Agent skill

thoroughness-scoring

Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.

Rohit Ghumare73,165★ · +3,601/wk · 3 repos on radarProfile →
claude-codecodexcursor
Install
npx skills add rohitg00/pro-workflow --skill thoroughness-scoring --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/thoroughness-scoring/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,760 · +95 this week
Language: JavaScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Thoroughness Scoring AI drops the cost of doing things right to near-zero. Stop picking the quick hack when the thorough option takes the same wall-clock time with AI assistance. ## The Rating Scale Every option gets a Thoroughness score (T:X/10): | Score | What It Means | |-------|---------------| | T:10 | All edge cases handled, full test coverage, docs updated, error messages helpful | | T:9

More from pro-workflow
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About this skill
What does the thoroughness-scoring skill do?

Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.

How do I install it?

Run `npx skills add rohitg00/pro-workflow --skill thoroughness-scoring --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From rohitg00/pro-workflow, a repository with 2,760 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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