillsSkill
- summarize-filesSkill
- sync-websiteSkill
- trim-agent-docsSkill
- update-pluginSkill
- weekly-reviewSkill
- whats-changedSkill
- write-agent-docsSkill
- write-area-briefSkill
- write-context-docsSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 4 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 58 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 21
If your workload doubled tomorrow, what breaks first?
- Very specific: line 29
Eliminate → Automate → Delegate: Ask "what if we just stop doing this?" If nothing breaks, exit cheerfully — that's a win.
- Distinctive: line 36
If they can't name one, stop.
- Very specific: line 38
Write the scoped spec to decisions/log.md as a dated entry.
- Distinctive: line 41
Ask how to ship, lowest-infrastructure first:
- Distinctive: line 48
Default to the highest non-automated option that solves it.
“Common” is measured: kept by at least 6 in 10 of the 58 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
/retrospective — find one piece of leverage, ship it
One interview = one artifact. Also installs the [[operating-principles]] habits over time. Reads
context/priorities.md, context/current-focus.md, connections.md, decisions/log.md, recent
daily/*, and existing skills/*.
Phase 1 — Notice (find the candidate)
Ask, conversationally:
- What did you do 3+ times this week? (frequency)
- What felt manual, boring, or copy-paste? (drudgery)
- Where did you think "a smart intern could do this"? (delegation)
- If your workload doubled tomorrow, what breaks first? (constraint)
- What knowledge did you keep re-looking-up? (a missing note)
Output: 1-3 candidates, one line of "why this is leverage" each. Ask the user to pick one.
Phase 2 — Decide (scope it)
Walk the five filters from [[operating-principles]]:
- Constraint — which bottleneck does this solve?
- Eliminate → Automate → Delegate. Ask "what if we just stop doing this?" If nothing breaks,
exit cheerfully — that's a win. Log it to
decisions/log.mdand stop. - Map the steps — trigger, inputs, transformations, decision points, destination. If they can't articulate them, send them to sketch it first.
- Lowest autonomy that works — suggest < draft < supervise < auto. Default low; push back on "fully autonomous" without proof.
- Tie to an outcome — more output / less time / fewer errors / learning + a specific metric. If they can't name one, stop.
Write the scoped spec to decisions/log.md as a dated entry.
Phase 3 — Build (ship one artifact)
Ask how to ship, lowest-infrastructure first:
- A note — a permanent note in
notes/(often the answer for "I keep re-looking this up"). - A template — a reusable scaffold in
templates/. - A saved prompt / SOP — a
resources/doc the user runs by hand. - A new ritual — a
skills/<name>/SKILL.md(deterministic first; one AI step only if needed). - A scheduled task — only once the manual version works.
Default to the highest non-automated option that solves it. Build it, confirm it works, and remind the user to run it manually for a week before trusting it.
Output every run
- One
decisions/log.mdentry. 2. One shipped artifact. 3. A one-screen recap.
Rules
- Notice always runs first, even if the user arrives with an idea.
- Eliminate-first: if the answer is "stop doing it", that's success, not failure.
- Boring is beautiful — bias to notes/templates/prompts over agents.
When the floor is not met
Notice → Decide → Build asks the model to survey everything, pick the one piece of leverage, and ship it. The survey is the part that degrades: a weaker setup picks the most recent thing rather than the most leveraged, and the ritual becomes a to-do list.
Below the floor: run /audit-notes score instead. It scores the four layers against fixed criteria and names the top three gaps by a stated weighting, so the ranking comes from the rubric rather than from judgment.
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.

