Read one Celestia community forum thread (forum.celestia.org) with its posts, by numeric topic id. This is the CELESTIA FORUM channel — not GitHub Discussions (use get_github_discussion). Get the id from search or get_cip_mentions.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Forum topic ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It clearly states this is a read operation ('Read') and specifies the scope ('a thread with its posts'). It also clarifies the source channel (forum.celestia.org vs GitHub Discussions). It doesn't mention error conditions or response format, but for a simple read-only tool, the behavior is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is just two sentences, with the core purpose in the first sentence and usage guidance in the second. Every word earns its place, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no output schema), the description covers the essential context: what it reads, where to get the id, and how to avoid confusing it with a sibling tool. It doesn't detail the return structure, but 'with its posts' implies that, and it's sufficient for a straightforward read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the single parameter 'id' (type integer, description 'Forum topic ID'). The description adds value by noting the id is numeric and providing concrete sources for obtaining it ('from search or get_cip_mentions'), which goes beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Read one Celestia community forum thread (forum.celestia.org) with its posts, by numeric topic id.' It uses a specific verb ('Read'), identifies the resource (Celestia forum thread), and distinguishes it from the sibling tool get_github_discussion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent when to use this tool versus an alternative: 'This is the CELESTIA FORUM channel — not GitHub Discussions (use get_github_discussion).' It also provides guidance on how to obtain the required id: 'Get the id from search or get_cip_mentions.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.