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InterLogue

Fact-check a piece against its transcript

check_citations

Validate that every quote resolves verbatim to a transcript timestamp before publishing. Checks section order, timestamps, and numbers, then persists a clean piece as a draft or returns failing spans to fix.

Instructions

Validates that every quoted span resolves to a subject turn at the cited timestamp. With piece_id it re-checks a stored piece. With brief_id and markdown it checks a host-written piece: section order (story, then pull quotes), every quote verbatim and timestamped, no numbers outside quotes, no repeated frames. A clean pass persists the piece as a draft for human review and returns its piece_id. A fail returns every failing span with the closest matching turn so you can fix and resubmit; nothing is persisted on a fail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brief_idNoWith markdown: the brief whose transcript the piece was written from.
markdownNoWith brief_id: the host-written piece. H1 headline, prose story, then '## Pull quotes' with one '> “quote” (MM:SS)' per line. The per-question view is appended for you.
piece_idNoRe-check a stored piece by id. Give either piece_id, or brief_id plus markdown.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the validation rules (section order, verbatim timestamped quotes, no numbers outside quotes, no repeated frames), that a clean pass persists a draft for human review and returns a piece_id, and that a fail persists nothing and returns failing spans with the closest matching turn.

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?

Front-loads the core validation statement, then the two modes, then the pass/fail outcomes. Every sentence conveys a distinct behavioral fact with no filler.

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?

There is no output schema, so the description must explain return behavior; it does so for both paths (piece_id on pass, failing spans plus nearest turn on fail). Nothing an agent needs to call or interpret this tool is missing.

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 coverage is 100%, and the parameter descriptions already explain the two invocation modes and the required markdown format. The description restates the piece_id vs. brief_id+markdown split without adding syntax or format detail beyond the schema, so the baseline 3 applies.

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: validates that quoted spans resolve to a subject turn at the cited timestamp. This is clearly distinct from sibling generators like draft_piece and generate_piece, and the title reinforces the fact-check framing.

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 description explicitly documents two invocation modes: 'With piece_id it re-checks a stored piece' and 'With brief_id and markdown it checks a host-written piece.' That gives clear context for selecting arguments, though it never names sibling alternatives or says when this check should be skipped.

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