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Crawlora MCP

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research_related_papers

Get paper references or citing papers. Return one-hop Europe PMC citation edges, canonical seed IDs, source provenance and a frozen owner-bound cursor. Modes are references and citers; intent is unsupported.

Instructions

Get paper references or citing papers. Return one-hop Europe PMC citation edges, canonical seed IDs, source provenance and a frozen owner-bound cursor. Modes are references and citers; intent is unsupported. Partial results explicitly report indexed-source and candidate-window limits.

Input Schema

NameRequiredDescriptionDefault
requestYesSeed IDs and graph direction, or cursor and optional limit

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.12

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 behavioral burden and does substantial work: it discloses the one-hop traversal limit, that seed IDs come back canonicalized, that provenance is included, that the cursor is frozen and owner-bound, and that partial results self-report indexed-source and candidate-window limits. It omits any auth/permission requirements, but the disclosed behavior far exceeds a minimum.

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?

Three front-loaded sentences with zero restatement of the name; the core purpose leads and the return-shape detail follows. Slightly jargon-dense ('frozen owner-bound cursor', 'candidate-window limits') but each clause carries distinct information.

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?

For a tool with no output schema and no annotations, the description supplies the essential return-shape (citation edges, canonical seed IDs, provenance, cursor) and a partial-result caveat. The nested request object's sub-fields are not individually explained, but the mode/cursor semantics are covered well enough to call it 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 coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: it tells the agent that only 'references' and 'citers' are valid modes and, critically, that the schema's 'intent' property is unsupported despite existing in the object. It also characterizes the cursor as frozen and owner-bound, which the schema does not.

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 opens with a specific verb and resource: 'Get paper references or citing papers.' It names the exact citation-edge scope (one-hop Europe PMC) and both modes, which lets an agent distinguish it from siblings like research_search_papers or research_read_paper without opening any schema.

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?

It enumerates the modes (references vs citers) and rules out 'intent' as unsupported, which is useful routing context. But it never states when to choose this tool over siblings such as research_search_papers or research_read_paper, so the when-to-use decision 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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