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Proofrail

by armsteadj1
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TypeScript
Local

Verify claims and return the least-proven repair packet

proofrail_verify
Idempotent

Verifies code claims from proofrail.json by running declared commands, scores each claim deterministically, and returns a ranked list plus a repair packet for the least-proven claim.

Instructions

Load proofrail.json, resolve every anchor, run the manifest-declared commands the claims depend on, score every claim deterministically, and return the ranking plus one compact repair packet for the least-proven claim (anchors, missing proof, reproducer, done condition). Set run=false to score from cached command results without executing anything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jevNoAlso ask the configured local Jev command for advisory judgments. Reports "unavailable" when none is configured.
runNoExecute the declared commands (default true). false uses cached results; dynamic proofs without a cached run report not-run.
claimIdsNoRestrict verification to these claim ids.
projectRootNoProject directory containing proofrail.json. Must be inside a root the server was started with. Defaults to the first allowed root.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate non-read-only, non-destructive, and idempotent behavior. The description adds that it executes manifest-declared commands and scores deterministically, and that run=false skips execution. This adds behavioral context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense sentence that front-loads the core action and appends the run=false caveat. It is efficient with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main behavior, the return format (ranking plus repair packet with components), and the run=false option. Given the tool's complexity and lack of output schema, it is reasonably complete, though it could detail the ranking structure more.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers all four parameters with descriptions, and the description repeats the run=false behavior without adding new information. With 100% schema coverage, the description adds no extra semantic value, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it loads proofrail.json, resolves anchors, runs manifest-declared commands, scores claims deterministically, and returns a ranking plus one repair packet. This is a specific verb and resource, and it distinguishes from typical tools by describing the full verification pipeline.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus proofrail_focus or proofrail_recheck. It only mentions the run=false option for using cached results, which is a parameter behavior, not a tool-selection guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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