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996.fm perspective graph

Get the transcript around a claim

get_context
Read-onlyIdempotent

The transcript around one claim — the moment in context, with its receipt. Spoken: the episode's public transcript, windowed ±90s around the claim's timestamp. Written (an essay): the verbatim excerpt snapshotted at digest plus a link into the original; never the surrounding text, never a live fetch. Quote the receipt — episode + timestamp, or essay link + excerpt — so the founder can check the moment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claim_idYesClaim id from any tool that returned a card, e.g. clm-5p0ken01

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / claim_id / description
      Added value: +"Claim id from any tool that returned a card, e.g. clm-5p0ken01"
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as safe. The description adds value by disclosing that written content returns a verbatim excerpt plus a link, and explicitly states 'never the surrounding text, never a live fetch' – behavior not captured in annotations. It also instructs quoting the receipt for verification, adding practical context.

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?

Three sentences, efficient and front-loaded with the core purpose. The spoken/written distinction is clearly organized. Some redundancy exists ('the moment in context' and 'transcript around one claim'), but overall it's tight and readable.

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?

For a single-parameter, read-only tool with no output schema, the description covers what is returned (transcript window, excerpt, link) and how to use the receipt. It doesn't mention potential error cases, but those aren't essential. It's sufficiently complete for an agent to call it correctly.

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% – claim_id is fully described in the schema with an example. The description does not add any additional semantic detail about the parameter beyond what the schema already provides. Baseline 3 is appropriate since the schema does the heavy lifting.

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: 'The transcript around one claim'. It clearly identifies what the tool returns (transcript context) and differentiates the spoken vs written cases, which helps the agent understand the exact scope. Siblings like find_perspectives and get_stances are about different resources, so this stands distinct.

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?

Provides clear context on when to use the tool (to get the transcript around a claim) and explains the two content types (spoken vs written) with specific behavior (windowed ±90s, excerpt snapshot). It does not explicitly mention when NOT to use it or name alternative tools, but the guidance is strong enough for an agent to infer appropriate use.

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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