Searches Europe PMC using confirmed queries and returns de-duplicated, retraction-excluded paper candidates for relevance scoring.
Europe PMC を検索し、撤回除外・重複除外した候補を返す（ユーザー確認済みクエリ前提）。
返した各候補は LLM が当該 Qi への関連度で採点し、関連するものだけ ingest_stage で _inbox へ隔離すること。生ファイル名・サンプル名をクエリに含めないこと。
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| max_results | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint/openWorldHint annotations, it discloses meaningful behavior: retraction exclusion, de-duplication, an external service dependency, and a query-hygiene constraint (no raw filenames/sample names). It does not describe the shape of each candidate or what happens with large result sets, so it is strong but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The core purpose is front-loaded in the first sentence, and the remaining lines are pure operational guidance with no filler. Every sentence either states a constraint or directs a downstream action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read-only search with no output schema, the description supplies the external source, the filtering behavior, the query constraint, and the downstream pipeline, which is enough to call it correctly. The main residual gap is that the returned candidate fields and result-limit behavior are left unstated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 the parameter burden. It does add a real constraint on the content of `query` (exclude raw filenames/sample names), but `max_results` is never mentioned and no format hints are given for the query string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence names a specific verb and resource ('Europe PMC を検索し') plus result shaping ('撤回除外・重複除外した候補を返す'), which clearly separates it from the dataset/sample search siblings. It stops short of explicitly naming an alternative search tool, so sibling differentiation is inferred from the Europe PMC domain rather than stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states a prerequisite ('ユーザー確認済みクエリ前提') and a follow-on workflow (LLM scoring of candidates, then isolating relevant ones into _inbox via ingest_stage), which is real routing guidance. However, it never explicitly says when NOT to use this tool or names a competing tool as the alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.