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rixile9999

tdl-mcp

by rixile9999

Read recent Telegram messages

tg_messages

Export recent media messages from a Telegram chat by id or @username as compact {id,date,file,text} objects; use last_n or since_id for recent or incremental reads.

Instructions

Export recent media messages from one chat (by id or @username) and return them as compact {id, date, file, text} objects — newest range exported via tdl. Use last_n for 'the last N media messages', or since_id to fetch only messages after a known message id (incremental reads). Read-only.

Input Schema

NameRequiredDescriptionDefault
chatYesChat id or @username/domain (as shown by tg_chats)
last_nNoHow many recent media messages to export (default 50, max 500)
since_idNoOnly messages with id > since_id (overrides last_n; for incremental reads)
with_textNoInclude message text content (default true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.1.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / since_id / maximum
      Added value: +9007199254740991
  2. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It discloses the 'Read-only' safety profile and that export is done via tdl, but says nothing about auth requirements, rate limits, or error behavior. It adds useful context beyond structured fields but leaves real gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence that covers purpose, parameters, and return shape without fluff. It is dense with parenthetical asides but every clause earns its place.

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?

For a 4-param read tool with no output schema, the description usefully describes the returned object shape and the backend. It omits auth/pagination/failure detail, but the core information an agent needs to invoke it is present.

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 each parameter is already documented, including the since_id-overrides-last_n relationship. The description reinforces intended usage of last_n and since_id but adds no syntax or format detail beyond the schema, so baseline 3 is appropriate.

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?

States a specific verb (export) and resource (recent media messages from one chat) and even specifies the return shape {id, date, file, text}. This clearly distinguishes it from siblings tg_chats (listing chats) and tg_download (fetching files).

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

Usage Guidelines4/5

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

Explicitly explains when to use last_n ('the last N media messages') versus since_id (incremental reads after a known id). It does not name sibling alternatives like tg_download for a specific message, but the parameter-selection guidance is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.