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Python
Hybrid

corpus_links_suggest

Rank URLs your corpus frequently cites but has never deposited, surfacing hearsay-versus-primary-source gaps by trust-weighted source diversity and recency for read-only review.

Instructions

Rank undeposited URLs the corpus frequently cites (read-only).

Surfaces primary sources the corpus leans on but has never deposited —
"hearsay vs. primary source" gaps — ranked by trust-weighted distinct-source
diversity × recency. Read-only: the ``dismiss`` half of the
workflow lives on the CLI / HTTP API.

Args:
    limit: Maximum suggestions to return. Defaults to
        ``citation_signal.rank_cap`` when omitted.
    min_sources: Minimum distinct citing sources required to surface a URL.
        Defaults to ``citation_signal.min_distinct_sources`` when omitted.

Returns:
    ``{suggestions, total_candidates, capped}`` matching the
    ``DepositSuggestReport`` schema.

Input Schema

NameRequiredDescriptionDefault
limitNo
min_sourcesNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.210.2

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations supplied, the description does real work: it declares read-only behavior, explains the trust-weighted distinct-source diversity × recency ranking, and states that dismissal is out of scope. It does not cover auth, rate limits, or what capping means operationally, 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the purpose and read-only constraint, then uses explicit Args and Returns sections. It is slightly verbose around the 'hearsay vs. primary source' framing, but every section is useful and nothing is buried.

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?

For a two-optional-parameter read-only query tool with an output schema, the description supplies the selection semantics, defaults, scope limitation, and return shape. An agent has enough information to call it correctly without external docs.

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 0%, so the description must compensate, and it does: limit is 'maximum suggestions to return' with a named default ('citation_signal.rank_cap'), and min_sources is a distinct-citing-source threshold with its own config default. The parameter meanings are clear even though the config keys themselves are not expanded.

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 verb and resource ('rank undeposited URLs the corpus frequently cites') and characterizes the target set as primary sources cited but never deposited. This is clearly distinct from generic link suggestions and from the sibling links_suggest tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly frames the read-only half of a workflow and says the dismiss half lives on the CLI/HTTP API, which tells the agent this tool cannot complete the full loop. It does not explicitly contrast with the sibling links_suggest, so it falls short of a 5.

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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