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Picsha AI MCP Server

Picsha AI MCP Server

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by picsha-ai
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reanalyze_asset

Initiate AI re-analysis of an asset to detect faces, objects, and other features.

Instructions

Manually trigger AI re-analysis on an existing asset to detect faces, objects, etc.

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": {
      "id": "<id>"
    },
    "name": "reanalyze_asset"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe unique ID of the asset

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.12

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description must fully convey behavioral traits. It fails to disclose whether the operation is synchronous or asynchronous, idempotent, or if it overwrites previous analysis. It also lacks information on required permissions or side effects.

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 description is a single, front-loaded sentence with no redundant text. It efficiently conveys the core purpose without wasting words.

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 simple one-parameter tool with no annotations or output schema, the description provides minimal context. It explains what the tool does but omits details about return value, whether the operation is immediate or queued, and any constraints. It is adequate but not complete.

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 coverage is 100% with the parameter 'id' already described as 'The unique ID of the asset'. The tool description adds no additional meaning, so baseline score of 3 is appropriate.

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?

The description clearly states the tool triggers AI re-analysis on an existing asset to detect entities like faces and objects. The verb 'trigger' and resource 'asset' are specific, and it distinguishes from sibling tools like 'moderate_asset' or 'get_asset'.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives such as 'moderate_asset' or 'summarize_asset'. There is no mention of prerequisites, post-conditions, or scenarios where re-analysis is appropriate.

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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