Money Strategy
iamzifei/show-me-the-money
Create comprehensive business strategy with premise deconstruction, business model stress test, pricing, go-to-market plan, and competitive positioning.
World-Class Adaptability & Learning Playbook. An agent skill from LeoYeAI/openclaw-master-skills.
Install Adaptive Learning Playbook
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbook --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/adaptive-learning-playbook .claude/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.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/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .claude/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbookType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbook --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/adaptive-learning-playbook .agents/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .agents/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbook --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/adaptive-learning-playbook .cursor/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .cursor/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/adaptive-learning-playbook--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbook --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/adaptive-learning-playbook .gemini/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .gemini/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbookInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/adaptive-learning-playbook .github/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .github/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills adaptive-learning-playbook --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/adaptive-learning-playbook .opencode/skills/adaptive-learning-playbook && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "adaptive-learning-playbook" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/adaptive-learning-playbook into .opencode/skills/adaptive-learning-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adaptive-learning-playbook", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
adaptive-learning-playbook- GitHub stars
- 2.2k
- Token cost
- ~4k tokens
- SKILL.md length
- 1,633 words
- Files
- 4 (incl. references)
- Skills in repo
- 1,235
- Repo updated
- First seen
- Licence
- MIT
At a glance
World-Class Adaptability & Learning Playbook. An agent skill from LeoYeAI/openclaw-master-skills.
- Works in 10 steps: The Adaptability Capability Stack… → Market Trend Awareness → Organisational Agility → …
- : market trend awareness
- SKILL.md covers Core Philosophy, 1. The Adaptability Capability…, 2. Market Trend Awareness and 3. Organisational Agility, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Adaptive Learning Playbook is an agent skill from LeoYeAI/openclaw-master-skills. World-Class Adaptability & Learning Playbook. Use for: market trend awareness, horizon scanning, PESTLE analysis, organisational agility, Kaizen, PDCA cycles, 5S, lean operations, experimentation culture, hypothesis-driven development, A/B testing, MVP design, knowledge management, decision logs, ADRs, after-action reviews, competitive intelligence, SWOT, Porter's Five Forces, battlecards, pivoting strategy, lean startup, business model canvas, signal detection, scenario planning, learning velocity, value stream…
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `README.md`, `_meta.json` and `references/extended-playbook.md`).
It sits in Marketing & SEO, covering Startup and business strategy, Competitor analysis and A/B testing. 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
- : market trend awareness
- Horizon scanning
- PESTLE analysis
- Organisational agility
Example prompts
- “/adaptive-learning-playbook”
Workflow steps
10 steps, taken from the step headings in SKILL.md.
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
No scripts in the folder and no shell commands in SKILL.md.
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
Adaptive Learning Playbook loads about 4k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 229 tokens; SKILL.md has 1,633 words of instructions outside code blocks.
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 LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,633 words, ~4,039 tokens.
Download SKILL.mdSave it as
.claude/skills/adaptive-learning-playbook/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- adaptive-learning-playbook
- description
- World-Class Adaptability & Learning Playbook. Use for: market trend awareness, horizon scanning, PESTLE analysis, organisational agility, Kaizen, PDCA cycles, 5S, lean operations, experimentation culture, hypothesis-driven development, A/B testing, MVP design, knowledge management, decision logs, ADRs, after-action reviews, competitive intelligence, SWOT, Porter's Five Forces, battlecards, pivoting strategy, lean startup, business model canvas, signal detection, scenario planning, learning velocity, value stream mapping, Gemba walks. Trigger when discussing ANY organisational learning, strategic adaptability, continuous improvement, competitive analysis, experimentation, knowledge systems, or pivot/persevere decisions. Also for startup strategy around product-market fit or validated learning. If it touches learning faster, adapting better, or competing smarter — use this skill.
World-Class Adaptability & Learning Playbook
You are operating as a world-class strategic advisor on organisational adaptability. Every piece of advice must meet the standard of elite startup and enterprise strategy — grounded in research, practically actionable, and calibrated for resource-constrained, multi-jurisdictional technology companies. No generic consulting platitudes. No theory without application.
Core Philosophy
CONTINUOUS ADAPTATION > RESILIENCE > AGILITY
Resilience survives disruption. Agility responds to it.
Continuous adaptation creates the future rather than preparing for it.Seven interlocking capabilities. One operating system. Daily compounding.
1. The Adaptability Capability Stack (Priority Order)
| # | Capability | Core Question |
|---|---|---|
| 1 | Market Trend Awareness | What is changing and what does it mean for us? |
| 2 | Organisational Agility | How fast can we sense change and reorganise? |
| 3 | Continuous Improvement (Kaizen) | Are we measurably better every single day? |
| 4 | Experimentation Culture | Do we test assumptions before committing resources? |
| 5 | Knowledge Management | Can the right person access the right knowledge at the right time? |
| 6 | Competitive Intelligence | Do we understand the landscape well enough to act, not just observe? |
| 7 | Pivoting Ability | Can we redirect strategy without losing momentum or identity? |
2. Market Trend Awareness
Signal Categories
| Signal Type | Confidence | Lead Time | Examples |
|---|---|---|---|
| Strong | High | Low | Published regulations, competitor launches, central bank decisions |
| Emerging | Medium | Medium | Patent filings, VC funding patterns, draft legislation, academic breakthroughs |
| Weak | Low | High | Social sentiment shifts, niche community discussions, adjacent-industry innovations |
Collection Architecture
- Regulatory Radar: Monitor FCA, Bank of Zambia, Estonian EFSA, EU Digital Finance Package
- Technology Watch: GitHub trending, Hacker News, ArXiv, ProductHunt — focus AI/ML, blockchain, embedded finance, real-time payments
- Customer Signals: NPS trends, support ticket themes, feature requests, churn reasons, social listening
- Macro Indicators: Currency volatility, inflation, mobile money adoption, smartphone penetration by market
Analysis Methods
| Method | When | Output |
|---|---|---|
| PESTLE | Quarterly | Risk/opportunity matrix by jurisdiction |
| Horizon Scanning | Monthly | Three-horizon map (now, next, future) |
| Scenario Planning | Bi-annually | 2–4 scenario narratives with strategic implications |
| Jobs-to-be-Done | New market entry | Unmet need map linked to product roadmap |
| Trend Convergence | Weak signal clusters | Innovation thesis for experimentation |
Cadence
- Weekly — 30-min trend digest (top 5–10 signals)
- Monthly — 60-min trend review (debate significance, update risk matrix)
- Quarterly — Full PESTLE + Horizon Scan → feeds OKR planning
- Annual — Deep scenario planning → multi-year strategic hedging
3. Organisational Agility
Three Dimensions (SAFe Model)
Dimension 1 — Lean-Thinking People & Agile Teams
- Cross-functional by default. No single points of failure.
- Push decisions to people closest to the information. Use the two-way door framework: if reversible, decide fast.
- Celebrate learning from failure. Normalise "I was wrong" as intellectual honesty.
Dimension 2 — Lean Business Operations
- Value Stream Mapping: Map end-to-end from customer request to value delivery. Find bottlenecks, handoffs, waste.
- Flow Metrics: Cycle time, lead time, throughput, WIP limits. Optimise for flow, not utilisation.
- Eliminate Muda: Overproduction, waiting, transport, overprocessing, inventory, motion, defects.
Dimension 3 — Strategy Agility
- Rolling Strategy Cycles: Quarterly strategy sprints > annual monoliths.
- Portfolio Thinking: Core 70% / Adjacent 20% / Transformational 10%.
- Strategic Optionality: Stage-gate funding tied to validated learning milestones.
Continuous Adaptation Model (WEF)
| Domain | Stability (Continuity) | Transformation (Change) |
|---|---|---|
| Operations | Standardised processes, SLAs, quality controls | Modular architecture, API-first, cloud-native |
| Organisation | Clear roles, shared values, communication cadence | Talent rotation, AARs, bottom-up idea flow |
| Finance | Cash reserves, working capital, compliance | Variable cost structures, stage-gate funding, optionality |
4. Continuous Improvement (Kaizen)
Core Principles
- Standardise then improve — No Kaizen without a standard. Establish → measure → improve → re-standardise.
- Go to the Gemba — Observe work where it happens. See problems in context.
- Visual management — Performance, problems, priorities visible at a glance.
- Eliminate waste — Target muda (waste), muri (overburden), mura (unevenness).
- Respect for people — Those closest to the work have the best insights.
PDCA Cycle
| Phase | Activities |
|---|---|
| PLAN | Identify problem. Define goals. Analyse current state. Develop hypothesis. Set success metrics. |
| DO | Implement on small scale / pilot. Document. Collect data. |
| CHECK | Compare results vs expectations. Root-cause any gaps. |
| ACT | If success → standardise. If not → revise hypothesis, re-cycle. Share learnings. |
Two Modes
- Everyday Kaizen: Daily standups, team boards, suggestion systems (teian), leader standard work. Aligns with CI/CD.
- Event Kaizen (Blitz): 3–5 day time-boxed cross-functional sprints on a defined bottleneck. Step-change improvements.
5S for Tech/Startup Context
| 5S | English | Application |
|---|---|---|
| Seiri | Sort | Remove unused code, deprecated APIs, stale docs, inactive repos |
| Seiton | Set in Order | Organise repos, label issues, standardise naming conventions |
| Seiso | Shine | Code reviews, dependency updates, security scans, DB cleanup |
| Seiketsu | Standardise | Linting rules, PR templates, deployment checklists, runbooks |
| Shitsuke | Sustain | Automated enforcement, retrospectives, continuous training |
5. Experimentation Culture
The Scientific Approach
Experimentation discipline matters as much as volume. Research shows programmes generating frequent early pivots may impede learning. Run the right experiments, learn the most from each.
Experimentation Lifecycle
- Hypothesise — "We believe [segment] will [action] because [reason]."
- Design — Minimum viable experiment (MVE). Define success criteria BEFORE running.
- Execute — Resist changing variables mid-test. Collect data rigorously.
- Analyse — Results vs pre-defined criteria. Signal vs noise.
- Decide — Persevere / Pivot / Kill.
- Codify — Document learning regardless of outcome. Update knowledge base.
Design Principles
- One variable at a time. Multi-variable = hard to learn from.
- Pre-register success criteria. Prevents post-hoc rationalisation.
- Time-box ruthlessly. Deadline for every experiment.
- Small batch, fast feedback. Many small > few large.
- Psychological safety. Reward experiment quality, not outcome.
Experiment Types
| Type | Speed | Fidelity | Best For |
|---|---|---|---|
| Smoke Test | Hours–Days | Low | Demand validation |
| Concierge MVP | Days–Weeks | Medium | Value proposition testing |
| A/B Test | Weeks | High | Conversion optimisation |
| Wizard of Oz | Days–Weeks | Medium-High | Complex feature feasibility |
| Pilot Launch | Weeks–Months | High | Market readiness |
| Hackathon Sprint | Days | Low-Medium | Technical feasibility, ideation |
6. Knowledge Management
Knowledge Types
| Type | Description | Capture Method |
|---|---|---|
| Explicit | Documented, codified. Code, SOPs, runbooks. | Notion, Git repos, playbooks, decision logs |
| Tacit | Experiential, intuitive. Why decisions were made. | Pair programming, mentorship, AARs, recorded walkthroughs |
| Embedded | Baked into systems. CI/CD pipelines, linting rules. | ADRs, automated tests, process templates |
Four-Layer Architecture
- Capture — Decision Logs, ADRs, After-Action Reviews (AARs), Experiment Library
- Organise — Single source of truth per knowledge type. Consistent tagging (domain, jurisdiction, status). SKILL.md architecture for AI workflows.
- Share — Push (digests, Slack alerts, onboarding). Pull (searchable wiki, AI Q&A). Social (pairing, knowledge sessions, rotations).
- Apply — Templates/checklists, AI augmentation (LLMs surfacing context), feedback loops on knowledge usage.
Show full SKILL.md (649 more words)Show less
Decision Log Template
## Decision: [Title]
- Date: YYYY-MM-DD
- Status: Proposed / Accepted / Superseded
- Context: What situation prompted this decision?
- Options Considered: [List with pros/cons]
- Decision: What was decided?
- Rationale: Why?
- Expected Outcome: What do we expect to happen?
- Review Date: When will we assess the result?ADR Template
## ADR-NNN: [Title]
- Status: Proposed / Accepted / Deprecated / Superseded
- Context: Technical context and problem statement
- Decision: The architectural decision made
- Consequences: Positive, negative, and risks7. Competitive Intelligence
The CI Cycle
- Define — What decision will this inform? Be specific.
- Gather — Websites, press releases, social, patents, job postings, regulatory filings, frontline sales intel.
- Analyse — SWOT, Porter's Five Forces, positioning maps, gap analysis.
- Implement — Battlecards (sales), strategic briefs (leadership), feature comparisons (product).
Intelligence Layers
| Layer | Track | Sources |
|---|---|---|
| Product | Features, pricing, UX, roadmap, APIs | Product pages, changelogs, app stores, dev docs |
| Go-to-Market | Positioning, messaging, campaigns, partnerships | Websites, social, press releases, ad libraries |
| Organisational | Hiring, team growth, leadership changes | LinkedIn, job boards, Companies House |
| Financial | Funding, revenue signals, M&A | Crunchbase, PitchBook, regulatory filings |
| Strategic | Vision shifts, expansion, IP filings | Earnings calls, blogs, patent DBs, conferences |
Competitor Categories
- Direct: Same product → same customer → same market
- Indirect: Different product → same problem
- Future: Adjacent capabilities or funding that could enter your market
- Substitutes: Entirely different approaches that could make your category irrelevant
CI Cadence
- Real-time: Automated alerts for pricing changes, launches, funding
- Weekly: 5-min digest of key movements + implications
- Monthly: Deep analysis, update positioning map + battlecards
- Quarterly: Comprehensive landscape review → strategic planning input
Budget CI Stack
Google Alerts (free) + Visualping (~£13/mo) + Similarweb free + LinkedIn + Crunchbase + Claude for synthesis
8. Pivoting Ability
Pivot Types
| Type | Description |
|---|---|
| Customer Segment | Same product, different target customer |
| Value Proposition | Same customer, different value (founders resist this most) |
| Channel | Different distribution/sales mechanism |
| Revenue Model | Different monetisation (subscription → transaction, B2C → B2B) |
| Technology | Same value prop, different stack/platform |
| Platform | Application → platform others build upon |
| Business Architecture | High-margin/low-volume ↔ Low-margin/high-volume |
| Market/Geography | Same product → different jurisdiction |
Pivot Signals
- Persistent failure to achieve product-market fit despite iterations
- CAC unsustainably high and not improving with optimisation
- Market moving against your value proposition
- New tech/regulation fundamentally changes landscape
- Strongest traction from unexpected segment/use case
- Team morale declining — feels like pushing a boulder uphill
Pivot Decision Framework
- Acknowledge evidence — Quantitative (metrics, experiments, financials) + qualitative (feedback, sentiment, advisor input)
- Separate identity from strategy — Experience, mentoring, and team size enable pivoting. Seek external perspective.
- Define what stays vs changes — A pivot preserves a kernel of value while changing one element.
- Design the experiment — MVE to validate new direction BEFORE full commitment.
- Communicate with radical transparency — Tell investors, team, stakeholders: what you learned, what's changing, why.
- Execute with speed — Half-pivots (split between old and new) are the most dangerous state.
Pivot vs Persevere vs Kill
- Noise: Random short-term variation. Do not pivot.
- Signal: Persistent validated evidence current direction is wrong. Consider pivot.
- Kill: Repeated pivots fail, hypothesis space exhausted. Preserve capital, redeploy.
9. Measurement Framework
Adaptability Scorecard (Quarterly)
| Capability | Key Metrics | Cadence |
|---|---|---|
| Market Trends | Signals detected/mo, time-to-insight, actionable signal ratio | Weekly/Monthly |
| Org Agility | Decision cycle time, reorg speed, cross-functional collab index | Monthly/Quarterly |
| Kaizen | Improvements/mo, cycle time reduction, defect rate | Weekly/Monthly |
| Experimentation | Experiments/mo, validation rate, time to first learning | Weekly/Monthly |
| Knowledge Mgmt | Articles created/updated, search satisfaction, onboarding time | Monthly |
| Competitive Intel | CI coverage, competitive response time, win/loss completion | Weekly/Monthly |
| Pivoting | Signal-to-decision time, pivot success rate, resource reallocation speed | Quarterly |
Meta-Metric: Learning Velocity
The single most important metric: validated hypotheses per unit time, weighted by strategic importance. How fast the organisation converts uncertainty into knowledge.
10. Quick-Start: 90-Day Implementation
Days 1–30 (Foundation):
- Weekly trend digest + signal collection
- Decision log for all significant decisions
- Top 5 competitor monitoring
- First PDCA retrospective
- SKILL.md knowledge architecture
Days 31–60 (Activation):
- First structured experiment (pre-registered criteria)
- Stakeholder knowledge gap interviews
- First competitive battlecard
- Visual management (Kanban/equivalent)
- First Kaizen event on a process bottleneck
Days 61–90 (Optimisation):
- Refine all cadences (daily/weekly/monthly/quarterly)
- Baseline learning velocity + improvement targets
- First quarterly PESTLE + Horizon Scan
- Assess pivot signals against framework
- First Adaptability Scorecard
For extended content — detailed tool comparisons, case studies (Amazon/AWS, Netflix, Toyota,
Ford, NSF I-Corps), advanced frameworks, and templates — consult:
→ references/extended-playbook.md
Remember: Adaptability is not a department. It is an operating system — daily habits, decision architectures, and cultural norms that compound over time. Learn faster than the market changes. BUILD – DOCUMENT – RESEARCH – LEARN – REPEAT.
© 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 3 other files (references) in skills/adaptive-learning-playbook of LeoYeAI/openclaw-master-skills.
- SKILL.md
- README.md
- _meta.json
- references/extended-playbook.md
Open the folder on GitHubat commit e5199b5
Compare with similar skills
Adaptive Learning Playbook 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Adaptive Learning Playbook this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~4k | Automated safety check: Pass | MIT | |
| Money Strategyiamzifei/show-me-the-money | 1k | — | ~7k | Automated safety check: Pass | Custom licence | |
| Startup Designferdinandobons/startup-skill | 1.2k | — | ~8.1k | Automated safety check: Pass | MIT | |
| Market Research Analysismanojbajaj95/claude-gtm-plugin | 105 | — | ~2.6k | Automated safety check: Pass | MIT | |
| Competitive Teardownalirezarezvani/claude-skills | 28k | 1 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Cashclaw Competitor Analyzerertugrulakben/cashclaw | 303 | — | ~2.7k | Automated safety check: Pass | MIT |
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Related
Questions about Adaptive Learning Playbook
What does Adaptive Learning Playbook do?
World-Class Adaptability & Learning Playbook. An agent skill from LeoYeAI/openclaw-master-skills. Adaptive Learning Playbook is an agent skill from LeoYeAI/openclaw-master-skills. World-Class Adaptability & Learning Playbook.
When should I use Adaptive Learning Playbook?
Adaptive Learning Playbook fits situations like: : market trend awareness; horizon scanning; PESTLE analysis; organisational agility.
How do I install Adaptive Learning Playbook in Claude Code?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a claude-code`. Or copy the skill folder (skills/adaptive-learning-playbook in LeoYeAI/openclaw-master-skills) into .claude/skills/adaptive-learning-playbook in your project. Claude Code loads it when a task matches its description.
How do I install Adaptive Learning Playbook in Codex?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill adaptive-learning-playbook -a codex`. Or copy the skill folder (skills/adaptive-learning-playbook in LeoYeAI/openclaw-master-skills) into .agents/skills/adaptive-learning-playbook in your project. Codex loads it when a task matches its description.
Can I use Adaptive Learning Playbook 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 adaptive-learning-playbook -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adaptive-learning-playbook, .gemini/skills/adaptive-learning-playbook, .github/skills/adaptive-learning-playbook and .opencode/skills/adaptive-learning-playbook in your project.
What does Adaptive Learning Playbook need to run?
SKILL.md names no scripts, command-line tools or credentials: Adaptive Learning Playbook is instructions for the agent only.
Does Adaptive Learning Playbook 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 Adaptive Learning Playbook 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 Adaptive Learning Playbook use?
Adaptive Learning Playbook 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 Adaptive Learning Playbook use?
About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.
What are the alternatives to Adaptive Learning Playbook?
Skills that share tags, products or a category with Adaptive Learning Playbook: Money Strategy (iamzifei/show-me-the-money, 1k stars), Startup Design (ferdinandobons/startup-skill, 1.2k stars), Market Research Analysis (manojbajaj95/claude-gtm-plugin, 105 stars) and Competitive Teardown (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Adaptive Learning Playbook?
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 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.