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ads_telegram_ai_post_list

Lists saved public Telegram posts from AI search and filters them by classification, score, or project; classifies results locally and never sends messages.

Instructions

List public Telegram posts saved from the global AI search. Results are classified locally as request, opportunity, discussion, promotion or repost; this tool never sends messages.

Input Schema

NameRequiredDescriptionDefault
limitNo
min_scoreNo
project_idNoneron
classificationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description does add real context: it is read-only ('never sends messages') and classification is performed locally with five fixed categories. It does not disclose ordering, pagination behavior, or permission/auth requirements for a tool with four optional parameters.

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 short sentences, front-loaded with what is listed, followed by the classification and safety note. No filler or restatement of the tool name.

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?

For a read-only listing tool with no annotations and no output schema, the description covers what the records are and their classification, which is enough to decide to call it. It leaves gaps around result ordering, paging via limit, and what min_score/project_id filter, which matter for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and none of the four parameters (limit, min_score, project_id, classification) are explained in the description. Mentioning the classification categories adds only a little, since the enum already enumerates those exact values, and min_score and project_id remain entirely opaque.

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 clear verb ('List') and a precisely scoped resource: public Telegram posts previously saved from the global AI search. The phrase 'saved from the global AI search' distinguishes it from live-search siblings like ads_telegram_public_posts_search, though it does not name any sibling explicitly.

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 implied by 'saved from the global AI search' — the agent infers this reads stored search output rather than performing a search. There is no explicit when-to-use guidance, no pointer to ads_telegram_ai_search_run_list or ads_telegram_ai_post_reclassify, and no statement of prerequisites such as needing a prior search run.

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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