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Glama

blobpedia

by io.github.UnityNodes

list_github_discussions

List GitHub Discussions from Celestia repos (e.g. celestiaorg/docs) cached on this server, ranked by upvotes then recency. Celestia repos only, from the local cache — not arbitrary GitHub Discussions (use a dedicated GitHub tool for those). Use get_github_discussion for the full body plus comments of one thread; this is GitHub Discussions, not the community forum (use get_discussion).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoFilter by repo, e.g. "celestiaorg/docs"
limitNo
categoryNoFilter by Discussions category, e.g. "Q&A", "Ideas"

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Discloses data source (cached), ranking order, and scope. No annotations provided, so description carries burden; it adds context about caching and ranking though omits potential staleness or authentication needs.

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 core purpose and key constraints. No unnecessary details, every sentence adds value.

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?

Covers purpose, scope, parameters, and alternatives. Lacks output format details, but acceptable for a list tool with no output schema. Adequate for agent invocation.

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?

Adds meaning to two parameters with examples (e.g., 'celestiaorg/docs', 'Q&A'). Explains ranking context. Despite high schema coverage, description provides useful usage hints beyond 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?

Clearly states it lists GitHub Discussions from Celestia repos cached locally, ranked by upvotes then recency. Distinguishes from get_github_discussion (single thread) and get_discussion (community forum).

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?

Explicitly limits to Celestia repos and local cache, warns not for arbitrary GitHub Discussions, and directs to dedicated tools. Provides clear when-to-use and alternatives.

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