Skip to main content
Glama
Sign In
tg

tg

by rodion1010
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

ocr_photos

Extracts text from photos in a Telegram chat using Apple Vision and adds it to the archive, handling selected images or all unprocessed ones by default.

Instructions

Распознаёт текст на фото (Apple Vision) и вписывает его в архив. Без ids — все необработанные фото чата.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "chat": "<chat>"
    },
    "name": "ocr_photos"
  }
}

Input Schema

NameRequiredDescriptionDefault
idsNo
chatYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior4/5

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

Although no formal annotations are present, the description provides valuable behavioral context by specifying the technology used (Apple Vision) and the side effect of the operation (archiving). This adds necessary operational detail beyond basic function.

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?

The definition is highly concise, using only two sentences to convey the core function, the processing technology, and the critical parameter behavior. Every part of the definition is essential and contributes to clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of surrounding annotations, the description is exceptionally complete. It defines the input (chat photos), the method (OCR), and the control flow (use IDs vs. process all), making correct invocation possible without ambiguity.

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

Parameters5/5

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

The description adds significant semantic meaning to the optional 'ids' parameter. It translates the technical concept of an optional list into a functional directive, explaining that its absence is intended to process all unprocessed media.

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?

The description clearly states the purpose: recognizing text on photos using Apple Vision and archiving the content. It distinguishes the tool by specifying the OCR function and the resulting archival action.

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?

It provides specific instructions on when to use the tool's parameters by explaining that omitting the 'ids' targets all unprocessed chat photos. This is a direct guideline for controlling the scope of execution.

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

Deploy Server

Other Tools