rei-checker

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verify

Check a logical expression and receive a verdict: VALID, INVALID, or UNDECIDED with a reason code. The expression is normalized and logged in an append-only ledger without LLM involvement.

Instructions

Verify one expression. Returns a three-valued verdict (VALID / INVALID / UNDECIDED) with a reason_code when UNDECIDED. No LLM anywhere on the judgment path (spec §1.1). The expression is normalized and recorded in the append-only refutation ledger (spec §4).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "expression": "<expression>"
    },
    "name": "verify"
  }
}

Input Schema

Name	Required	Description
`context`	No	Optional context (axioms, imports, prior definitions). Backend-defined semantics.
`expression`	Yes	The expression to judge.
`timeout_ms`	No	Hard timeout in milliseconds. Overrun → UNDECIDED/TIMEOUT. Default: 5000.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 23, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses the three-valued return, conditional reason_code, the no-LLM guarantee, and the side effect of recording in an append-only refutation ledger. This is strong transparency, though it omits details like idempotency or error behavior.

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?

Three dense sentences with no filler. The verdict behavior is front-loaded, and the side-effect and no-LLM guarantees are stated efficiently. Every sentence earns its place.

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?

There is no output schema, but the description adequately explains return values and side effects. The input schema covers parameters. The only notable gap is the lack of explicit routing guidance relative to the sibling tool, but the core information needed to call and interpret the tool is present.

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?

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds the fact that the expression is normalized, but it does not provide additional parameter-level guidance beyond what the schema already states.

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

Purpose4/5

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

The description states a specific action ('Verify one expression') and clearly defines the output (VALID / INVALID / UNDECIDED with reason_code). It is easily distinguishable from the sibling 'stats' tool, though it does not explicitly name or contrast that sibling.

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

Usage Guidelines3/5

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

The description implies this tool is for judging a single expression, but it gives no explicit guidance on when to choose it over 'stats' or any other alternative. There are no stated exclusions or conditions, leaving the usage context to inference.

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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Other Tools

statsA
verifyA