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TweekIT MCP Server

by io.github.equilibrium-team
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AI Hub Preflight & Format Recommendation

preflight
Read-onlyIdempotent

Validate whether a file format is supported by TweekIT and recommend the optimal AI-ready output format.

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": {
      "filename_or_ext": "<filename_or_ext>"
    },
    "name": "preflight"
  }
}

Input Schema

NameRequiredDescriptionDefault
filename_or_extYesInput filename, path, or extension to validate (e.g., 'scan.psd', 'report.xls', 'dwg').
target_providerNoTarget AI provider/hub profile ('claude', 'openai', 'gemini', 'mistral', 'grok', 'deepseek', 'openrouter', or 'default').default

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the scoping detail that validation is against TweekIT's supported formats and that a recommendation is produced, but says nothing about how strict the check is, whether it inspects file contents or just the extension, or any cost/latency traits.

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 both the validation and recommendation behaviors with no filler. It could be marginally improved by appending the pre-conversion usage cue, but nothing is wasted.

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?

With a rich annotation set, full schema coverage and an output schema, the description needs only to convey what the tool does and its role. It conveys the two-step outcome but leaves the workflow relationship to convert unexplained, which is the one remaining gap.

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% with both parameters fully documented, including provider examples, so the schema carries the load. The description adds no additional meaning about filename_or_ext resolution (e.g., path vs. bare extension) or how target_provider changes the recommendation.

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 names two specific actions on a concrete resource: validating whether a file format is supported by TweekIT and recommending an AI-ready output format. That is enough to distinguish it from siblings like convert or doctype without opening schemas, though it never explicitly contrasts itself with them.

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 only implied: the name 'preflight' and the validate/recommend framing suggest calling this before a conversion, but the description never states when to use it versus convert/doctype, nor any when-not condition. An agent must infer the workflow position.

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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