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LEGION Verify: MCP tool-list history

check_mcp_server

Read-onlyIdempotent

One-call summary for an MCP server registry id (e.g. "ai.alphaquantlabs/propertycheck"): tool-list fingerprint history observed by LEGION, last change, per-server coverage from the signed COVERAGE_V1 register (COMPLETE only if observed in every register cycle, UNKNOWN if partial), proof references and a command that verifies everything offline. Read-only. Unknown id -> state UNKNOWN (absence from the log is not a verdict). A change is not an attack; this log does not certify that a server is secure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
server_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover read-only, idempotent, non-destructive, and open-world behavior, but the description adds substantial behavioral context: unknown ids resolve to UNKNOWN, absence from the log is not a verdict, coverage is COMPLETE only when observed in every cycle, and the log does not certify security. These disclosures go well beyond the annotations.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and then packs in constraints and caveats efficiently. It is somewhat dense and runs as a single paragraph, but every clause appears to add useful information rather than filler.

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

Completeness5/5

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 enumerates the expected return contents and explains key result semantics (COMPLETE vs UNKNOWN, unknown id behavior, non-certification). Given the annotations and single simple parameter, an agent has enough context to call and interpret this tool correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry parameter meaning. It identifies the parameter as an MCP server registry id and supplies a concrete example format ('ai.alphaquantlabs/propertycheck'), which is useful. It does not describe validation rules or alternate id forms, so it is not complete enough for a 5.

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 verb and resource: 'One-call summary for an MCP server registry id.' It then enumerates the concrete contents of that summary (fingerprint history, last change, coverage, proof references, verification command), making the tool's purpose very clear. It does not explicitly name or differentiate itself from sibling tools like verify_mcp_server or get_server_changes, so it falls short of a 5.

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?

Usage is implied by 'One-call summary for an MCP server registry id' and the read-only nature, but there is no explicit guidance on when to use this versus siblings such as get_server_changes or verify_mcp_server. The caveat about unknown ids adds useful context but not alternative-selection guidance.

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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