Agent skill

Self Improving Cognition

by LeoYeAI in LeoYeAI/openclaw-master-skills

Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance.

MITAuto-check passed

Install Self Improving Cognition

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill self-improving-cognition -a claude-code

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

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills self-improving-cognition --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/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/self-improving-cognition .claude/skills/self-improving-cognition && 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
self-improving-cognition
GitHub stars
2.2k
Token cost
~4.3k tokens
SKILL.md length
853 words
Files
5 (incl. scripts, assets)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance.

  • Works in 3 steps: Cognitive Baseline (Week 1) → Targeted Training (Weeks 2-4) → Integration & Maintenance (Month 2+)
  • Noticing cognitive biases
  • SKILL.md covers Quick Reference, Cognitive Dimensions & Metrics, Logging Format and Cognitive Training Framework, plus 3 more sections
  • Runs Shell scripts from its folder

What it does

Self Improving Cognition is an agent skill from LeoYeAI/openclaw-master-skills. Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance. Use when noticing cognitive biases, making important decisions, solving complex problems, or wanting to enhance mental clarity and effectiveness.

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and assets (for example `_meta.json`, `assets/COGNITIVE_ASSESSMENT_TEMPLATE.md` and `clawhub.json`).

The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Noticing cognitive biases
  • Making important decisions
  • Solving complex problems
  • Wanting to enhance mental clarity and effectiveness

Example prompts

  • “/self-improving-cognition”

Requirements

  • A Bash shell

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Cognitive Baseline (Week 1)
  2. Targeted Training (Weeks 2-4)
  3. Integration & Maintenance (Month 2+)

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. 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

    Ships 1 file in scripts/ (Shell), which the agent can run.

    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

Self Improving Cognition loads about 4.3k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 853 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 853 words, ~4,338 tokens.

Download SKILL.mdSave it as .claude/skills/self-improving-cognition/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
self-improving-cognition
description
Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance. Use when noticing cognitive biases, making important decisions, solving complex problems, or wanting to enhance mental clarity and effectiveness.

Self-Improving Cognition

Structured approach to cognitive enhancement through measurable tracking of thinking patterns, bias identification, decision analysis, and mental skill development. Transforms vague "think better" into specific, improvable cognitive competencies.

Quick Reference

SituationAction
Making important decisionLog decision context, alternatives, reasoning, track outcome
Noticing cognitive biasIdentify bias type, record instance, develop correction strategy
Solving complex problemDocument problem space, approaches tried, breakthrough insights
Feeling mentally foggyTrack mental clarity factors, identify patterns, adjust routines
Learning new complex conceptMap understanding, identify gaps, track mastery progression

Cognitive Dimensions & Metrics

Attention & Focus (Cognitive Control)
  • Sustained Attention: Minutes of uninterrupted focus
  • Selective Attention: Ability to filter distractions (1-10)
  • Divided Attention: Task switching efficiency (1-10)
  • Focus Recovery: Time to regain focus after interruption
Memory & Recall (Information Processing)
  • Working Memory: Items held simultaneously (digit span, n-back)
  • Long-term Recall: Accuracy of factual recall (1-10)
  • Memory Speed: Time to retrieve information
  • Forgetting Curve: Retention after 1 day, 1 week
Logical Reasoning (Analytical Thinking)
  • Deductive Accuracy: Logical conclusion correctness (%)
  • Inductive Strength: Pattern recognition quality (1-10)
  • Fallacy Detection: Ability to spot reasoning errors (%)
  • Argument Quality: Structure and evidence strength (1-10)
Creative Thinking (Generative Cognition)
  • Idea Fluency: Number of ideas generated in time period
  • Idea Originality: Novelty score (1-10)
  • Concept Connection: Unusual associations made
  • Solution Elegance: Simplicity and effectiveness (1-10)
Metacognition (Thinking About Thinking)
  • Accuracy: Self-assessment vs. actual performance (% match)
  • Strategy Awareness: Understanding of own thinking processes
  • Error Detection: Ability to catch own mistakes
  • Learning Adaptation: Adjusting approach based on feedback

Logging Format

Cognitive Assessment Baseline

Append to .learnings/cognition/BASELINE.md:

markdown
## [COG-YYYYMMDD-001] Cognitive Baseline Assessment

**Assessed**: 2026-03-12T10:00:00Z
**Overall Cognitive Fitness**: 6.8/10
**Strengths**: Logical reasoning, Metacognition
**Areas for Improvement**: Sustained attention, Creative fluency

### Dimension Scores (1-10)
1. **Attention & Focus**: 5.5/10
   - Sustained: 25 minutes average
   - Selective: 6/10 (easily distracted by notifications)
   - Recovery: 3 minutes after interruption
   
2. **Memory & Recall**: 6.0/10
   - Working: 5±2 items (digit span)
   - Long-term: 7/10 (good factual recall)
   - Speed: 2.3 seconds average retrieval
   
3. **Logical Reasoning**: 8.0/10
   - Deductive: 85% accuracy
   - Inductive: 8/10 (strong pattern recognition)
   - Fallacy Detection: 75% accuracy
   
4. **Creative Thinking**: 5.0/10
   - Fluency: 12 ideas/10 minutes
   - Originality: 4/10 (mostly conventional)
   - Connections: 3 unusual associations/ session
   
5. **Metacognition**: 7.5/10
   - Accuracy: 80% (self-assessment vs. performance)
   - Strategy Awareness: 8/10 (knows thinking processes)
   - Error Detection: 7/10 (catches 70% of own errors)

### Cognitive Bias Inventory
- **Confirmation Bias**: Moderate (seeks confirming evidence)
- **Anchoring**: High (influenced by initial information)
- **Availability Heuristic**: Moderate (overweights recent examples)
- **Planning Fallacy**: High (underestimates time requirements)
- **Sunk Cost Fallacy**: Low (willing to cut losses)

### Environmental & Lifestyle Factors
- **Sleep**: 6.5/10 quality, 7 hours average
- **Nutrition**: 7/10 (balanced, but afternoon sugar)
- **Exercise**: 5/10 (3x/week, inconsistent)
- **Stress**: 6/10 (moderate work pressure)
- **Mental Stimulation**: 7/10 (varied but not challenging)

### Improvement Priorities
1. **Primary**: Increase sustained attention to 40+ minutes
2. **Secondary**: Boost creative fluency to 20+ ideas/10min
3. **Tertiary**: Reduce planning fallacy impact
4. **Supporting**: Improve sleep quality to 8/10

---
Decision Analysis Log

Append to .learnings/cognition/DECISIONS.md:

markdown
## [DEC-YYYYMMDD-001] Career Path Decision

**Decision Date**: 2026-03-12
**Importance**: High (career direction)
**Timeframe**: 6-12 month impact
**Status**: Decided (Option B)

### Context & Problem
Choose between:
- **Option A**: Stay current role (stable, limited growth)
- **Option B**: Take promotion (more stress, faster growth)
- **Option C**: Switch companies (unknown, potentially higher pay)

### Decision Process
1. **Information Gathering** (3 days)
   - Talked to 5 people in similar positions
   - Researched market salaries
   - Assessed personal tolerance for stress
   
2. **Criteria Weighting**
   - Growth potential: 30%
   - Work-life balance: 25%
   - Compensation: 20%
   - Learning opportunity: 15%
   - Team quality: 10%
   
3. **Option Scoring** (1-10 weighted)
   - Option A: 6.2 (stable but stagnant)
   - Option B: 7.8 (growth, manageable stress)
   - Option C: 6.5 (high risk, high potential reward)
   
4. **Cognitive Bias Check**
   - Status Quo Bias: Considered (Option A attractive due to comfort)
   - Loss Aversion: Addressed (willing to risk for growth)
   - Overconfidence: Guarded against (consulted others)
   - Sunk Cost: Irrelevant (no prior investment)

### Reasoning & Rationale
- **Option B chosen** because:
  1. Aligns with 3-year career goal (management track)
  2. Stress increase tolerable (15% vs. 50% more pay)
  3. Company investment in my growth (training budget)
  4. Backup plan exists (can return to individual contributor if needed)

### Confidence Level & Uncertainty
- **Confidence**: 8/10 in decision quality
- **Key Uncertainties**: 
  - Actual stress level in new role (estimated)
  - Team dynamics with new reports (unknown)
  - Company stability (market conditions)
- **Contingency Plans**:
  - 3-month review: If stress > 7/10, implement coping strategies
  - 6-month exit: If miserable, start job search with new title

### Expected Outcome vs. Actual Tracking
- **Expected**: 20% skill growth, 50% pay increase, stress +2 points
- **Actual**: [To be filled after 3 months]
- **Variance Analysis**: [To be filled]

### Cognitive Lessons
1. **Bias Management**: Successfully resisted status quo bias
2. **Decision Quality**: Structured approach improved confidence
3. **Information Sufficiency**: Gathered enough but not too much
4. **Emotion Integration**: Acknowledged fear but didn't let it decide

---
Problem-Solving Log

Append to .learnings/cognition/PROBLEMS.md:

markdown
## [PROB-YYYYMMDD-001] System Architecture Design Problem

**Problem Date**: 2026-03-12
**Complexity**: High (multiple constraints, novel requirements)
**Time Spent**: 8 hours over 2 days
**Solution Status**: Resolved (hybrid approach)

### Problem Definition
Design scalable notification system supporting:
- 1M+ users
- 10+ notification types
- <100ms latency requirement
- 99.99% reliability
- Cost < $500/month at scale

### Solution Approaches Considered
1. **Approach A**: Single monolithic service
   - Pros: Simple, fast to build
   - Cons: Hard to scale, single point of failure
   - Viability: Low (scaling constraints)
   
2. **Approach B**: Microservices architecture
   - Pros: Scalable, fault-tolerant
   - Cons: Complex, operational overhead
   - Viability: Medium (over-engineered for MVP)
   
3. **Approach C**: Serverless functions + queue
   - Pros: Cost-effective, auto-scaling
   - Cons: Cold start latency, vendor lock-in
   - Viability: High (meets requirements)

4. **Approach D**: Hybrid (Approach C + simple service)
   - Pros: Balances scalability and simplicity
   - Cons: More moving parts
   - Viability: Selected

### Breakthrough Insights
1. **Core Realization**: 80% of notifications are 3 types → optimize those
2. **Pattern Recognition**: Similar to email sending systems (existing patterns)
3. **Constraint Reframing**: Reliability requirement actually means "eventual consistency with retries"
4. **Simplification**: Batch processing acceptable for non-urgent notifications

### Solution Architecture
- **Urgent notifications** (<100ms): Dedicated service (5% of traffic)
- **Standard notifications**: Serverless functions + queue (95% of traffic)
- **Fallback**: Retry queue with exponential backoff
- **Monitoring**: Latency and error tracking for each type

### Cognitive Process Analysis
- **Initial Impasse**: Overwhelmed by constraints (30 minutes stuck)
- **Breakthrough Method**: Whiteboard diagramming → pattern emergence
- **Critical Thinking**: Questioned each requirement's validity
- **Creative Synthesis**: Combined approaches rather than choosing one

### Performance Metrics
- **Design Quality**: 8/10 (meets all requirements, elegant compromise)
- **Cognitive Effort**: High (complex trade-off analysis)
- **Time Efficiency**: Good (8 hours for complex problem)
- **Solution Novelty**: Medium (adapted existing patterns)

### Improvement Opportunities
1. **Faster Pattern Recognition**: Study more system design patterns
2. **Better Constraint Analysis**: Formalize requirement prioritization
3. **Reduced Overthinking**: Set timebox for decision making
4. **Collaborative Thinking**: Involve others earlier for perspective

---
Bias Identification & Correction

Append to .learnings/cognition/BIASES.md:

markdown
## [BIAS-YYYYMMDD-001] Confirmation Bias in Project Estimation

**Identified**: 2026-03-12T14:30:00Z
**Bias Type**: Confirmation Bias
**Context**: Software project timeline estimation
**Impact**: Moderate (2-week underestimation)

### Bias Manifestation
- **Situation**: Estimating new feature development time
- **Behavior**: Sought evidence supporting optimistic timeline
- **Ignored**: Previous similar projects that took longer
- **Result**: 4-week estimate (actual likely 6 weeks)

### Detection Process
1. **Trigger**: Felt too confident about estimate
2. **Check**: Asked "What evidence contradicts this?"
3. **Discovery**: Found 3 similar past projects averaged 6 weeks
4. **Recognition**: Realized seeking confirming evidence only

### Correction Applied
1. **Forced Consideration**: Listed all past similar projects
2. **Outsider View**: Asked "What would I estimate for someone else?"
3. **Pre-mortem**: Imagined project failed, identified causes
4. **Adjustment**: Revised to 6 weeks with risk buffer

### Root Cause Analysis
- **Motivation**: Wanted to please stakeholders with fast timeline
- **Pattern**: Recurring in estimation situations (3rd instance this year)
- **Environment**: Pressure to deliver quickly, reward for optimism
- **Cognitive Style**: Prefers action over caution

### Prevention Strategy
1. **Checklist**: Always review past similar projects before estimating
2. **Devil's Advocate**: Assign someone to challenge optimistic estimates
3. **Buffer Rule**: Add 30% to initial optimistic estimate
4. **Calendar Review**: Monthly review of estimates vs. actuals

### Bias Strength Assessment
- **Before Correction**: 8/10 (strong bias influence)
- **After Correction**: 3/10 (minimal residual influence)
- **Improvement**: 5-point reduction through structured process
- **Durability**: Expected to last 2-3 months before reinforcement needed

### Related Biases to Monitor
- **Planning Fallacy**: Often co-occurs with confirmation bias
- **Optimism Bias**: Similar root in underestimating difficulties
- **Anchoring**: Initial estimate anchors subsequent thinking

---

Cognitive Training Framework

Attention Training Protocol
  • Pomodoro Technique: 25min focus, 5min break (measure interruptions)
  • Deep Work Blocks: 90min uninterrupted sessions (track quality)
  • Distraction Management: Phone away, website blockers (measure effectiveness)
  • Mindfulness Practice: 10min daily meditation (track focus improvements)
Memory Enhancement System
  • Spaced Repetition: Anki or similar for factual recall
  • Method of Loci: Memory palace for complex information
  • Chunking Practice: Grouping information into meaningful units
  • Recall Testing: Regular retrieval practice vs. re-reading
Logical Reasoning Exercises
  • Logic Puzzles: Daily puzzle solving (track speed/accuracy)
  • Argument Analysis: Critique articles/arguments (identify fallacies)
  • Deduction Games: Games like Mastermind (pattern deduction)
  • Scientific Thinking: Formulate and test hypotheses
Creativity Development
  • Idea Generation: Daily 10-minute brainstorming (count ideas)
  • Alternative Uses Test: Find novel uses for common objects
  • Concept Combination: Merge unrelated concepts (track originality)
  • Constraint Removal: "What if X limitation didn't exist?" exercises
Metacognition Building
  • Thinking Journals: Document thought processes for decisions
  • Error Logs: Record and categorize thinking errors
  • Prediction Calibration: Make predictions, compare to outcomes
  • Strategy Evaluation: Assess effectiveness of thinking approaches

Cognitive Performance Factors

Lifestyle Optimization
  • Sleep: 7-9 hours, consistent schedule (track cognitive impact)
  • Nutrition: Balanced, regular meals, hydration (energy levels)
  • Exercise: 150min/week moderate (cognitive benefits)
  • Stress Management: Techniques, boundaries (prevent impairment)
Environmental Design
  • Workspace: Organized, minimal distractions (focus support)
  • Tools: Appropriate for cognitive task (reduce mental load)
  • Timing: Match tasks to circadian rhythms (productivity alignment)
  • Social: Collaboration vs. solo based on task needs
Cognitive Load Management
  • Chunking: Break complex tasks into manageable units
  • Externalization: Write down to free working memory
  • Automation: Develop routines for repetitive decisions
  • Delegation: Offload appropriate cognitive tasks
Show full SKILL.md (330 more words)Show less

Integration with Other Skills

With Self-Improving-Learning
  • Apply optimal learning techniques based on cognitive science
  • Match learning methods to cognitive strengths
  • Use metacognition to optimize learning strategies
With Self-Improving-Work
  • Apply clear thinking to work decisions and problem-solving
  • Use cognitive principles for productivity and focus
  • Match work tasks to cognitive energy levels
With Self-Improving-Habit
  • Build habits supporting cognitive performance (sleep, exercise)
  • Use habit stacking for cognitive training routines
  • Reduce decision fatigue through habit automation

Success Metrics

Performance Metrics
  • Attention Span: Sustained focus time (increase target)
  • Memory Accuracy: Recall correctness (% improvement)
  • Decision Quality: Outcome vs. expectation (closer alignment)
  • Problem-Solving Speed: Time to effective solution (reduction)
  • Bias Detection: Frequency and correction rate (increase)
Process Metrics
  • Metacognitive Accuracy: Self-assessment vs. reality (% match)
  • Cognitive Strategy Use: Variety and appropriateness
  • Bias Awareness: Identification frequency and speed
  • Adaptation Rate: Speed of adjusting thinking approaches
Outcome Metrics
  • Better Decisions: Improved life/work outcomes
  • Reduced Errors: Fewer mistakes from poor thinking
  • Increased Innovation: More novel solutions generated
  • Enhanced Learning: Faster skill/knowledge acquisition

Getting Started

Step 1: Cognitive Baseline (Week 1)
  1. Complete baseline assessment across 5 dimensions
  2. Identify top 2 cognitive strengths and weaknesses
  3. Select 1-2 priority areas for improvement
  4. Establish initial metrics and tracking system
Step 2: Targeted Training (Weeks 2-4)
  1. Implement specific exercises for priority areas
  2. Daily tracking of cognitive performance metrics
  3. Weekly review of progress and adjustments
  4. Environmental optimization for cognitive support
Step 3: Integration & Maintenance (Month 2+)
  1. Incorporate cognitive techniques into daily work/life
  2. Regular bias checks in important decisions
  3. Quarterly reassessment of cognitive fitness
  4. Continuous refinement of thinking strategies

Scientific Foundation

Based on:

  • Dual Process Theory (Kahneman): System 1 vs. System 2 thinking
  • Cognitive Bias Research (Tversky & Kahneman): Heuristics and biases
  • Working Memory Model (Baddeley): Cognitive architecture
  • Deliberate Practice (Ericsson): Expertise development
  • Metacognition Research (Flavell): Thinking about thinking

Integration Note: This skill provides the thinking toolkit for other self-improving skills, ensuring decisions and problem-solving are based on clear, bias-aware cognition rather than intuition or habit alone.

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

Files

SKILL.md and 4 other files (scripts, assets) in skills/self-improving-cognition of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • assets/COGNITIVE_ASSESSMENT_TEMPLATE.md
  • clawhub.json
  • scripts/cognitive-warmup.sh

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Self Improving Cognition 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.

Self Improving Cognition compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Self Improving Cognition this skillLeoYeAI/openclaw-master-skills2.2k—~4.3kAutomated safety check: PassMIT
Deep Think Maximum Cognitive Effort Protocol Mq8kvw92nexu-io/open-design100k—~1.7kAutomated safety check: PassApache-2.0
Vc Problem Solvingwithkynam/vibecode-pro-max-kit1.1k1 repos~1.1kAutomated safety check: PassMIT
Is This A Problemanthropics/claude-for-legal9.6k2 repos~2.3kAutomated safety check: PassApache-2.0
First Principles Thinkingmindfold-ai/Trellis15k—~4.1kAutomated safety check: PassMIT
Cognitive Patternruvnet/ruflo74k—~384Automated safety check: NotesMIT

Similar skills

  • Vc Problem Solving

    withkynam/vibecode-pro-max-kit

    Apply systematic problem-solving techniques when stuck. An agent skill from withkynam/vibecode-pro-max-kit.

    1.1k GitHub starsUsed in 1 repo~1.1k tokens
    Auto-check passed
  • Is This A Problem

    anthropics/claude-for-legal

    Official

    Fast "is this a problem?" answer for the quick Slack question — pattern-matches against your calibration.

    9.6k GitHub starsUsed in 2 repos~2.3k tokens
    Business, Finance & HRAuto-check passed
  • First Principles Thinking

    mindfold-ai/Trellis

    Systematic first principles thinking for any problem domain.

    15k GitHub stars~4.1k tokensUpdated 10 days ago
    DevelopmentAuto-check passed
  • Cognitive Pattern

    ruvnet/ruflo

    Define and manage cognitive patterns for agent reasoning and decision-making

    74k GitHub stars~384 tokensUpdated today
    Auto-check: notes
  • Resourceful Problem Solving

    swarmclawai/swarmclaw

    Always-on guidance for solving tasks resourcefully. An agent skill from swarmclawai/swarmclaw.

    688 GitHub stars~460 tokensUpdated 3 mo ago
    Agent WorkflowsAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 1,235 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Questions about Self Improving Cognition

What does Self Improving Cognition do?

Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance. Self Improving Cognition is an agent skill from LeoYeAI/openclaw-master-skills. Systematic improvement of thinking patterns, decision quality, problem-solving abilities, and mental performance.

When should I use Self Improving Cognition?

Self Improving Cognition fits situations like: noticing cognitive biases; making important decisions; solving complex problems; wanting to enhance mental clarity and effectiveness.

How do I install Self Improving Cognition in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill self-improving-cognition -a claude-code`. Or copy the skill folder (skills/self-improving-cognition in LeoYeAI/openclaw-master-skills) into .claude/skills/self-improving-cognition in your project. Claude Code loads it when a task matches its description.

How do I install Self Improving Cognition in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill self-improving-cognition -a codex`. Or copy the skill folder (skills/self-improving-cognition in LeoYeAI/openclaw-master-skills) into .agents/skills/self-improving-cognition in your project. Codex loads it when a task matches its description.

Can I use Self Improving Cognition 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 LeoYeAI/openclaw-master-skills --skill self-improving-cognition -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/self-improving-cognition, .gemini/skills/self-improving-cognition, .github/skills/self-improving-cognition and .opencode/skills/self-improving-cognition in your project.

What does Self Improving Cognition need to run?

Going by SKILL.md and its folder, Self Improving Cognition needs a shell for the scripts in its folder. Our summary lists: A Bash shell.

Does Self Improving Cognition 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 Self Improving Cognition 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Self Improving Cognition use?

Self Improving Cognition is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Self Improving Cognition use?

About 4.3k tokens (SKILL.md is roughly 17k 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 Self Improving Cognition?

Skills that share tags, products or a category with Self Improving Cognition: Deep Think Maximum Cognitive Effort Protocol Mq8kvw92 (nexu-io/open-design, 100k stars), Vc Problem Solving (withkynam/vibecode-pro-max-kit, 1.1k stars), Is This A Problem (anthropics/claude-for-legal, 9.6k stars) and First Principles Thinking (mindfold-ai/Trellis, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Self Improving Cognition?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,160 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.