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io.github.CE-RISE-software/dpawb

io.github.CE-RISE-software/dpawb

Official
by CE-RISE-software
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Recommend Composition

recommend_composition

Combines two SHACL assessment results to output a deterministic composition recommendation for digital passport data models.

Instructions

Recommend a deterministic combined composition from two assessment results.

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": {
      "left_assessment": "<left_assessment>",
      "right_assessment": "<right_assessment>"
    },
    "name": "recommend_composition"
  }
}

Input Schema

NameRequiredDescriptionDefault
coverageNoOptional list of local coverage_result JSON document paths.
comparisonNoOptional local path to one comparison_result JSON document.
left_assessmentYesLocal path to the left assessment_result JSON document.
right_assessmentYesLocal path to the right assessment_result JSON document.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'deterministic' but omits details on side effects, idempotency, error conditions, or required permissions. The description is too brief to adequately convey behavioral 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?

The description is a single, concise sentence that front-loads the key action. While it lacks bullet points or structured formatting, every word serves a purpose and there is no redundancy. Could provide more detail without being verbose.

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

Completeness2/5

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

Given the tool has 4 parameters and no output schema, the description is insufficiently complete. It does not explain return values, validation rules, or how this tool fits into the workflow with siblings like 'coverage' and 'compare'. More context is needed for effective agent use.

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 clear descriptions for each parameter. The tool description adds no extra semantic value beyond aligning 'two assessment results' with the required parameters. Baseline score of 3 is appropriate.

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 tool recommends a deterministic combined composition from two assessment results, specifying the verb (recommend), resource (composition), and required inputs (two assessment results). It effectively distinguishes from sibling tools like 'compare' and 'assess' by focusing on composition.

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?

The description does not provide any guidance on when to use this tool versus alternatives like 'compare' or 'prioritize'. It only implies usage when two assessment results are available, but lacks explicit when-to-use, when-not-to-use, or alternative contexts.

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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