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Get paper full text

get_paper_fulltext
Read-onlyIdempotent

Use this when the user asks “what does the methods/results section say”, wants to quote a specific section, or when the abstract isn't enough to verify a claim. Heavy: only call once a paper looks relevant from search_papers, search_related_papers, or get_paper_citations. format=markdown returns one rendered document; format=json returns a structured section list. Pass sections (case-insensitive headings, e.g. ["Methods"]) to fetch only those sections instead of the whole document.

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": {
      "paper_id": "<paper_id>"
    },
    "name": "get_paper_fulltext"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNo`markdown` returns one rendered document, ready to read or quote inline. `json` returns a structured section list, useful when you want to navigate by section name (methods / results / related work).markdown
paper_idYesA corpus paper UUID, from a search_papers / search_papers_many / search_related_papers / get_paper_citations result.
sectionsNoReturn only these sections (case-insensitive heading match), e.g. ["Methods", "Results"]. Omit to return the whole document.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds the genuinely useful non-obvious trait: the call is expensive/heavy and should be deferred until relevance is confirmed, plus what each format actually yields. It does not mention size limits or truncation behavior for very long papers, which keeps it from 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-loads the usage trigger and the cost warning before the parameter mechanics, which is the right order for an agent deciding whether to call. The final two sentences largely duplicate the schema's own parameter descriptions, so there is some redundancy, though nothing is padded.

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?

With no output schema, the description usefully explains the two return shapes (one rendered document vs a structured section list) and that section filtering reduces payload. The source of paper_id is only in the schema, but that is adequately covered there, leaving no significant gap for an agent to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already explains format (markdown vs json) and sections (case-insensitive heading match, omit for whole document). The description restates essentially the same meanings with a worked example, so it adds little beyond the schema — baseline 3 for a fully documented schema.

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 retrieval action on a specific resource (full text of a paper), and disambiguates it from sibling search tools by naming them and framing this as the step after relevance is established. An agent can identify this tool's role without opening the schema.

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?

Gives explicit when-to-use triggers ("what does the methods/results section say", quoting a section, verifying a claim the abstract cannot support), an explicit gating condition ("only call once a paper looks relevant from search_papers, search_related_papers, or get_paper_citations"), and a stated cost tradeoff ("Heavy").

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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