thoroughness-scoring

Scores implementation options with a 1-10 thoroughness rating and recommends the higher-quality choice.

1|Updated May 6, 2026
One-click install
npx skills add https://github.com/surfingalien/FinSurfing --skill thoroughness-scoring-surfingalien
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: thoroughness-scoring
Source: https://github.com/surfingalien/FinSurfing/tree/main/.claude/skills/thoroughness-scoring
Command: npx skills add https://github.com/surfingalien/FinSurfing --skill thoroughness-scoring-surfingalien

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI assistance drops the cost of doing work properly to near-zero, yet developers still default to quick hacks that accumulate technical debt. This Skill forces every decision point to be scored on a Thoroughness Rating (T:1-10) so the higher-quality option is chosen whenever the AI-assisted effort delta is small. ## Core Features & Use Cases - Thoroughness Rating Scale: Scores every option from T:1 (untested copy-paste) to T:10 (full edge cases, tests, docs) with a defined rubric. - Structured Option Presentation: Re-states project, branch, and task context, then rates each option with manual vs AI-assisted effort estimates and a coverage delta. - Scope Classification: Distinguishes contained work (score and execute at T:8+) from unbounded work (break into independently shippable pieces before scoring). - Use Case: When adding rate limiting to an API endpoint, the Skill presents a full sliding-window Redis-backed limiter (T:9, ~20 min with AI) versus a basic in-memory counter (T:4, ~5 min), quantifies what the extra 15 minutes buys, and recommends the thorough option. ## Quick Start Ask the AI to score the implementation options for your current task using thoroughness scoring and recommend the highest-rated approach.

Frequently Asked Questions about thoroughness-scoring

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

FAQPage Schema
How do I decide between a quick hack and a thorough implementation?

Score each option on a Thoroughness Rating from T:1 to T:10, then compare the manual effort estimate against the AI-assisted estimate. When AI closes the effort gap, pick the T:8 or higher option since the marginal cost is near-zero.

What is a thoroughness rating scale for code quality?

It is a 1-10 scale where T:10 means all edge cases handled with full tests and docs, T:7 means happy path with basic tests, and T:1 means untested copy-paste code. Each option presented gets scored so trade-offs are explicit.

When should I not use thoroughness scoring?

Skip scoring for exploratory spikes, one-off throwaway scripts, debugging sessions, and learning exercises where iteration speed matters more than completeness. State explicitly that scoring was skipped so the choice is conscious.

How do I handle tasks that are too large to do thoroughly?

Classify the scope first: unbounded work like refactoring all error handling must be broken into contained pieces such as auditing patterns, defining a standard, and fixing one module at a time. Score each contained piece independently.

Why do quick hacks cost more in the long run?

Low-thoroughness options skip tests, persistence, error handling, and edge cases, creating technical debt that is repaid at roughly 10x cost later. The scoring format quantifies exactly what the higher-rated option adds for its small extra time.