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amulen-mcp

amulen-mcp

by lramirezq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

amulen_upload_attachment

Attach evidence files or written text to a specific task via local file path or inline content, with optional renaming and a 25 MB limit.

Instructions

Attach evidence to a task (max 25 MB).

Either file_path: a local file (screenshot, PDF, log, zip...) on this machine; nombre optionally renames it. Or nombre + contenido_texto: a text document you write (e.g. "evidencia.md" with a summary of the work done).

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": {
      "project_slug": "<project_slug>",
      "board_slug": "<board_slug>",
      "task_slug": "<task_slug>"
    },
    "name": "amulen_upload_attachment"
  }
}

Input Schema

NameRequiredDescriptionDefault
nombreNo
file_pathNo
task_slugYes
board_slugYes
project_slugYes
contenido_textoNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=true, and the description meaningfully adds the 25 MB size limit plus the fact that file_path reads from this machine. It does not disclose permission requirements, what happens on name collisions or failures, or what the call returns.

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 clauses, front-loaded with the core action and size constraint, and the mode split is scannable. No wasted wording.

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 6-parameter mutating tool with no output schema and no parameter descriptions, the description covers the genuinely ambiguous inputs well but leaves the three required slug parameters, error behavior, and return value to inference. Adequate, with visible gaps.

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

Parameters4/5

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

With 0% schema description coverage, the description carries real weight: it defines file_path as a local file, explains that nombre renames it, and establishes that contenido_texto is an alternative to file_path rather than a companion — a mutual exclusivity the schema does not express. The three slug parameters receive no explanation, but their meaning is apparent from their names.

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?

"Attach evidence to a task" is a specific verb plus resource, and the 25 MB cap frames the operation precisely. The two-mode framing (file vs. inline text) further separates it from siblings like amulen_add_comment or amulen_list_attachments, though no sibling is named explicitly.

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?

The "Either ... Or ..." structure gives clear conditions for choosing each invocation mode, with a concrete example ("evidencia.md"). It stops short of naming when to prefer other tools or when not to use this one.

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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