Meta Pattern Recognition
- 273 installs
- 733 repo stars
- Updated October 14, 2025
- obra/superpowers-skills
Turn a spec or requirements into bite-sized implementation tasks before any code is written.
About
meta-pattern recognition — Writing Plans converts specs into engineer-ready implementation plans—file structure, checkbox tasks, failing-test-first steps, and commit boundaries—assuming zero codebase context. It pairs with executing-plans and subagent-driven-development for delivery. Solo builders use it after brainstorming when a feature needs disciplined execution.
- Bite-sized TDD-friendly tasks with explicit file paths and verification commands.
- Requires plan header with goal, architecture, and required sub-skills.
- Scope check to split multi-subsystem specs into separate plans.
Meta Pattern Recognition by the numbers
- 273 all-time installs (skills.sh)
- +24 installs in the week ending Jul 26, 2026 (Skillselion tracking)
- Ranked #926 of 3,301 Productivity & Planning skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 273 |
|---|---|
| repo stars | ★ 733 |
| Security audit | 3 / 3 scanners passed |
| Last updated | October 14, 2025 |
| Repository | obra/superpowers-skills ↗ |
What it does
Turn a spec or requirements into bite-sized implementation tasks before any code is written.
Files
Meta-Pattern Recognition
Overview
When the same pattern appears in 3+ domains, it's probably a universal principle worth extracting.
Core principle: Find patterns in how patterns emerge.
Quick Reference
| Pattern Appears In | Abstract Form | Where Else? |
|---|---|---|
| CPU/DB/HTTP/DNS caching | Store frequently-accessed data closer | LLM prompt caching, CDN |
| Layering (network/storage/compute) | Separate concerns into abstraction levels | Architecture, organization |
| Queuing (message/task/request) | Decouple producer from consumer with buffer | Event systems, async processing |
| Pooling (connection/thread/object) | Reuse expensive resources | Memory management, resource governance |
Process
1. Spot repetition - See same shape in 3+ places 2. Extract abstract form - Describe independent of any domain 3. Identify variations - How does it adapt per domain? 4. Check applicability - Where else might this help?
Example
Pattern spotted: Rate limiting in API throttling, traffic shaping, circuit breakers, admission control
Abstract form: Bound resource consumption to prevent exhaustion
Variation points: What resource, what limit, what happens when exceeded
New application: LLM token budgets (same pattern - prevent context window exhaustion)
Red Flags You're Missing Meta-Patterns
- "This problem is unique" (probably not)
- Multiple teams independently solving "different" problems identically
- Reinventing wheels across domains
- "Haven't we done something like this?" (yes, find it)
Remember
- 3+ domains = likely universal
- Abstract form reveals new applications
- Variations show adaptation points
- Universal patterns are battle-tested
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Is Meta Pattern Recognition safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.