Spec Score MCP

Score your specs before Claude builds from them.

A balanced spec produces balanced code. An unbalanced spec produces creative fiction.

The problem

When your spec is detailed on some axes but vague on others, Claude doesn't ask for clarification — it fills in the blanks. The result compiles, the tests pass, but it's not what you meant.

This tool catches that before you start building. It scores your spec on 4 axes, tells you which one is weakest, and gives you a concrete tip to fix it.

4 axes

Axis	Question it answers
completeness	Can Claude understand the full scope of what to build?
clarity	Is there only one way to interpret this spec?
constraints	Does Claude know what NOT to build?
specificity	Are there concrete, testable details?

Each axis scores 0.0 to 1.0. The balance score measures how evenly the 4 axes are covered.

Balance matters more than individual scores. A spec scoring 0.50 on all 4 axes (balance: 0.97) will produce better output than one scoring 0.95 / 0.95 / 0.20 / 0.90 (balance: 0.58). Why? That one weak axis — constraints at 0.20 — is exactly where Claude will improvise. You described what to build in detail, but forgot to say what's out of scope. So Claude builds everything you asked for, plus features you didn't.

On the radar chart: an even diamond beats a sharp spike.

Verdicts

Verdict	What it means
SHIP IT	Spec is ready — Claude knows what to build and what not to
ALMOST	One axis needs a small fix before you start
DRAFT	Multiple axes need work, but the structure is there
VAGUE	Well-organized but too abstract to act on
UNBOUNDED	Clear goal but no boundaries — Claude will over-build
OVER-CONSTRAINED	Lots of rules but unclear what the actual goal is
SKETCH	Starting point — needs detail on most axes

Not SHIP IT yet? The tool tells you which axis is weakest and what to add. Fix that axis, re-score, repeat. Most specs reach SHIP IT in 2-3 rounds.

Install

npm i -g spec-score-mcp
claude mcp add spec-score -- npx spec-score-mcp

That's it. The 3 tools are now available in every Claude Code session.

Usage

Slash commands

Clone this repo to get the built-in slash commands:

/project:scan my-feature-spec.md

Reads the file, scores it, and writes a my-feature-spec.md.scored.md with scores, verdict, tip, and a radar chart.

/project:compare blueprint.md implementation.md

Scores both files and writes a compared.scored.md with side-by-side radar charts.

Direct tool use

The 3 MCP tools work in any Claude Code conversation:

Tool	What it does
spec_score	Scores a spec on 4 axes, returns balance score and verdict
spec_visualize	Generates an SVG radar chart from scores
spec_compare	Side-by-side comparison of two scored specs

Ask Claude: "Score this spec", "Show me the radar chart", or "Compare these two specs".

Example: from UNBOUNDED to SHIP IT

This tool scoring its own spec — four rounds, each fixing the weakest axis:

Round 1: the idea

Build a spec scoring tool

UNBOUNDED  0.12  Tip: What does 'scoring' mean? What axes? What output?

One axis is high (clarity — the goal is clear), everything else is near zero. Claude would build... anything. A web app? A CLI? A VS Code extension? No way to know.

Round 2: add context

Build an MCP server that scores specs on 4 axes: completeness, clarity, constraints, specificity. Each axis is 0.0-1.0. Returns a balance score and verdict.

ALMOST  0.67  Tip: What are the verdicts? What does the tool NOT do?

Now Claude knows what to build. But constraints are still weak — it might add auto-fixing, CI integration, a database.

Round 3: add boundaries

Three tools: spec_score, spec_visualize, spec_compare. Non-goals: no auto-fixing, no CI integration, no storage.

SHIP IT  0.84  Tip: Add testable criteria — what balance maps to which verdict?

Crossed the threshold. Claude now knows what to build AND what not to build. Specificity is still the weakest axis.

Round 4: add testable details

Balance = 1 - sqrt(variance)/mean. SHIP IT > 0.75, ALMOST > 0.60, plus pattern-based verdicts. Node.js, MCP SDK, stdio transport.

SHIP IT  0.95  Spec is ready for implementation.

Four rounds: 0.12 → 0.67 → 0.84 → 0.95. Each round fixed exactly one thing.

The math

1. Claude scores each axis (0.0 - 1.0)
2. Normalize the vector: v / ||v||
3. Balance: 1 - sqrt(variance) / mean
4. Verdict: balance threshold + axis pattern matching

The scoring intelligence comes from Claude, not from the algorithm. The algorithm only measures balance.

Also available as

Platform	Link
npm	npx spec-score-mcp
MCP Registry	io.github.openpoem/spec-score-mcp
ChatGPT	Custom GPT in ChatGPT Store
Smithery	MCP server directory
Glama	MCP server directory
HTTP API	spec-score-mcp.vercel.app

The HTTP API powers the Custom GPT and can be used standalone:

Endpoint	What it does
POST /api/score	Score a spec → JSON with balance, verdict, axes
POST /api/visualize	Score a spec → SVG radar chart
POST /api/compare	Compare two specs → side-by-side SVG

Project structure

src/
  mcp.ts        # MCP server (3 tools)
  score.ts      # Scoring engine
  visualize.ts  # SVG radar charts
api/
  score.ts      # HTTP API — JSON scoring
  visualize.ts  # HTTP API — SVG radar chart
  compare.ts    # HTTP API — side-by-side comparison
  index.ts      # Landing page
  privacy.ts    # Privacy policy
  openapi.json  # OpenAPI spec (used by ChatGPT Actions)
.claude/
  commands/
    scan.md     # /project:scan command
    compare.md  # /project:compare command

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OpenPoem — spec-score-mcp

MIT License.

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