naulon

Appraise candidates for a topic

naulon_appraise

Read-onlyIdempotent

Score how relevant each candidate is to the topic from its free teaser alone: a relevance from 0 to 1 and a one-line rationale for each. Call it on the rows naulon_discover returned, to decide which are worth a live price from naulon_quote. Calls are limited per caller: a refused call says how many seconds to wait. It is free: it reads the teaser and the match flags, never the text behind the toll, and it fetches nothing. Pass each row back whole, or a subset of whole rows. matchedInBody and matchedSemantic tell the scorer why the search returned a row, and without them a source matched in its body scores the same as a near miss.

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": {
      "topic": "<topic>",
      "candidates": "<candidates>"
    },
    "name": "naulon_appraise"
  }
}

Input Schema

Name	Required	Description	Default
`topic`	Yes	The research topic to score relevance against.
`candidates`	Yes	Candidates to appraise — pass naulon_discover's rows through unmodified.

Output Schema

Name	Required	Description	Default
`appraised`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 13, 2026
- addedInput schema / properties / candidates / items / properties / slug / description
```
Added value: +"The row's `slug` from discovery, returned on its score so the two can be joined."
```
- addedInput schema / properties / candidates / items / properties / title / description
```
Added value: +"The row's `title` from discovery, judged with the teaser."
```
First observedNov 11, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds the operationally critical traits: per-caller rate limits with a refusal message containing the wait time, no cost, no fetching, and no reading of tolled content. Those are exactly the facts an agent needs before retrying or budgeting calls.

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-loads the purpose, then pipeline guidance, then limits, and every sentence carries information. A few sentences are compound and dense (the match-flag explanation) but nothing is 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?

Output schema exists, yet the description still summarizes the return ('relevance 0-1 plus rationale' joined on slug). Cost, rate-limit behavior, input pass-through rules and pipeline placement are all covered, so nothing needed to call this correctly is missing.

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 100%, so baseline is 3, but the description adds real meaning: it explains that matchedInBody and matchedSemantic tell the scorer why a row was returned, and that omitting them collapses a body match into a near miss. That is scoring behavior the schema's one-line field descriptions do not convey.

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?

States a specific verb and resource ('score how relevant each candidate is to the topic') and pins the output ('a relevance from 0 to 1 and a one-line rationale for each'). The teaser-only scope distinguishes it from retrieval tools that fetch full text.

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

Usage Guidelines5/5

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

Explicitly routes the agent: call it on rows returned by naulon_discover, to decide which are worth a live price from naulon_quote. That is a concrete when-to-use plus the next step in the pipeline, with the input-shape constraint (whole rows or a subset of whole rows) spelled out.

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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