About speccheck
speccheck audits caller-supplied spec requirements against issue, pull request, and code claims. It reports coverage, claim counts, dangling references, and a verdict without accessing a repository or network.
Key features
- 01Requirement coverage audit
- 02Issue, PR, and code claims
- 03Dangling claim detection
- 04Coverage counts and verdict
- 05Local CLI and validation
Use cases
- 01Check whether spec items have implementation claims
- 02Find claims linked to nonexistent requirement IDs
- 03Review coverage before a release
- 04Run a local spec audit from JSON
MCP support
Exposes the `check_spec_coverage` tool to MCP clients. Clients provide requirements and claims; the tool returns covered and uncovered items, dangling claims, counts, and a verdict.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
1Saved tool list · updated 1w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| claims | array | Yes | Claims that an issue, pull request, or code reference addresses a requirement |
| requirements | array | Yes | The spec's requirements |
Details
From the project READMEspeccheck
A spec is only as good as the work that actually answers it. Requirements get written, issues get filed, pull requests get merged, code lands — and somewhere in that pile the mapping between "what the spec asked for" and "what claims to have done it" quietly rots. speccheck audits that mapping. You supply the spec's requirements and the claims made against them, and it reports which requirements are covered, which are not, which claims point at requirements that do not exist, and how many claims each requirement collected.
Nothing is fetched. A requirement counts as covered the moment at least one claim names its id; the claiming source can be an issue, a pull request, or a code reference, and duplicate claims each count — three issues claiming the same requirement is a fact worth seeing in the count, not noise to deduplicate. A claim naming an id that no requirement has is dangling: it is echoed back in full, in the order the claims arrived, and it counts nowhere — not toward coverage, not toward any requirement's total. It usually means a renamed requirement or a typo, and either way it is the spec owner's problem to see, not the tool's to guess at.
The verdict compresses the report into one word. If
every requirement is claimed, the spec is
fully_covered. Otherwise the coverage percentage —
covered over total, rounded to the nearest integer —
decides: 80 or above is mostly_covered, 50 or above is
partial, and anything lower is sparse. The counts
always travel with the verdict, so the word never has to
be taken on faith.
Malformed input is a validation error naming the
offending path, with no partial result: requirements
must be a non-empty array of objects each carrying a
non-empty id and text, requirement ids must be
unique (a duplicate is an error naming the id), and
claims must be an array — possibly empty — of objects
each carrying a non-empty requirement_id and
source_ref plus a source_kind of issue, pr, or
code. Unknown extra fields are ignored. The computation
is pure and local: no network, no configuration, and no
repository is read or touched.
CLI
npx @reneturcios/speccheck check --input args.json
npx @reneturcios/speccheck --version
args.json contains the full arguments object:
{
"requirements": [
{ "id": "REQ-1", "text": "Users can sign in with a passkey" },
{ "id": "REQ-2", "text": "Sessions expire after 24 hours" },
{ "id": "REQ-3", "text": "Admins can revoke any session" }
],
"claims": [
{ "requirement_id": "REQ-1", "source_kind": "pr", "source_ref": "PR #412" },
{ "requirement_id": "REQ-1", "source_kind": "issue", "source_ref": "issue #388" },
{ "requirement_id": "REQ-2", "source_kind": "code", "source_ref": "src/session.ts" },
{ "requirement_id": "REQ-9", "source_kind": "issue", "source_ref": "issue #401" }
]
}
The result is printed as JSON:
{
"covered": ["REQ-1", "REQ-2"],
"uncovered": ["REQ-3"],
"dangling_claims": [
{ "requirement_id": "REQ-9", "source_kind": "issue", "source_ref": "issue #401" }
],
"claim_counts": { "REQ-1": 2, "REQ-2": 1, "REQ-3": 0 },
"coverage_percent": 67,
"verdict": "partial",
"requirement_count": 3,
"claim_count": 4
}
claim_counts carries an entry for every requirement,
including zeros, with keys in the order the requirements
were supplied. Exit codes: 0 on success, 1 on a
runtime error (including an unreadable or invalid input
file, or invalid input), 2 on a usage error.
MCP server
npx -y @reneturcios/speccheck mcp
MCP client config:
{
"mcpServers": {
"speccheck": {
"command": "npx",
"args": ["-y", "@reneturcios/speccheck", "mcp"]
}
}
}
Tools
-
check_spec_coverage— Verify a spec's requirements are claimed by issues, pull requests, or code, from caller-supplied requirement and claim facts.requirements(array, required, at least 1 item) — the spec's requirements; each item is an object with a non-emptyidandtext, and ids must be uniqueclaims(array, required, may be empty) — claims that an issue, pull request, or code reference addresses a requirement; each item is an object with a non-emptyrequirement_id, asource_kindofissue,pr, orcode, and a non-emptysource_ref
Returns
{covered, uncovered, dangling_claims, claim_counts, coverage_percent, verdict, requirement_count, claim_count}.
Docker
docker run -i ghcr.io/cloudcorprecords/speccheck
docker run --rm -v "$PWD:/w" ghcr.io/cloudcorprecords/speccheck check --input /w/args.json
Development
npm install
npm run build # tsc -> dist/
npm test # tsx --test test/*.test.ts (pure local, no network)
npm run dev # run the CLI from source
License
MIT — Copyright (c) 2026 Rene Turcios
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.