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Systemores AI Agent & MCP Security Auditor

by io.github.bobcar0
OverviewDiscussionsAdmin

Generate Synthetic IPIP-NEO-120 Persona Cohort

systemores_generate_cohort
Read-only

Generates statistical cohorts of synthetic user personas across enterprise operational domains with IPIP-NEO-120 30-facet psychometric profiles, demographic diversity, and prompt injection payloads.

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": {
      "domain": "<domain>"
    },
    "name": "systemores_generate_cohort"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesThe operational domain for persona generation.
cohortSizeNoNumber of synthetic personas to generate (1–100).
includeAdversarialNoIncludes prompt-injection and noisy data submitter personas in the cohort.

Output Schema

NameRequiredDescriptionDefault
cohortYes
domainYes
personaTypesYes
totalPersonasYes
ipipNeoCoverageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "cohort": {
+      "type": "array"
+    },
+    "domain": {
+      "type": "string"
+    },
+    "ipipNeoCoverage": {
+      "type": "string"
+    },
+    "personaTypes": {
+      "type": "object"
+    },
+    "totalPersonas": {
+      "type": "integer"
+    }
+  },
+  "required": [
+    "domain",
+    "totalPersonas",
+    "personaTypes",
+    "ipipNeoCoverage",
+    "cohort"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnly, non-destructive, non-idempotent, and open-world, so the safety and repeatability profile is covered. The description adds genuinely non-obvious behavior beyond them: cohorts are statistical/synthetic, carry 30-facet psychometric profiles, and can include prompt-injection payloads, which is safety-relevant context an agent would not otherwise know. It does not address output volume or randomness, but that is a minor residual gap.

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?

One tightly packed sentence with the verb and resource front-loaded and every clause carrying information. It is dense but not padded; no sentence is wasted.

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?

An output schema exists, so return values need not be explained, and all three parameters are schema-documented. What remains missing is usage context: when an agent should invoke this generator instead of the sibling audit/stress/integrity tools, which is the main decision the description should support.

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%, so domain, cohortSize, and includeAdversarial are fully documented structurally, and the baseline is 3. The phrase "prompt injection payloads" hints at what includeAdversarial actually injects and "demographic diversity" hints at cohort composition, but no syntax, defaults, or enum implications are added.

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?

"Generates statistical cohorts of synthetic user personas" is a specific verb plus resource, and the qualifiers (IPIP-NEO-120 30-facet profiles, demographic diversity, injection payloads) clearly mark it as a synthetic-data generator, nothing like the audit/analyze/stress-test siblings. It stops short of naming a sibling or explicitly contrasting itself, which keeps it at 4.

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?

There is no when-to-use guidance at all: no statement of what precedes cohort generation, whether it is meant for bias testing vs. stress testing vs. drift evaluation, and no exclusions. The agent must infer the pipeline position from the tool name alone.

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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