reflect
Skill4 starsChanged 3 months agoMITView on GitHub
Session retrospective — capture learnings into the project context scaffold and per-project session memory.
172 other projects use a version of this.
Adopted by
Most recently taken up by
- Yeachan-Heo/oh-my-claude-sisyphustheir own version, first seen Nov 8, 2026
- Loner1024/skillstheir own version, first seen Nov 8, 2026
- caidanw/skillstheir own version, first seen Nov 8, 2026
- Yeachan-Heo/oh-my-claudecodetheir own version, first seen Nov 8, 2026
- endqwerty/endstacktheir own version, first seen Nov 8, 2026
- tristanphvn/keeltheir own version, first seen Nov 8, 2026
Used with
Projects with it also use poteto-help, setup-pstack 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.
ianclearySkillpoteto-help
Guides users through pstack setup, /poteto-mode, and picking the skill, playbook, or principle for a task. Type /poteto-help with a question.
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bnemaSkillsetup-pstack
Configure which Pi models pstack uses per role. Detects available provider/model specs and writes pstack's user configuration. Use for /setup-pstack, "configure pstack models", or changing pstack model choices.
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eryzerzSkillmake-bot-ui
Use when building a custom UI (page, dashboard, buttons) that should wake a Grok Bot over a webhook, when the user must provide a webhook sender key, or when exposing that UI on Tailscale.
Also in 19 projects that use this
ianclearySkillprinciple-explain-the-number
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Also in 26 projects that use this
jaydubya818Skillautomate-me
Use when the user wants working preferences captured in a reusable mode skill.
Also in 39 projects that use this
jaydubya818Skillpoteto-mode
Use when non-trivial work should follow the smallest rigorous Jstack workflow.
Also in 27 projects that use this
- +6 more from jaydubya818
Other versions172 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 172
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- github/gh-aw★ 5.6ksame name
- backnotprop/pstack★ 3.8ksame 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
162 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 repository53 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- llms.txtllms.txt
- actionableSkill
- astro-bootstrapSkill
- astro-patternsSkill
- autopilotSkill
- axon-code-intelSkill
- brainstormingSkill
- commit-conventionsSkill
- cross-repo-contextSkill
- django-bootstrapSkill
- django-patternsSkill
- executeSkill
- find-sessionSkill
- flutter-bootstrapSkill
- flutter-patternsSkill
- full-featureSkill
- intelSkill
- nextjs-bootstrapSkill
- nextjs-fullstack-bootstrapSkill
- nextjs-fullstack-patternsSkill
- nextjs-mui-bootstrapSkill
- nextjs-patternsSkill
- nextjs-shadcn-bootstrapSkill
- orchestratorSkill
- phase-breakdownSkill
- plan-and-scopeSkill
- prdSkill
- reactSkill
- recallSkill
- relaySkill
- rememberSkill
- scaffoldSkill
- scratchSkill
- tailwindSkill
- ux-specSkill
- ux-to-promptsSkill
- verify-astroSkill
- verify-djangoSkill
- verify-flutterSkill
- verify-nextjs-fullstackSkill
- verify-nextjs-muiSkill
- verify-nextjs-shadcnSkill
- verify-nextjsSkill
- verifySkill
- visual-feedbackSkill
- work-disciplineSkill
- worktreesSkill
- wrapSkill
- write-as-friendSkill
- write-as-humanSkill
- writing-clearlySkill
- writing-skillsSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 3 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 163 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 13
Run /reflect at the end of a productive session — especially when:
- Distinctive: line 58
After filtering, do a second pass on the surviving findings.
- Distinctive: line 100
Only write what the user explicitly approves.
- Very specific: line 106
Write each approved finding to its own file in the memory store, with the name/description/metadata frontmatter from Memory Organization …
- Very specific: line 107
Add a one-line pointer to it in MEMORY.md
- Distinctive: line 108
If a memory file already covers the topic, update or replace it rather than adding a duplicate
“Common” is measured: kept by at least 6 in 10 of the 163 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
Session Reflection
Capture what you learned this session into persistent memory.
When to Use
Run /reflect at the end of a productive session — especially when:
- You corrected Claude's approach or preferences
- You hit a tricky bug and found the root cause
- You established or discovered project conventions
- You repeated a workflow pattern multiple times
Skip for quick sessions or trivial changes.
1. Scan the Session
Review the conversation history. Look for four categories:
Corrections (highest signal)
- Times the user redirected your approach
- Suggestions the user rejected and what they wanted instead
- Explicit preferences ("always do X", "never do Y")
Debugging Insights
- Root causes that weren't obvious from the error
- Framework gotchas or environment quirks
- Diagnostic sequences that worked
Patterns
- Repeated workflows worth codifying
- File organization or naming conventions
- Tool preferences or configurations
Conventions
- Architectural patterns found in the codebase
- Implicit project rules not documented elsewhere
- Integration patterns between services
2. Filter Ruthlessly
Each candidate must pass ALL four checks:
- Stable? — Will this recur? One-off decisions don't need memory.
- Already documented? — Check CLAUDE.md, existing memory files, project docs. Don't duplicate.
- Actionable? — "The API is complex" is useless. "Always pass X header when calling Y endpoint" is useful.
- Project-scoped? — The memory store is per-project. If a finding applies to all projects (a user preference, a general workflow lesson), still record it here — note the broader scope in the entry so it can be promoted later.
Discard anything that fails any check.
3. Bridge to Project Context
After filtering, do a second pass on the surviving findings. Ask: "Is this finding project-structural?"
A finding is project-structural if it describes:
- An architectural decision or tradeoff (→
decisions.md) - A naming, file organization, or error handling convention (→
conventions.md) - A reusable structural pattern (→
patterns/)
For any project-structural findings, check if .claude/context/ exists:
If the scaffold exists: Propose writing them with the remember skill's format — read the installed remember skill (.claude/skills/remember/SKILL.md, or skills/remember/SKILL.md in the repo) for its classify → format → write steps rather than guessing the scaffold format. Present each one:
**Context type:** Decision | Convention | Pattern
**Target:** .claude/context/<file>
**Entry:**
> [The formatted entry text]Group these separately from session memory proposals (Step 4). The user approves context writes independently from memory writes.
If the scaffold doesn't exist: Skip this step. Mention that /intel can generate the scaffold if the user wants to persist project-level findings.
Non-structural findings (personal preferences, debugging tricks, tool configurations) stay in session memory only — continue to Step 4 for those.
4. Propose Session Memory Updates
For each surviving finding, present:
**Type:** User | Feedback | Project | Reference
**File:** <memory file slug — one fact per file, e.g. git-commit-style.md>
**Action:** Add | Update | Remove
> The exact text to write
**Evidence:** What happened in the session that produced thisPick Type using the same taxonomy as Memory Organization below. Group by type, then by file.
5. Write Approved Changes
Only write what the user explicitly approves.
Project context entries (from Step 3): Follow the installed remember skill (.claude/skills/remember/SKILL.md, or skills/remember/SKILL.md in the repo) — its classify → deduplicate → format → write process is the single source of truth for context-scaffold entries. Don't re-derive the format here.
Session memory entries (from Step 4):
- Write each approved finding to its own file in the memory store, with the
name/description/metadatafrontmatter from Memory Organization (create the file — don't append into an unrelated one) - Add a one-line pointer to it in
MEMORY.md - If a memory file already covers the topic, update or replace it rather than adding a duplicate
Memory Organization
Session memory lives in the harness's per-project auto-memory store:
~/.claude/projects/<project-path>/memory/. The convention is one fact per
file, each file carrying frontmatter:
---
name: {short-kebab-slug}
description: {one-line summary — this is what future sessions scan to judge relevance}
metadata:
type: {user | feedback | project | reference}
---
{The memory itself — a few lines. Link related memories with [[other-slug]].}Pick type by what the finding is: a fact or preference about the user → user;
guidance on how to work, or a correction → feedback; state about the current
work → project; a pointer to where information lives elsewhere → reference.
MEMORY.md is the index, not a store: one pointer line per memory file
(- [Title](file.md) — one-line hook), no frontmatter, kept short (it is always
loaded into context, and lines past ~200 are truncated). Never write memory
content directly into MEMORY.md.
Organize by topic, not by date. When a finding supersedes an earlier one, update or remove that memory file instead of appending a contradiction.
What NOT to Save
- Session-specific context (current task, temporary state)
- Information already in CLAUDE.md or project docs
- Speculative conclusions from limited evidence
- Generic best practices any developer would know
- Anything that contradicts established project conventions
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
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- 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.

