evolve
Skill50 starsChanged 7 months agoMITView on GitHub
Use when many related hardened instincts (high-confidence feedback_*/discovery_* memories) have piled up in one domain, when the user runs /evolve or asks to promote, cluster, graduate, or consolidate accumulated instincts into a Command, Skill, or Agent, or when files in Instinct Proposals need review. Part of the Instinct Engine. Not for one-off pattern capture (use patterns), daily journaling, or sharing instinct packs (use instinct-export / instinct-import).
41 other projects use a version of this.
Adopted by
Most recently taken up by
- SethGammon/Citadeltheir own version, first seen Nov 4, 2026
- vidit19sharma/neogentstheir own version, first seen Nov 1, 2026
- cabernect/caberostheir own version, first seen Nov 1, 2026
- Snowflake-Labs/coco-skillstheir own version, first seen Nov 1, 2026
- NobiResearch/Ovenbirdtheir own version, first seen Nov 1, 2026
- ES-92/esctheir own version, first seen Oct 20, 2026
Used with
Projects with it also use refactor-clean, map and 8 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.
TheKREATORSSkillrefactor-clean
No description
Also in 3 projects that use this
AWSSkillmap
Map verified service capabilities against customer-provided control framework and threat model. Produces mapping-results.json, controls-catalog.md, and framework-mapping.md. Supports pluggable frameworks: CCMv4, NIST 800-53, CIS Benchmarks, ISO 27001, etc. Split into 4 focused sub-skills for better accuracy; this skill orchestrates them.
Also in 5 projects that use this
diego-tobalinaSkillbuild-fix
Fix build and compilation errors systematically. Run when build fails.
Also in 3 projects that use this
launch52-aiSkillskill-create
Create and validate Claude Code skills with proper structure, checklists, and validation scripts. Use when creating a new skill, auditing existing skills, or ensuring skills meet quality standards. Generates complete skill scaffolds with SKILL.md, check scripts, guides, and templates.
Also in 3 projects that use this
qtzx06Skilleval
Evaluate trained YOLO model accuracy with mAP metrics and per-class error analysis. Identifies failure cases for targeted improvement. Use after training.
Also in 5 projects that use this
MontimageSkilltest-coverage
Improve test coverage by finding untested branches, error paths, and edge cases. Use when measuring or strengthening a project's tests. Don't use for production debugging, code review, or feature implementation.
Also in 3 projects that use this
Other versions41 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 41
- revfactory/harness★ 9.1ksame name
- Q00/ouroboros★ 6.3ksame name
- yologdev/yoyo-evolve★ 1.9ksame name
- iovisor/ubpf★ 996same name
- SethGammon/Citadel★ 927same name
- GAIR-NLP/ASI-Evolve★ 867same name
- Kanevry/session-orchestrator★ 53same name
- Snowflake-Labs/coco-skills★ 49same name
- unclejobs-ai/second-claude-code★ 41same name
- epicsagas/epic-harness★ 20same name
31 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 repository39 other files it gives its agents.
- docs/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- setup-brainSkill
- backfill-journal-body-contextSkill
- cierre-de-llamadaSkill
- coachingSkill
- coachSkill
- daily-journalSkill
- deconstructSkill
- diagnoseSkill
- doubt-driven-developmentSkill
- for-my-teamSkill
- graphifySkill
- health-contextSkill
- health-doctorSkill
- health-setupSkill
- ingest-githubSkill
- ingest-healthSkill
- ingest-youtubeSkill
- insightsSkill
- instinct-exportSkill
- instinct-importSkill
- interview-meSkill
- longitudinalSkill
- meeting-todosSkill
- nano-bananaSkill
- note-todosSkill
- optimize-brainSkill
- patternsSkill
- repurpose-talkSkill
- resolver-querySkill
- riseSkill
- second-brain-mappingSkill
- secret-warnSkill
- security-snapshotSkill
- setup-vault-typesSkill
- skillify-meta-loopSkill
- sunday-reviewSkill
- vault-systemSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 36 edited versions we read keep these.
0
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
- Very specific: line 11
When many related, high-confidence instincts pile up in one domain, that is a signal to promote them into ONE reusable structure instead of …
“Common” is measured: kept by at least 6 in 10 of the 36 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
/evolve — promote a cluster of instincts into a structure
{SKILL_DIR}= this skill's own folder (locally: the directory this SKILL.md lives in; a served brain substitutes the real absolute path before you read this). Shared starter files live at the repo root two levels up:{SKILL_DIR}/../... If a path does not resolve, name the missing file and stop — never guess another location.
When many related, high-confidence instincts pile up in one domain, that is a
signal to promote them into ONE reusable structure instead of leaving them as
loose memories. /evolve finds those clusters deterministically and drafts a
proposal you refine.
ECC source pattern: "/evolve clusters related instincts into higher-level structures: Commands / Skills / Agents." Reimplemented clean per license-hygiene.
Step 1 — run the clusterer (deterministic, zero LLM cost)
python3 "{SKILL_DIR}/../../scripts/instinct.py" evolveIt groups every instinct by inferred domain, computes each cluster's median
effective confidence, and for clusters that clear the propose bar
(>= 2 instincts AND median confidence >= 0.80) writes a scaffold to
<vault>/⚙️ Meta/Instinct Proposals/proposed-skill-<domain>.md. Clusters below
the bar print as watch (not yet ripe).
Step 2 — judge each PROPOSE cluster
For each proposal the script wrote, decide the structure:
- Command — the cluster is ONE repeatable procedure with a clear trigger.
- Skill — the cluster is a coherent body of domain guidance (most common).
- Agent — the cluster describes an autonomous multi-step workflow.
A cluster that is really just 2-3 facets of an existing rule should be CONSOLIDATED into that rule, not promoted. Reject those.
Step 3 — draft (only on confirm)
For an accepted cluster, draft the real skill/command body from the member instincts (keep each instinct's Action + Evidence). Place it in the right repo per the install rules, wire its discoverability + automation + verification in the SAME session (the three-layer wiring rule), then retire or link the source memories. Delete the proposal file once adopted or rejected — proposals are scratch, not a backlog.
Headless/auto mode
In a cron/--print session: run Step 1, report the PROPOSE clusters and the
proposal paths, and STOP. Promotion to a real skill is a judgment call that
needs a human — never auto-create skills.
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.

