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aminehamlouchi

InterLogue

Get the reporter's packet to write the piece

draft_piece

Assemble a reporter's packet from an interview transcript: brief, angle, question plan, writing contract, ranked verbatim quotes with timestamps. Enables drafting a piece before citation checks.

Instructions

Returns everything needed to write the published piece from the transcript: the brief and angle, the question plan, a strict writing contract, ranked verbatim quote candidates each with its timestamp, and the full timestamped transcript. You (the host) write the story first, then pull quotes, in markdown, and submit it to check_citations. Every quoted span must be verbatim from a subject turn and followed by its (MM:SS). Nothing is published until the check passes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brief_idYesThe brief_id whose transcript you are writing from. run_interview must have stored a transcript for it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the publication gate ('nothing is published until the check passes') and the hard constraint that every quoted span be verbatim from a subject turn and carry its (MM:SS). It stops short of stating access/permission requirements or whether the packet is cached/regenerated.

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?

Four sentences, front-loaded with what is returned, then the authoring rules. Dense but each sentence earns its place; the return-content list is long but necessary given there is no output schema.

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?

No output schema exists, so describing the returned packet is essential, and the description does so thoroughly while also covering the citation format and the check_citations gate. An agent has everything needed to invoke it and act on the result.

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 there is only one parameter, so the schema already defines brief_id's meaning and the precondition that run_interview stored a transcript. The description adds no further semantics about brief_id, so the baseline of 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?

The description states a specific retrieval action and enumerates the exact payload (brief/angle, question plan, writing contract, ranked verbatim quote candidates with timestamps, full timestamped transcript). It also implicitly distinguishes itself from siblings like generate_piece and fetch_transcript by clarifying that the host writes the story, not the 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?

It gives a clear workflow: write the story first, then pull quotes in markdown, then submit to check_citations, with the rule that nothing is published until the check passes. It names a downstream sibling and its ordering but never states when NOT to use this tool (e.g., versus fetch_transcript) or any prerequisites beyond the transcript existing.

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