continuous-learning
Skill1 starsChanged 7 months agoMITView on GitHub
Extract repeated patterns from archived sessions and offer to convert them into reusable skills
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 repository206 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- project-healthSkill
- skill-validatorSkill
- accessibilitySkill
- agent-debugSkill
- agent-evaluateSkill
- ai-governanceSkill
- ai-system-reviewSkill
- api-docs-generateSkill
- api-examplesSkill
- api-mockSkill
- api-test-generateSkill
- api-validateSkill
- architecture-diagramSkill
- ask-mattSkill
- assumption-mapSkill
- boilerplateSkill
- brainstormSkill
- branch-finishSkill
- briefingSkill
- browser-testing-with-devtoolsSkill
- bundle-analyzeSkill
- cache-strategySkill
- canarySkill
- carefulSkill
- cavemanSkill
- changelog-autoSkill
- chaos-testSkill
- ci-setupSkill
- ci-sweepSkill
- cleanprojectSkill
- click-path-auditSkill
- codebase-designSkill
- code-review-checklistSkill
- code-tourSkill
- commitSkill
- completion-verifySkill
- complexity-reduceSkill
- component-librarySkill
- config-cleanupSkill
- config-generateSkill
- conflict-resolveSkill
- container-optimizeSkill
- context-budgetSkill
- context-engineeringSkill
- context-restoreSkill
- context-saveSkill
- contributingSkill
- cost-trackSkill
- councilSkill
- create-todosSkill
- cross-modal-reviewSkill
- database-connectSkill
- db-diagramSkill
- ddd-modelSkill
- debug-root-causeSkill
- debug-sessionSkill
- debug-systematicSkill
- decision-logSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 37 edited versions we read keep these.
2
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
- Distinctive: line 29
If fewer than 3 session files exist, report "Not enough session history yet (need 3+)" and exit.
- Distinctive: line 150
Never deletes or modifies existing skills or session files.
- Very specific: line 152
Does not commit anything; user must run /commit explicitly.
“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
Scan archived session logs to surface recurring manual workflows, then offer to convert high-frequency patterns into new SKILL.md stubs so repeated work becomes permanent automation.
Usage
/continuous-learning # Scan all archived sessions for patterns
/continuous-learning --min 2 # Lower threshold (default: 3 repetitions)
/continuous-learning --generate # Auto-generate stubs without promptingBehavior
Phase 1: Discover sessions
# Find all archived session files (not the active .current-session pointer)
find .claude/sessions -name "*.md" -not -name ".current-session" 2>/dev/null | sortIf fewer than 3 session files exist, report "Not enough session history yet (need 3+)" and exit.
Phase 2: Extract commands and workflows
Scan each session file for lines that match invocation patterns:
# Commands invoked (slash commands, skill names)
grep -h -E "^/[a-z]|^\*\*Command\*\*:|Ran:|Invoked:" .claude/sessions/**/*.md 2>/dev/null \
| sed 's|.*: ||' | sort | uniq -c | sort -rn | head -40Also extract multi-step sequences: look for clusters of 3+ consecutive commands that appear together in at least --min sessions.
Phase 3: Build pattern registry
Load or create .claude/cache/continuous-learning/patterns.json:
{
"last_scan": "2026-06-04T00:00:00Z",
"patterns": [
{
"commands": ["/security-scan", "/review", "/test"],
"frequency": 5,
"sessions": ["session-a.md", "session-b.md"],
"candidate_name": "quality-gate"
}
]
}Merge new findings with prior registry. Patterns that drop below --min threshold are removed.
Phase 4: Present findings
Display a ranked table of patterns that meet the threshold:
Repeated patterns found across your sessions:
Rank Frequency Pattern
──── ───────── ───────────────────────────────────────────
1 7x /security-scan → /review → /test
2 5x /find-todos → /fix-todos → /commit
3 4x /db-diagram → /migration-generate → /seed-data
4 3x /brainstorm → /write-plan → /implement
Convert any of these to a skill? (enter rank, or 'none'):Phase 5: Generate skill stub (if requested)
For the chosen pattern, emit a SKILL.md stub using the skillify template:
---
name: <candidate-name>
description: <inferred one-line description>
disable-model-invocation: false
risk: safe
---
# <Title>
## Usage
\`/<candidate-name>\`
## Behavior
1. Run `/step-one`
2. Run `/step-two`
3. Run `/step-three`
## Token Optimization
**Expected range**: 200–600 tokens (delegates to constituent skills)
**Early exit**: Each constituent skill handles its own early exit.
**Patterns used**: Delegation to existing skillsSave to skills/<candidate-name>/SKILL.md and confirm location to user. Do not commit.
Examples
No patterns yet:
/continuous-learning
→ Scanned 2 session files — need at least 3 to detect patterns.
Run more sessions, then try again.Patterns found:
/continuous-learning
→ Scanned 8 sessions. Found 3 repeated patterns (threshold: 3x).
[table shown]
Convert #1 to a skill? → User enters "1"
→ Stub written: skills/quality-gate/SKILL.mdToken Optimization
Expected range: 400–900 tokens (initial scan), 150–300 tokens (cache hit)
Caching: Stores pattern registry in .claude/cache/continuous-learning/patterns.json. On subsequent runs, only sessions newer than last_scan are re-processed; old results are merged from cache.
Early exit: Exits immediately if fewer than 3 archived session files exist.
Patterns used: Grep-before-Read (scan with grep, never read full session files into context), Bash for system queries, progressive disclosure (summary table before detail), early exit.
Edge Cases
- No sessions directory: Reports setup instructions and exits.
- Sessions with no command lines: Skips those files silently.
- Candidate name collision with existing skill: Appends
-2suffix and warns user. - User declines all patterns: Exits cleanly with "Nothing converted."
Safety
- Never deletes or modifies existing skills or session files.
- Skill stubs are written to
skills/only — not installed to~/.claude/skills/automatically. - Does not commit anything; user must run
/commitexplicitly.
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.

