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trust_score

When to call: before you connect to, install, wire into an agent, or recommend an MCP server, to check what the public record shows about whether it is still maintained. Pass the MCP schema-server id. Returns: JSON with trust_score (0 to 100 or null), display (score · depth · provisional), depth/depth_max, per-dimension values (liveness, maintenance, adoption, spec_currency, dependency_health; null = unknown, never invented), effective_weights, resolution method/confidence, status (scored | unresolved | insufficient_data), methodology URL. Depth 2 answers mortality more than merit; cite display as-is. Not a prediction, not advice, not a ranking of alternatives. Example: {"id":"io.github.06ketan/medium-ops"} id: MCP schema-server identifier (e.g. io.github.owner/name or owner/name). Not an npm package name, Action slug, or Docker image.

Input Schema

NameRequiredDescriptionDefault
idYesMCP schema-server identifier, e.g. io.github.owner/name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: nulls are 'never invented', status takes scored|unresolved|insufficient_data, depth 2 answers mortality more than merit, and the display string must be cited as-is. It omits operational traits such as auth, rate limits, or cost, which keeps it short of a 5.

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?

Front-loaded with 'When to call:' and 'Returns:' headers, and most sentences earn their place by constraining interpretation. The trailing id definition largely restates the schema description, which is the one redundant piece.

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, so the description must explain the return payload, and it does: fields, null semantics, status enum, depth meaning, weights/resolution, and methodology URL, plus the caveat about what the score does not mean. An agent has everything needed to call it and interpret the result.

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 coverage is already 100%, so the baseline is 3, but the description adds genuine disambiguation: the id is an MCP schema-server identifier and explicitly is not an npm package name, Action slug, or Docker image. That prevents a realistic class of wrong invocations.

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: check the public record on whether an MCP server is still maintained, and returns a scored trust judgment. It does not, however, differentiate itself from the siblings dependency_risk and schema_history, even though its own 'dependency_health' dimension clearly overlaps with dependency_risk.

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

Usage Guidelines4/5

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

The 'When to call:' clause gives an explicit triggering moment (before connecting, installing, wiring into an agent, or recommending a server) and boundaries ('not a prediction, not advice, not a ranking of alternatives'). It still never names the sibling tools as alternatives for adjacent questions, so routing between dependency_risk, schema_history and this tool is left 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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