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Glama

list_videos

Retrieve a summary of every video indexed in the RAG system, including name, path, and chunk count, to confirm which recordings are ready for natural language querying.

Instructions

List all videos currently indexed in the RAG system.

Returns a summary of each ingested video including its name, path, and chunk count.

Returns: JSON list of indexed videos with metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It implies a read-only inventory operation and describes the per-item fields, but says nothing about ordering, pagination, result limits, or behavior when the index is empty — meaningful gaps for an unannotated tool, though minor given the trivial zero-parameter surface.

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 first sentence is well front-loaded, but the second and third sentences restate the same return information twice ('Returns a summary of each ingested video...' followed by 'Returns: JSON list of indexed videos with metadata'). One of those should be cut.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the description is not obligated to describe return values, and the tool has no parameters — the definition is therefore close to sufficient. However, it omits ordering/scope details (does 'all' mean truncated or paginated?) that an agent would need to interpret the result set.

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?

The tool takes no parameters, so there is no parameter semantics to document and the baseline of 4 applies. The description adds nothing parameter-related, which is appropriate here.

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 specific verb (list) and resource (videos indexed in the RAG system), plus what each entry contains (name, path, chunk count). It does not explicitly contrast itself with siblings like search_video or ingest_video, but the distinction is clear enough from the verb alone.

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 can infer this is the tool for enumerating everything currently indexed rather than querying it. There is no explicit statement of when to prefer this over search_video or ask_video, and no exclusions or prerequisites.

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