Skip to content
FunCoding

Search

Search docs, Skills and MCP

thinking-lindy-effect

Use when longevity of a non-perishable option matters. Treat survival duration as a remaining-life prior, then check domain drift before favoring the proven.

AI 与智能体1.6kskills/thinking-lindy-effect/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/tjboudreaux/cc-thinking-skills/thinking-lindy-effect/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Lindy Effect

For non-perishable ideas, technologies, and practices, expected remaining life scales with current survival age. Prefer proven survivors unless the new option clears a burden of proof or the domain has drifted.

When to Use

  • Choosing languages, frameworks, databases, protocols, patterns, or dependencies where long-term survival matters.
  • Skill or architecture bets whose value depends on lasting relevance.
  • Ranking options when ages differ materially and the choice outlives a short experiment.

When NOT to Use

  • Perishable targets: specific SaaS vendors, hardware, fashion, or products that can shut down regardless of concept age.
  • Active paradigm discontinuity where age in the old regime is weak evidence.
  • Throwaway work where longevity is irrelevant — optimize for fit and speed.
  • Treating "older" as "optimal for a new requirement"; survival predicts further survival, not best fit.

Procedure

  1. Confirm non-perishable scope. Concept/tech/practice continues; vendor/device → score fit/risk only and stop.
  2. Record survival age. First significant production use and current age (ecosystem-relative if the ecosystem is young).
  3. Form the Lindy prior. Expected remaining life ≈ current age; mark confidence from age and continued active use.
  4. Run domain-drift checks. Problem class changed? Paradigm shift invalidating old assumptions? New option uniquely closes a real present gap?
  5. Assign burden of proof. Default to the older adequate option. Accept newer only for a stated necessary advantage the Lindy option cannot meet at acceptable cost.
  6. Decide with residual risk. Pick primary; note impact if the prior is wrong and any fallback.

Stop condition: Primary chosen with age prior, drift check, and why new did or did not meet burden of proof.

Output

Options: <name, age, Lindy prior>
Drift: stable | discontinuous — <note>
Burden: on new | waived because <gap>
Decision: <primary>
Rejected: <one line each>
If Lindy wrong: <impact + fallback>

Verification

  • Falsify if age was used without non-perishable scope, or a paradigm shift was ignored.
  • Falsify if a new option was rejected solely for youth despite a documented necessary gap.
  • Over-application guard: skip throwaway prototypes and perishable vendor bets where fit and exit cost dominate.

Similar Skills

brand-guidelines
anthropics/skills180k

brand-guidelines

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

AI & agents

internal-comms
anthropics/skills180k

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

AI & agents

template-skill
anthropics/skills180k

template-skill

Replace with description of the skill and when Claude should use it.

AI & agents

mcp-builder
anthropics/skills180k

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

AI & agents

algorithmic-art
anthropics/skills180k

algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

AI & agents

academy-guide
anthropics/skills180k

academy-guide

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

AI & agents