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Eclipse-Cj

Paper Distill MCP Server

pool_refresh

Refresh academic paper search results by querying 9 major databases including OpenAlex, Semantic Scholar, and PubMed. Use when search pool is exhausted or when adding new research topics.

Instructions

Refresh the paper search pool by querying 9 academic APIs.

Call this when pool is exhausted or when adding a new research topic. Searches: OpenAlex, Semantic Scholar, PubMed, arXiv, Papers with Code, CrossRef, Europe PMC, bioRxiv, DBLP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional single topic key to search (for new topics). If None, refreshes all topics.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the action (refreshing via 9 APIs) and when to call it, but doesn't mention behavioral traits like whether this is a long-running operation, rate limits, authentication needs, what 'refreshing' entails (overwrites? appends?), or error handling. The description adds basic context but lacks important operational details.

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 sentences with zero waste: first states purpose and mechanism, second provides usage guidelines, third lists the 9 APIs. Every sentence adds value, and the structure is front-loaded with the core action and when to use it.

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?

Given 1 parameter with 100% schema coverage and an output schema exists, the description is reasonably complete. It covers purpose, usage guidelines, and parameter semantics well. However, as a tool with no annotations that performs API queries across 9 sources, it should ideally mention more about behavior (e.g., execution time, rate limits, what 'refresh' means operationally) to be fully complete.

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 100%, so the schema already documents the single parameter 'topic' with its optional/null behavior. The description adds meaningful context by explaining the parameter's purpose: 'for new topics' and clarifying that 'If None, refreshes all topics.' This provides semantic value beyond the schema's technical specification.

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?

The description clearly states the specific action ('Refresh the paper search pool') and the mechanism ('by querying 9 academic APIs'), then lists all 9 APIs. It distinguishes this tool from siblings like 'search_papers' (which likely searches within the pool) and 'add_topic' (which adds topics without refreshing).

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 states when to use: 'Call this when pool is exhausted or when adding a new research topic.' This provides clear context for invocation and distinguishes it from alternatives like 'search_papers' (for searching within existing pool) or 'add_topic' (just adding topics without API queries).

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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