Skip to main content
Glama

submit_claims

Add timestamped knowledge cards to a video using quotes copied exactly from its transcript; each quote is code-verified, mismatches are dropped, and the response reports how many were kept.

Instructions

Add your knowledge cards for a video. Each item: {"claim": one plain sentence, "quote": 6-40 words copied EXACTLY from the transcript, "t": "mm:ss", "topic": short Title Case topic (reuse known topics), "kind": advice|fact|protocol|warning|opinion}. Code checks every quote against the transcript and drops any that don't match word for word; the result says how many were kept.

Input Schema

NameRequiredDescriptionDefault
claimsYes
video_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the exact-match validation, that non-matching items are silently dropped, and that the result reports how many were kept. It omits duplicate handling (does resubmitting replace or append claims?) and any auth/permission constraints.

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?

The payload shape is front-loaded and every clause earns its place — the quote-length range and the exact-copy rule are exactly what an agent needs to avoid a silent drop. Slightly dense as a single run-on block, but 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?

An output schema exists, so return values are covered, and the description still adds the one return-relevant fact (kept-count). Combined with the full payload specification and the cross-reference to 'reuse known topics' (sibling 'list_topics'), an agent has enough to call this correctly.

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 description coverage is 0%, and the item object is otherwise opaque ('additionalProperties: true'), so the description's per-field breakdown (claim, quote with 6-40 word exactness rule, t as mm:ss, topic Title Case reuse, kind enum) is essential and well done. The 'video_id' parameter is left undocumented, presumably assumed obvious.

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 concrete verb and resource: 'Add your knowledge cards for a video'. This is clearly distinct from the sibling 'add_videos' (which registers videos rather than extracted claims), though the distinction is implied rather than stated explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied — an agent infers this is the step after 'next_video_to_analyse' and possibly after 'list_topics'. There is no explicit when-to-use, no prerequisite (e.g. must the video be in an analysis session?), and no statement of what to do if a quote is rejected.

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