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recipes_agentic_posture_snapshot

Return the generated enterprise posture snapshot for agentic AI and MCP operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
finding_idNo
workflow_idNo
minimum_scoreNo
risk_factor_idNo
posture_decisionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, and it only reveals that the tool returns a pre-generated snapshot. It does not disclose whether filters are applied, whether a single object or a collection is returned, whether the call can create or refresh anything, or what authorization or resource requirements exist.

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

Conciseness3/5

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

The single sentence is readable and front-loads the action and object, but it is also under-specified. The shortness is not harmful, yet the missing parameter and usage detail means the structure is minimal rather than fully useful.

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?

For a tool with five optional but undocumented parameters and no annotations, this definition is incomplete: it does not explain filter semantics or how the snapshot is selected. Having an output schema helps with the return shape, but not with the input contract or when to call this tool.

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

Parameters1/5

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

Schema description coverage is 0%, and the description mentions none of the five parameters (finding_id, workflow_id, minimum_score, risk_factor_id, posture_decision). An agent cannot tell what minimum_score means, whether filters are combined, or which identifier is required to retrieve a specific snapshot.

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 names a specific action (Return), a specific resource type (generated enterprise posture snapshot), and a domain (agentic AI and MCP operations), so an agent can tell this is a retrieval tool. It does not explicitly distinguish among the many recipe_* siblings, such as recipes_get or recipes_agentic_readiness_scorecard, so it misses full sibling differentiation.

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 statement about when to use this snapshot over the many sibling recipes, when not to use it, or whether it should be called before generating or refreshing a snapshot. The word 'generated' weakly implies an existing artifact, but no alternative or precondition is mentioned.

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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