Yank

Check a statement against its source

check_quote

Read-onlyIdempotent

Yank Check: a statement and the source it is supposed to come from, in; a verdict and a receipt, out. FOUND (the words are in the representation Yank inspected), CLOSE MATCH (substantially the same wording, with the difference shown), DISTILLED MATCH (a passage shares most of the statement's content words but not its literal words; shared words can say the opposite, so read the passage), NOT FOUND (Yank inspected an adequate representation and could not find support), or CAN'T ESTABLISH (Yank could not obtain or inspect enough evidence; the reason says why). With where (a moment for media, the publisher's page opened on the exact words for an article), speaker with the class of that claim (file-stated, representation-stated, not-established), the passage around it, which representation was read (captions, transcript, article text, filing, document) and how much of it (inspected: words, duration, and sha256, the fingerprint of the exact text read), the checker's version (checker), and when. A NOT FOUND is a bounded claim scoped to the representation read, never a claim that the words were not said; a CLOSE MATCH lists the words that differ (difference.tokens), never a similarity number; every verdict carries one plain sentence (finding). No model is consulted: the verdict resolves against the representation itself. Sources Yank already holds check immediately; an article, a public PDF (located by page) or a captioned video is read for the check; audio that would need transcribing is not spent on here and returns CAN'T ESTABLISH with acquisition_required, so yank it first. None of the verdicts is a judgement on whether the statement is true.

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": {
      "statement": "<statement>",
      "source": "<source>"
    },
    "name": "check_quote"
  }
}

Input Schema

Name	Required	Description	Default
`source`	Yes	The public http(s) link the statement is supposed to come from.
`statement`	Yes	The words to check, as claimed. One claim at a time, up to 600 characters.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 27, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Beyond the readOnly/idempotent/openWorld annotations, it discloses that no model is consulted and verdicts resolve deterministically against the representation, that NOT FOUND is bounded to what was inspected rather than a claim about the world, that CLOSE MATCH returns differing tokens instead of a similarity score, and that none of the verdicts is a truth judgement. It also states cost behavior (transcription is not spent here) — exactly the kind of context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The input/output frame is front-loaded and every section carries information, but it is delivered as one long run-on sentence chain dense with internal jargon ('Yank', 'representation', 'receipt', 'inspected'), which slows parsing considerably. It is over-stuffed rather than padded — trimming the jargon would preserve content and improve structure.

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?

With no output schema, the description carries the full return-value burden and does: it enumerates all five verdicts with meanings, plus every receipt field (where, speaker class, passage, representation type, inspected words/duration/sha256, checker, timestamp). For a 2-parameter open-world check tool, an agent has everything needed to call it and interpret the result.

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% and the two parameters are documented, so the baseline is 3; the description adds real meaning by specifying which source kinds are readable (article, public PDF located by page, captioned video) versus which return CAN'T ESTABLISH, which is not in the schema. It does not add format detail beyond the schema for `statement`.

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?

The opening clause 'a statement and the source it is supposed to come from, in; a verdict and a receipt, out' states a specific verb (check), resource (statement vs. source), and output shape, so the tool's function is unmistakable. It never names the sibling check_memory or explains how this differs from checking against stored memory, so sibling differentiation is left to inference.

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?

It gives concrete eligibility rules: sources Yank already holds check immediately, articles/public PDFs/captioned video are fetched, and audio needing transcription is refused with CAN'T ESTABLISH plus acquisition_required and an instruction to 'yank it first.' That is a genuine when-to-use/when-not boundary, but it is expressed as source-type eligibility rather than as a choice among the available sibling tools.

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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