telegram_channel_post_getGet a single public post from a Telegram channel by handle and post ID. Groups are not supported.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Telegram public username (channel or group), with or without leading @. | |
| postId | Yes | Numeric Telegram channel post ID from the public URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the safe-read nature is covered. The description adds the constraint that groups are not supported and that it only retrieves public posts, which is valuable behavioral context. However, it doesn't describe response format, error behavior, or rate limits, which would be additional transparency.
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 a single, concise sentence that front-loads the core purpose and ends with a clear limitation. No filler or redundant information; every word contributes.
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?
For a simple two-parameter getter with no output schema, the description is complete. It specifies the resource, the input, the public scope, and the unsupported case (groups). Nothing critical for an agent to call it correctly is missing.
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?
Schema description coverage is 100%, with both handle and postId fully described. The description merely reiterates 'by handle and post ID' without adding new meaning beyond the schema. Since the schema does the heavy lifting, a baseline of 3 is appropriate.
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 action (get a single public post), the resource (Telegram channel), and the specific identifiers (handle and post ID). The word 'single' distinguishes it from sibling tools like telegram_channel_posts_get and telegram_channel_get, making its purpose unambiguous.
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 provides clear context for when to use this tool: when you have a specific post ID from a public channel. It explicitly excludes groups, which is a useful limitation. However, it doesn't name alternative tools for listing posts or channel metadata, so the guidance is clear but not fully explicit.
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.
Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.