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blobpedia

by io.github.UnityNodes

get_video

Get one Celestia-related YouTube video cached on this server (metadata plus transcript), by video id. Celestia-only cache — does NOT fetch arbitrary YouTube videos or search YouTube at large (use a dedicated YouTube tool for that). Find ids via list_videos or search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesYouTube video id, e.g. "dQw4w9WgXcQ"
transcript_charsNoTranscript characters to return. Default 12000; raise it (max 200000) for the full text, or set 0 for metadata only.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / transcript_chars
      Added value: +{
+  "default": 12000,
+  "description": "Transcript characters to return. Default 12000; raise it (max 200000) for the full text, or set 0 for metadata only.",
+  "maximum": 200000,
+  "minimum": 0,
+  "type": "integer"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool reads from a server-side cache, does not fetch arbitrary YouTube videos, and returns both metadata and transcript. It does not explicitly describe missing-id or error behavior, but the main operational behavior is clearly stated.

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?

Two sentences, front-loaded with the core operation, followed by scope exclusions and ID discovery guidance. Every sentence earns its place with no repetition or 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?

For a simple id-based retrieval tool with two well-documented parameters, the description fully equips an agent: it states the return content (metadata plus transcript), the cache boundary, the exclusion of general YouTube search, and how to obtain valid ids. No output schema is needed because the return shape is adequately described.

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 description coverage is 100%, so the schema already documents both id and transcript_chars thoroughly, including defaults, bounds, and the 0-for-metadata-only behavior. The description adds little beyond reinforcing the metadata-plus-transcript idea, which is already in the schema.

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 names a specific verb ('Get'), a specific resource ('one Celestia-related YouTube video cached on this server'), and the key scope distinction (by video id, metadata plus transcript). It differentiates itself from generic YouTube fetching and from sibling tools like list_videos or search.

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

Usage Guidelines5/5

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

It clearly states when to use the tool (for cached Celestia videos by id), when not to use it (arbitrary YouTube videos or searching YouTube at large), and provides explicit routing: use a dedicated YouTube tool for general video tasks, and find ids via list_videos or search.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct content types and actions, and descriptions carefully carve out boundaries (e.g. get_network_state vs get_network_stats, get_discussion vs get_github_discussion). However, the overlapping get_/find_/search_ families plus the very similar network_state/network_stats names leave some edge cases where an agent could select the wrong tool.

Naming Consistency4/5

The dominant convention is verb_noun (find_*, get_*, list_*, search_*), and get/list/find roughly map to id-based retrieval, browsing, and discovery. Deviations like learning_path, ecosystem_dependency_graph, and semantic_search break the pattern, and the get_ vs find_ vs search_ boundaries are not perfectly predictable.

Tool Count2/5

43 tools is on the high side for a single MCP server; even though the Celestia knowledge domain is broad, the surface is heavy and will increase selection cost. Most tools are individually useful, but the set would benefit from consolidation, e.g. merging release tools or search variants.

Completeness4/5

The server covers an unusually broad range of content types—CIPs, docs, forum, GitHub issues/discussions, releases, videos, whitepapers, ecosystem, and network state—with list/get/search access for most. Minor gaps remain, such as no dedicated blog retrieval and get_issue_status only returning status rather than full issue body, but core knowledge workflows have no dead ends.

Resources