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Mirdan

Mirdan

by S-Corkum
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

analyze_intent

Analyzes developer prompts to detect intent, identify entities, and recommend structured approaches for code generation.

Instructions

Analyze a prompt without enhancement, returning the detected intent, entities, and recommended approach.

Args: prompt: The developer prompt to analyze

Returns: Structured intent analysis

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": {
      "prompt": "<prompt>"
    },
    "name": "analyze_intent"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool analyzes a prompt and returns structured intent analysis, but doesn't disclose behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what happens with invalid inputs. This is a significant gap for a tool with no annotation coverage.

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?

The description is appropriately sized and front-loaded, with the core purpose stated first. The additional details about args and returns are useful but could be more integrated. There's no wasted text, though it could be slightly more polished for optimal clarity.

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?

Given the tool's moderate complexity (1 parameter, no annotations, but has an output schema), the description is minimally complete. It covers the purpose and basic I/O, but lacks details on behavior, error handling, or how it differs from siblings. The presence of an output schema reduces the need to explain return values, but more context is needed for full understanding.

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?

The description adds minimal semantics beyond the input schema: it defines 'prompt' as 'The developer prompt to analyze'. With 0% schema description coverage and only 1 parameter, this provides some value, but it's basic and doesn't elaborate on format, constraints, or examples. The baseline is 3 since the schema covers the parameter structure adequately.

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's purpose: 'Analyze a prompt without enhancement, returning the detected intent, entities, and recommended approach.' This specifies the verb (analyze), resource (prompt), and output (intent, entities, approach). However, it doesn't explicitly differentiate from sibling tools like 'enhance_prompt' or 'suggest_tools', which prevents a perfect score.

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?

The description implies usage by mentioning 'without enhancement' and listing output components, suggesting it's for raw analysis rather than enhancement. However, it lacks explicit guidance on when to use this tool versus alternatives like 'enhance_prompt' or 'suggest_tools', and doesn't specify prerequisites or exclusions, leaving some ambiguity.

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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