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Agent skill

Continuous Learning

by rohitg00 in rohitg00/awesome-claude-code-toolkit

Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring

Apache-2.0Auto-check passedKnowledge Management

Install Continuous Learning

skills CLI
$ npx skills add rohitg00/awesome-claude-code-toolkit --skill continuous-learning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rohitg00/awesome-claude-code-toolkit continuous-learning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rohitg00/awesome-claude-code-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/continuous-learning .claude/skills/continuous-learning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
continuous-learning
GitHub stars
2.7k
Token cost
~1.4k tokens
SKILL.md length
396 words
Files
1
Skills in repo
37
Repo updated
First seen
Licence
Apache-2.0

At a glance

Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring

  • Works in 3 steps: Corrections - Mistakes caught during… → Successful Approaches - Patterns that… → Anti-Patterns - Approaches that caused…
  • Knowledge Management work in your project
  • SKILL.md covers Pattern Extraction Framework, Learning Entry Format, Confidence Scoring and Session Wrap-Up Protocol, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Continuous Learning is an agent skill from rohitg00/awesome-claude-code-toolkit. Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management. The repository describes itself as: The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills, 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion apps, 52… The licence is Apache-2.0.

When your agent uses it

  • Knowledge Management work in your project

Example prompts

  • “/continuous-learning”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Corrections - Mistakes caught during review or by the user
  2. Successful Approaches - Patterns that worked well and should be repeated
  3. Anti-Patterns - Approaches that caused problems and should be avoided

What it can do on your machine

Read from SKILL.md and the folder at commit ebdf1d5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Continuous Learning loads about 1.4k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 396 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from rohitg00/awesome-claude-code-toolkit at commit ebdf1d5, republished under its Apache-2.0 licence (© rohitg00). 396 words, ~1,360 tokens.

Download SKILL.mdSave it as .claude/skills/continuous-learning/SKILL.md (or your agent's skills folder).
name
continuous-learning
description
Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring

Continuous Learning

Pattern Extraction Framework

After every significant coding session, extract and categorize learnings into three buckets:

  1. Corrections - Mistakes caught during review or by the user
  2. Successful Approaches - Patterns that worked well and should be repeated
  3. Anti-Patterns - Approaches that caused problems and should be avoided

Learning Entry Format

yaml
pattern:
  id: "LEARN-2025-0042"
  category: "error-handling"
  type: "correction"         # correction | success | anti-pattern
  confidence: 0.85           # 0.0 to 1.0
  language: "typescript"
  context: "API error responses"
  observation: "Returning raw error messages from database exceptions exposes internals"
  lesson: "Always map database errors to application-level error codes before returning"
  example:
    before: "catch (e) { res.status(500).json({ error: e.message }) }"
    after: "catch (e) { logger.error(e); res.status(500).json({ error: 'INTERNAL_ERROR' }) }"
  frequency: 3               # times this pattern has been observed
  last_seen: "2025-06-15"

Confidence Scoring

ScoreMeaningAction
0.95+Verified across multiple projectsApply automatically
0.80-0.94Confirmed in this codebaseApply and mention
0.60-0.79Observed but not fully validatedSuggest with caveat
0.40-0.59Hypothesis based on limited dataAsk before applying
<0.40Speculative, needs validationDocument but do not apply

Update confidence based on:

  • +0.10 when pattern is confirmed correct by user
  • +0.05 when pattern is observed again in a different context
  • -0.15 when pattern leads to a correction
  • -0.20 when pattern is explicitly rejected by user

Session Wrap-Up Protocol

At the end of each session or before context compaction:

  1. Review changes made - Scan diffs for patterns
  2. Identify corrections - What was changed after initial implementation?
  3. Note successful first-attempts - What worked without revision?
  4. Record environment details - Framework versions, config specifics
  5. Update confidence scores - Adjust based on session outcomes
  6. Write to knowledge base - Append new entries to CLAUDE.md or LEARNED.md
markdown
## Session Learnings (2025-06-15)

### Corrections Applied
- [0.85] TypeScript: Use `satisfies` instead of `as` for type narrowing with object literals
- [0.90] Next.js: Server Actions must be async functions, even for synchronous operations

### Successful Patterns
- [0.80] PostgreSQL: Partial indexes on status columns reduced query time by 60%
- [0.75] React: Extracting data fetching into Server Components eliminated 3 useEffect hooks

### Anti-Patterns Identified
- [0.70] Avoid: Nesting more than 2 levels of Suspense boundaries (causes waterfall)
- [0.65] Avoid: Using `any` to suppress TypeScript errors in catch blocks (use `unknown`)

Knowledge Base Organization

Structure the knowledge base by domain:

knowledge/
  error-handling.md      # Error patterns across languages
  testing.md             # Test patterns and anti-patterns
  performance.md         # Optimization learnings
  api-design.md          # API design decisions
  deployment.md          # Infrastructure learnings
  project-specific.md    # Current project conventions

Each file follows the same entry format. Deduplicate entries with matching observation fields by incrementing frequency and updating confidence.

Show full SKILL.md (166 more words)Show less

Correction Tracking

When a user corrects code or approach:

  1. Record what was originally produced
  2. Record what the correction was
  3. Identify the root cause (wrong assumption, missing context, outdated pattern)
  4. Create or update a learning entry
  5. Search for similar patterns that might need the same correction
markdown
### Correction Log
- **Original**: Used `useEffect` to fetch data on mount
- **Correction**: Moved data fetching to Server Component
- **Root cause**: Applied client-side SPA pattern in Server Component context
- **Generalization**: In Next.js App Router, prefer server-side data fetching for initial page data
- **Confidence**: 0.90 (confirmed across 4 components)

Pattern Reinforcement

Track how often patterns are applied and whether they hold:

Pattern: "Use zod for API input validation"
  Applied: 12 times
  Confirmed: 11 times
  Corrected: 1 time (edge case with file uploads)
  Confidence: 0.92
  Status: ESTABLISHED

Statuses:

  • EMERGING (frequency < 3) - New pattern, needs validation
  • GROWING (frequency 3-7) - Building evidence, apply with mention
  • ESTABLISHED (frequency 8+, confidence > 0.85) - Apply automatically
  • DEPRECATED - Once valid, now superseded by a better approach

Integration with Memory Files

Store learnings in the project's memory file (CLAUDE.md or equivalent):

  • High-confidence learnings (>0.85) go in the main instructions section
  • Medium-confidence (0.60-0.84) go in a dedicated "Learnings" section
  • Low-confidence (<0.60) stay in session notes until validated
  • Deprecated patterns move to an archive section with reason for deprecation

Review and prune the knowledge base monthly. Remove entries that have not been referenced in 90 days and have confidence below 0.70.

© rohitg00, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/continuous-learning of rohitg00/awesome-claude-code-toolkit.

Open the folder on GitHubat commit ebdf1d5

Compare with similar skills

Continuous Learning next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Continuous Learning compared with similar skills
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Continuous Learning this skillrohitg00/awesome-claude-code-toolkit2.7k—~1.4kAutomated safety check: PassApache-2.0
Logseq Review Workflow Evallogseq/logseq45k—~1kAutomated safety check: PassAGPL-3.0
Baoyu URL To Markdownsdyckjq-lab/llm-wiki-skill2.5k2 repos~3.2kAutomated safety check: PassNone
Obsidian CLIAtmosphere/atmosphere3.8k13 repos~795Automated safety check: PassApache-2.0
Esm Cjs Risk Scanlogseq/logseq45k—~3.3kAutomated safety check: PassAGPL-3.0
Karpathy LLM WikiAstro-Han/karpathy-llm-wiki2.4k—~3.6kAutomated safety check: PassMIT

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Categories

Questions about Continuous Learning

What does Continuous Learning do?

Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring. Continuous Learning is an agent skill from rohitg00/awesome-claude-code-toolkit.

When should I use Continuous Learning?

Continuous Learning fits situations like: knowledge Management work in your project.

How do I install Continuous Learning in Claude Code?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill continuous-learning -a claude-code`. Or copy the skill folder (skills/continuous-learning in rohitg00/awesome-claude-code-toolkit) into .claude/skills/continuous-learning in your project. Claude Code loads it when a task matches its description.

How do I install Continuous Learning in Codex?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill continuous-learning -a codex`. Or copy the skill folder (skills/continuous-learning in rohitg00/awesome-claude-code-toolkit) into .agents/skills/continuous-learning in your project. Codex loads it when a task matches its description.

Can I use Continuous Learning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rohitg00/awesome-claude-code-toolkit --skill continuous-learning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/continuous-learning, .gemini/skills/continuous-learning, .github/skills/continuous-learning and .opencode/skills/continuous-learning in your project.

What does Continuous Learning need to run?

SKILL.md names no scripts, command-line tools or credentials: Continuous Learning is instructions for the agent only.

Does Continuous Learning access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Continuous Learning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Continuous Learning use?

Continuous Learning is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Continuous Learning use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Continuous Learning?

Skills that share tags, products or a category with Continuous Learning: Logseq Review Workflow Eval (logseq/logseq, 45k stars), Baoyu URL To Markdown (sdyckjq-lab/llm-wiki-skill, 2.5k stars), Obsidian CLI (Atmosphere/atmosphere, 3.8k stars) and Esm Cjs Risk Scan (logseq/logseq, 45k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Continuous Learning?

rohitg00 (a GitHub user) maintains it in rohitg00/awesome-claude-code-toolkit, which has 2,683 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on May 12, 2026.

Source: rohitg00/awesome-claude-code-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.