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CISO Assistant MCP Server

Api crq quantitative risk studies object retrieve

ciso_assistant_api_crq_quantitative_risk_studies_object_retrieve
Read-onlyIdempotent

Retrieve a quantitative risk study by ID from CISO Assistant to access its details for analysis.

Instructions

api_crq_quantitative_risk_studies_object_retrieve

Input Schema

NameRequiredDescriptionDefault
idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.6

TDQS

C2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered structurally. The description adds nothing beyond that - no note on permissions, object-not-found behavior, or whether the payload is heavy. It does not contradict the annotations, but it contributes zero behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single token string with no wasted words, but that is under-specification rather than conciseness - there is no front-loaded statement of purpose or scope. Length is fine; content is the problem.

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?

There is no output schema, so the description carries the burden of saying what a quantitative risk study object record contains and why one would fetch just one - it does neither. Given the density of CRQ siblings, an agent cannot confidently select or invoke this tool from the definition.

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 description coverage is 0% and the description supplies no meaning for the single required `id` parameter - not its type, format (UUID? slug? ref_id?), nor which identifier space it belongs to. The schema alone gives only `type: string`, so the description fails to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is verbatim the tool name ("api_crq_quantitative_risk_studies_object_retrieve"), so it only restates the identifier rather than stating in prose what the tool does. An agent can infer from the slug that it fetches an object, but nothing distinguishes it from the sibling `ciso_assistant_api_crq_quantitative_risk_studies_retrieve` or explains what an "object" variant means here.

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?

No when-to-use, when-not-to-use, or alternative is named. With nearby siblings `..._studies_retrieve`, `..._studies_list`, `..._studies_object_retrieve` and numerous computed endpoints (`ale_comparison`, `key_metrics`, `combined_ale`), the agent is left guessing which one to pick.

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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