thinking-lindy-effect
Use when longevity of a non-perishable option matters.
Skill by tjboudreaux
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/tjboudreaux-thinking-lindy-effect
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/thinking-lindy-effect
What's inside
- Skill name
thinking-lindy-effect- Description
- 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.
- License
- MIT
- Instructions
- 46 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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 ```text 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.
From tjboudreaux/cc-thinking-skills, MIT.
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Signals
- Stars
- 1,668
- Forks
- 185
- Open issues
- 2
- Last commit (this folder)
- Jul 17, 2026 (3 months ago)
- Last release
- Aug 4, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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thinking-lindy-effect skill. Agent Mart. https://agentmart.dev/skills/tjboudreaux-thinking-lindy-effect (last updated 2026-10-24)