
re0-memo
Turn a finished, failed, or disappointing work cycle into portable lessons, anti-patterns, quality gates, and next-cycle vocabulary. Use after a build, QA pass, demo, user complaint, or abandoned attempt when the useful output is what the next pass must learn rather than the code itself.
- Installs
- 1.2K
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/lilmgenius/paperthin --skill re0-memo- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads re0-memo automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Turn a completed cycle into lessons the next cycle can actually use.
Goal
re0-memo extracts durable learning from a work cycle without defending the artifact that produced it. A cycle can run, pass tests, and still be the wrong thing. The output is not a changelog or therapy note: it is a local, evidence-backed record of what worked, what misled the build, and what gate the next pass must clear.
Use re0-memo when the artifact is done, failed, disappointing, or ambiguous enough that the next agent needs the cycle's lessons more than its momentum.
Workflow
- Read the original objective, final artifact, QA evidence, user complaints, and any local planning notes.
- Separate working assets from misleading progress: contracts, schemas, tests, services, vocabulary, and examples that earned reuse vs. UI, panels, scaffolds, or abstractions that only looked productive.
- Generalize before recording: when feedback arrives as many specific complaints, cluster them upward into the shared pattern before writing anything down — many specifics against many items usually share one root gap. Record the root and its pattern family as the lesson; keep the specifics under it as evidence, not as lessons themselves.
- Name each failure as an anti-pattern, not a mood.
- Convert repeated or high-impact failures into quality gates for the next pass.
- Convert vague user direction into architecture vocabulary a fresh agent can use.
- Write or refresh local docs for the cycle: a re0-memo for lessons and a plan for next-cycle contracts, gates, and vocabulary.
- Verify that a from-scratch agent could avoid the same failure from those docs alone.
Rules
- Do not defend the artifact. If it missed the product, say what missed.
- Do not write a changelog. File lists and effort summaries are not lessons.
- Do not transcribe a specific complaint as a lesson. A lesson that only fixes the reported case keeps the system human-in-the-loop: the same class of failure returns anywhere a person didn't point. Escalate every specific to the pattern that catches its whole class — the reporter's exact words are evidence, not the gate.
- Preserve negative corpus. Failed paths are training data.
- Prefer hard gates over advice.
- Cite evidence from the cycle: objective, file facts, QA output, screenshots, transcripts, diffs, or user feedback.
- If the next agent cannot act on it, it is not a lesson yet.
- Keep provenance local; shipped artifacts should not narrate their scars.
Verification
Before finishing:
- Every lesson traces to observed cycle evidence.
- Every anti-pattern names a concrete failure mode and the gate that catches it.
- No lesson is a single reported case in disguise: each covers a class, with the specifics that raised it sitting under it as evidence.
- A fresh agent can tell what to preserve, what to discard, and what to test first without reading the whole old session.
FAQ
What does the re0-memo skill do?
Turn a finished, failed, or disappointing work cycle into portable lessons, anti-patterns, quality gates, and next-cycle vocabulary. Use after a build, QA pass, demo, user complaint, or abandoned attempt when the useful output is what the next pass must learn rather than the code itself.
How do I install re0-memo?
Run npx skills add https://github.com/lilmgenius/paperthin --skill re0-memo in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/re0-memo/ (personal) or .claude/skills/re0-memo/ (project).
Which AI agents can use re0-memo?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is re0-memo safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains re0-memo?
It is published by lilmgenius in lilmgenius/paperthin. It has 1,179 recorded installs.
More from lilmgenius/paperthin
dedash
lilmgenius/paperthin
Remove em-dashes and the dashes standing in for them from a user-owned scope, reading each occurrence in context and choosing the punctuation or wording that fits.
ssotize
lilmgenius/paperthin
Audit and consolidate a fact that's scattered across places into one canonical source, after approval, and replace the rest with references. Use when asked to find duplication, check consistency, locate the source of truth, deduplicate, consolidate, unify, or establish SSOT across artifacts or platforms. Starts read-only, reports the map and plan, then mutates only after explicit approval.
shower
lilmgenius/paperthin
Cold-read the artifact you're focused on from a fresh, zero-context sub-session to confirm it stands on its own — a shower-thought reset for accumulated session bias. Use when a long session has worn away your fresh eyes and you can no longer tell whether the artifact in focus is clear to someone with no prior context; before a handoff, publish, or merge; or when you want a clean-room comprehension smoke test. Spawns a separate context-free reviewer; it diagnoses, it does not fix.
hate
lilmgenius/paperthin
Attack a plan, design, or argument like you want it to fail before you commit real effort — return the single load-bearing objection and the cheapest experiment that would prove it matters, not a checklist. User-invoked on purpose: a hate-it reflex always in the agent's reach would bias it toward demolition. Weighs many failure axes but owns the synthesis to one root.
factchk
lilmgenius/paperthin
Verify reality-grounded claims against external sources in both directions before they ship — could the 'absurd' be real, could the 'obvious' be false or long-established? Use whenever an artifact, or the sentence you are about to write, asserts something as plausible, realistic, absurd, novel, or impossible from intuition rather than a checked source; before relying on a factual claim in prose, a design rationale, a research claim, or a plan. Fires on metacognitive doubt — when you can't actually know, verify instead of trusting the feeling. Scans read-only, then fixes the clear errors or flags the judgment calls; leaves deliberate fiction alone.
re0
lilmgenius/paperthin
Refresh an existing artifact into the current best v0. Use when the user asks to clean up, sync up, dedupe, de-noise, smooth, rewrite, or update an artifact after iteration; when nearby artifacts may have drifted; or when changes in one place should be reflected across related artifacts while keeping the result minimal.
Popular testing & qa skills
tdd
mattpocock/skills
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
grilling
mattpocock/skills
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
migrate-to-shoehorn
mattpocock/skills
Migrate test files from as type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace as in tests, or needs partial test data.
run-train
lllllllama/rigorpilot-skills
Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized trainoutputs/. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.
test-driven-development
obra/superpowers
Use when implementing any feature or bugfix, before writing implementation code
finishing-a-development-branch
obra/superpowers
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work