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Machine Relations Index

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Sources one answer engine cites

mri_get_engine
Read-onlyIdempotent

Ranked sources one answer engine cites, by that engine's citation rate across the whole window. Pass category to limit the list to sources with a published segment in that category; the rate stays the whole-window rate and is not a rate inside the category. Collecting categories and engines below the evidence floor withhold the ranking. Use to answer 'what sources does Perplexity cite most?' or 'which sources does Google AI Overviews cite among published sources'.

Input Schema

NameRequiredDescriptionDefault
limitNo
cursorNoPage token from the previous response's next.cursor. When set, offset is ignored.
engineYesEngine key from mri_list_engines: chatgpt, claude, gemini, google_ai_mode, google_ai_overviews, perplexity.
offsetNo
categoryNoOptional category key. Limits the ranking to sources with a published segment in that category.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / cursor
      Added value: +{
+  "description": "Page token from the previous response's next.cursor. When set, offset is ignored.",
+  "type": "string"
+}
  2. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely non-obvious behavior: the rate is computed over the whole window and stays whole-window even when a category filter is applied, and results are suppressed for entities below the evidence floor. It does not mention pagination behavior, though the cursor/offset precedence is documented in the schema.

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 definition and ordering metric, then the category caveat, then call examples — a sensible priority order with no filler. The evidence-floor sentence is slightly awkwardly phrased ('Collecting categories and engines ... withhold the ranking') but still carries 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?

No output schema exists, and the description covers the essential contract: what is ranked, by what metric, and how filtering affects the metric. Ordering direction (descending by rate) and the shape of each result row are inferred rather than stated, which is the main residual gap.

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 60%, with engine, cursor and category documented. The description adds real meaning the schema does not: category narrows which sources appear while the ranking metric remains whole-window, and engine is implicitly tied to the mri_list_engines key set. limit and offset carry no semantics in either place.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (ranked sources), the scoping dimension (one answer engine), and the ordering (that engine's citation rate across the window). It is distinguishable from the list/domain siblings by scope, but it never names or contrasts with mri_get_cited_sources, which sounds closely related.

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?

The closing sentence gives concrete triggering questions ('what sources does Perplexity cite most?', 'which sources does Google AI Overviews cite among published <category> sources'), which maps intent to tool. It also states a when-not condition — rankings are withheld below the evidence floor — but offers no explicit alternative tool for the related cited-sources use case.

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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