find-big-wins

Propose ranked structural bets that eliminate classes of engineering work.

3|3|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/PioneerAIAcademy/cowork-genealogy --skill find-big-wins-pioneeraiacademy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: find-big-wins
Source: https://github.com/PioneerAIAcademy/cowork-genealogy/tree/main/.claude/skills/find-big-wins
Command: npx skills add https://github.com/PioneerAIAcademy/cowork-genealogy --skill find-big-wins-pioneeraiacademy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Issue boards and audit passes only produce incremental fixes, so teams keep hill-climbing the current design without ever questioning its shape. This Skill runs a weekly structural review that reads the board as a symptom, mines the repo's measured evidence, and sweeps outside the repo for lifted platform constraints, producing ranked proposals for changes that remove constraints or eliminate whole classes of work. ## Core Features & Use Cases - Three-layer evidence sweep: Reads cluster labels and recurring issue patterns on the board, internal measured evidence (e2e corpus, latency reports, judge audits, the nothing-checks register, ADRs), and external sources (platform changelogs, current practice, published work) via WebSearch and WebFetch. - Subtraction hunting: Actively searches for mechanisms to retire, guarantees to drop, warn-only checks nobody reads, and lanes to delete, not just additions. - Ledger-backed memory: Carries forward, re-ranks, and records verdicts (accepted, deferred, set aside, rejected) in an ADR ledger so researched-and-rejected ideas are never re-proposed. - Use Case: After the weekly board audit, run the Skill to get a ranked list of structural proposals, each with a pre-verified claim, the constraint it removes, observable outcomes, and a cheapest one-day probe that could kill it. ## Quick Start Run /find-big-wins after the weekly board audit to propose ranked structural bets for the lead to review.

Frequently Asked Questions about find-big-wins

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find structural improvements instead of incremental fixes?▼

Run this Skill after the weekly board audit. It reads cluster labels, recurring issue phrases, and reopened issues as symptoms, then mines the e2e corpus, latency reports, and ADRs for measured evidence, producing ranked proposals that each name a constraint removed or a class of work eliminated.

What makes a proposal qualify as a structural bet?▼

A proposal must name both the constraint it removes or class of work it eliminates, and what would be observably different if it worked. Ideas that name neither are increments and get filed as normal issues instead. Subtractions like retiring a mechanism qualify exactly like additions.

Does this Skill write code or create pull requests?▼

No. It only proposes; the lead decides each idea individually. Its only write access is appending rows to the structural bets ledger in ADR-0010. Approved ideas become senior-labelled issues in stage 3, and the assignee writes the plan and implementation.

How does the ledger prevent re-proposing rejected ideas?▼

Every proposal gets a ledger row with a verdict: accepted, deferred, set aside, or rejected. A rejected row means the idea was researched and refuted, which bars re-proposal. Set-aside rows can be re-proposed under a higher burden, naming what changed since the refutation.

Why does the Skill search outside the repository?▼

Internal evidence only shows where the current design's walls are; it cannot reveal constraints that upstream platforms have lifted. The Skill checks ADR decisions older than a month against current Claude Code, Cowork, and Agent SDK capabilities, citing changelogs or release notes with dates.

What happens if a run finds no qualifying ideas?▼

A zero-result run is considered successful. The Skill reports what was swept and which evidence layer came back empty, since there is no target count and padding the list with filler proposals would waste the lead's limited weekly review capacity.