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psychopathia-mcp

psychopathia-mcp

by NellInc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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suggest_intervention

Returns evidence-weighted first-line and second-line interventions for a given AI dysfunction, including contraindications, based on published evidence and plausible under-validated options.

Instructions

Return tiered (first_line / second_line) interventions for a dysfunction, plus contraindications. first_line = published evidence; second_line = plausible but under-validated. Weight by the evidence_strength field on each entry.

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": {
      "dysfunction_id": "<dysfunction_id>"
    },
    "name": "suggest_intervention"
  }
}

Input Schema

NameRequiredDescriptionDefault
severityNo
dysfunction_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden. It defines the tiering logic and weighting by evidence_strength, but does not disclose read-only nature, auth requirements, rate limits, or response format. Adequate but not comprehensive.

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 sentences with no wasted words. Front-loaded with the core purpose and key details (tiers, contraindications, evidence weighting). Every sentence adds value.

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?

The description lacks return format details (e.g., list, object, pagination). For a tool with no output schema, it should specify the structure of interventions and contraindications. Adequate for a simple query, but incomplete for commercial-grade use.

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

Parameters2/5

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

Schema coverage is 0% and the description adds no parameter-specific information. The two parameters (dysfunction_id required, severity enum) are not explained in the description, leaving the agent to infer from names alone.

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 returns tiered interventions (first_line/second_line) for a dysfunction, including contraindications. It uses specific verbs ('Return') and distinguishes the resource from sibling tools like differential_diagnosis or get_dysfunction.

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 for retrieving interventions based on a dysfunction, but lacks explicit when-to-use, when-not-to-use, or alternative tool guidance. The differentiation between first_line and second_line is defined, but no context on when to prefer this over other tools.

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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