continuous-learning
Skill2 starsChanged 28 days agoApache-2.0View on GitHub
Extracts architectural lessons, developer corrections, and project conventions from the current session and records them into permanent rules or Knowledge Items. Activate when the user runs /learn or after resolving a complex issue.
42 other projects use a version of this.
Adopted by
Most recently taken up by
- Rojios/everything-claude-codetheir own version, first seen Nov 8, 2026
- ahmadvahidi/skill-atlastheir own version, first seen Nov 8, 2026
- shetengteng/skillix-hubtheir own version, first seen Nov 8, 2026
- XD3an/cc-plustheir own version, first seen Nov 7, 2026
- pankaj-mahaur/Agent-Daemontheir own version, first seen Nov 6, 2026
- darknecrocities/SkillBuildertheir own version, first seen Nov 1, 2026
Used with
Projects with it also use project-guidelines-example, clickhouse-io 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.
HABUBUSSSkillproject-guidelines-example
Also in 7 projects that use this
HABUBUSSSkillclickhouse-io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Also in 6 projects that use this
mstuder-slalomSkillcontinuous-learning-v2
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Also in 7 projects that use this
Microsoft AzureSkilliterative-retrieval
Max-3-cycle protocol for agent sub-tasks with WHY context and coordinator validation. Use when spawning sub-agents to complete scoped work.
Also in 9 projects that use this
mstuder-slalomSkilldjango-verification
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
Also in 4 projects that use this
nek1987Skillpostgres-patterns
PostgreSQL patterns for reviewing migrations and writing efficient queries. Use when reviewing Alembic migrations, optimizing queries, or debugging database issues.
Also in 7 projects that use this
- +4 more from HABUBUSS
- +1 more from mstuder-slalom
Other versions42 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 42
- blader/claude-code-continuous-learning-skill★ 2.4ksame name
- blader/Claudeception★ 2.4ksame name
- loulanyue/awesome-claude-notes★ 272same name
- MRCalderon3D/everything-game-dev-code★ 105same name
- Fmarzochi/EGC★ 61same name
- AlexMikhalev/claude-code-continuous-learning-skill★ 36same name
- vneseyoungster/ChocoVine★ 27same name
- mhylle/claude-skills-collection★ 20same name
- ckorhonen/claude-skills★ 17same name
- darknecrocities/SkillBuilder★ 13same name
32 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 repository108 other files it gives its agents.
- AGENTS.mdAGENTS.md
- everything-gemini-maintainerSkill
- adversarial-fuzz-generatorSkill
- agent-evalsSkill
- ai-first-engineeringSkill
- alloydb-omni-vectorSkill
- apache-kafka-streamsSkill
- api-craftsmanSkill
- architecture-designerSkill
- argon-3d-game-engineSkill
- argon-3d-scene-architectSkill
- argon-procedural-asset-generatorSkill
- argon-visual-critique-loopSkill
- argo-workflowsSkill
- autonomous-incident-healerSkill
- axum-web-serviceSkill
- bigquery-vector-searchSkill
- browser-qa-testerSkill
- chromadb-vector-storeSkill
- cilium-ebpf-networkingSkill
- clickhouse-analyticsSkill
- cloud-deploy-canarySkill
- cloudflare-r2-object-storageSkill
- cloudflare-workersSkill
- cloud-run-agentsSkill
- context-cachingSkill
- context-distillation-compressorSkill
- context-warmerSkill
- cost-oracle-finopsSkill
- cross-repo-swarm-syncSkill
- cve-remediation-orchestratorSkill
- database-architectSkill
- dataproc-spark-analyticsSkill
- dbt-transformationSkill
- debezium-cdcSkill
- devops-pipelineSkill
- distributed-rate-limitingSkill
- docker-compose-orchestratorSkill
- duckdb-local-olapSkill
- dynamic-thinking-allocationSkill
- ebpf-microvm-sandboxSkill
- ebpf-sandbox-enforcerSkill
- elephant-goldfish-modelSkill
- envoy-ai-gatewaySkill
- ephemeral-swarm-orchestratorSkill
- fastapi-productionSkill
- fullstack-nextjsSkill
- game-audio-synthesizerSkill
- game-studioSkill
- gemini-function-callingSkill
- gemini-groundingSkill
- gemini-live-audio-transcriberSkill
- gemini-live-multimodalSkill
- gemini-live-screen-visionSkill
- gemini-multimodalSkill
- genetic-prompt-cross-pollinatorSkill
- git-craftsmanSkill
- github-opsSkill
- google-axSkill
- google-flow-orchestratorSkill
- The first 60 shown.
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 37 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 31
If the insight affects the broader repository architecture, write a dedicated Knowledge Item in <appDataDir>/knowledge with metadata.json …
“Common” is measured: kept by at least 6 in 10 of the 37 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
Continuous Learning & Instinct Recording
This skill enables Antigravity to retain lessons and developer feedback so mistakes are never repeated.
Learning Workflow
1. Identify the Core Insight
Determine what was learned:
- Correction: Did the user correct a style, framework version, or tool choice?
- Bug Fix: Was an obscure bug or configuration issue solved after debugging?
- Workflow: Was an optimal command sequence identified for building/testing?
2. Format the Instinct
Formulate a concise, imperative rule:
- Bad: "We had an issue with Docker not starting on port 8080."
- Good: "Always map Docker container port 8080 to host 8081 to avoid conflicting with local proxy."
3. Persist to .agents/rules/instincts.md
Append the new instinct under the appropriate section in .agents/rules/instincts.md:
- **Topic Name**: Concrete rule statement.4. For Major Architectural Changes: Create Knowledge Item
If the insight affects the broader repository architecture, write a dedicated Knowledge Item in <appDataDir>/knowledge with metadata.json and artifact details.
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.

