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Walk a paper's citation graph

paper_graph
Read-onlyIdempotent

Trace a paper's references and citing works to verify its status, uncover subsequent research, and build a reading list from one paper.

Instructions

Follow the citations of ONE paper, and check whether it still stands.

`search` finds papers that MENTION your words. This follows the edges
instead: what a specific paper built on, and what has built on it since.

Best for:
- Checking a citation before repeating it: is the DOI real, and has the
  paper been retracted or corrected?
- "What happened after this result": citing works come back ordered by how
  much the field cited them, so a 2019 paper leads to the current state of
  the art rather than to the most recent preprint about it.
- Building a reading list backwards from one good paper.

Not recommended for:
- Finding papers by topic -> `search(category="paper")`, or a sub-group
  like `"paper.biomed"` / `"paper.cs"` / `"paper.preprint"`.
- Reading the paper itself -> `read_doc` on the returned URL.

Returns:
- markdown (default): the paper with its retraction/correction notices,
  then "References" and "Cited by" sections.
- json: {paper, references, citations, notes}, where `paper.crossref`
  carries `registered` and every post-publication `notices` entry.

Common mistakes:
- Passing a topic instead of a paper. A title resolves to its single best
  match; a phrase that names no specific paper resolves to the wrong one.
- Reading an empty `citations` list as "uncited" when `notes` says the
  lookup was truncated.

Args:
    paper: DOI (`10.1145/1571941.1572114`, or a doi.org URL), an OpenAlex
        ID (`W2148972377`), or the paper's exact title.
    direction: "both", "references" (what it cites) or "citations" (what
        cites it).
    limit: Max neighbours per direction, 1-50.
    format: "markdown" or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
paperYes
formatNomarkdown
directionNoboth

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.12.0

TDQS

A5/5.0
Behavior5/5

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

Annotations provide readOnlyHint, openWorldHint, and idempotentHint, but the description adds substantial behavioral context: retraction/correction notices, citation ordering by field impact, truncation behavior in citations list, and specific return format details. It also explains the 'notes' field for truncated lookups. No contradictions with annotations.

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?

Though lengthy, the description is meticulously structured with headers, bullet lists, and code blocks. The core purpose and differentiation are front-loaded, and every section (Best for, Not recommended, Returns, Common mistakes) provides non-redundant, actionable information.

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?

Given there is no output schema, the description fully explains both markdown and json return formats, including nested fields like paper.crossref and notices. It covers edge cases like truncated citations and retraction notices, ensuring an agent has all necessary information to invoke the tool correctly.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully compensates. It explains the paper parameter with concrete examples (DOI, OpenAlex ID, exact title), the direction enum with meanings, the limit range (1-50), and format with return-type implications. This goes far beyond the schema's bare definitions.

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 states the specific verb 'follow the citations' and the resource 'ONE paper', clearly differentiating from search which finds mentions. It also explains the distinction between edge-following and text-matching, making the purpose unambiguous.

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 provides 'Best for' and 'Not recommended for' sections, naming alternatives like search(category=...), read_doc, and giving concrete scenarios. Also includes 'Common mistakes' that warn against passing topics instead of papers, which directly guides correct usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.