strategic-mindset-principles
Skill2 starsChanged 8 months agoNo licenceView on GitHub
当需要为长期战略决策（如职业发展、商业竞争）建立底层认知和心态基础时
In this repository48 other files it gives its agents.
- abcd-modelSkill
- advantage-compounding-in-networksSkill
- adversity-to-opportunity-frameworkSkill
- ancestor-wisdom-inheritanceSkill
- anti-fragility-gene-cultivationSkill
- apical-dominance-positioningSkill
- bidirectional-mentorship-modelSkill
- burden-shifting-identificationSkill
- concise-communication-principleSkill
- constraint-inertiaSkill
- contextual-insight-extrapolationSkill
- cultivate-professional-aweSkill
- derepSkill
- distinguish-productive-playSkill
- dual-perspective-decision-filterSkill
- dual-role-mindset-integrationSkill
- embodied-cognition-learningSkill
- emomemSkill
- external-leverage-amplificationSkill
- find-space-through-external-perspectiveSkill
- foundational-skill-isolationSkill
- human-machine-collaboration-mindsetSkill
- idea-integration-before-creationSkill
- identify-singularity-trendSkill
- identity-leverage-frameworkSkill
- information-network-as-acceleratorSkill
- information-source-classification-frameworkSkill
- interest-first-communicationSkill
- late-mover-advantage-strategySkill
- llm-wikiSkill
- minimal-resistance-pathSkill
- narrative-to-roadmap-translationSkill
- on-demand-skill-managementSkill
- optimal-return-focus-strategySkill
- personal-pe-valuationSkill
- premise-identification-for-effective-actionSkill
- priority-invisible-layer-problem-solvingSkill
- process-over-inspirationSkill
- product-scene-transformationSkill
- quantity-over-initial-qualitySkill
- raw-information-extractionSkill
- risk-hedging-by-counterbalanceSkill
- role-adaptation-through-artistic-observationSkill
- self-evaluation-via-reversed-criteriaSkill
- superconductor-thinkingSkill
- thick-and-flexible-evaluationSkill
- threshold-crossing-strategySkill
- write-code-anlsSkill
The file
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.