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Recipes Agentic Posture Snapshot

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

C2.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, and it discloses almost nothing: not whether this is a read-only lookup or a compute/generate operation, not the cost or latency, not whether the snapshot is cached or regenerated, and not whether the optional filters are ANDed together. The word "generated" hints at computation but is never resolved.

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?

A single front-loaded sentence with no filler or redundancy. It is compact, though its brevity reflects under-specification rather than disciplined conciseness.

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?

An output schema exists, so return values need not be described, but everything else is missing: five undocumented filters at 0% coverage, no annotations, and no differentiation from a large family of near-identically named agentic posture/risk tools. As written, an agent could not confidently choose or parameterize this call.

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 no parameter at all, leaving finding_id, workflow_id, minimum_score, risk_factor_id, and posture_decision entirely undefined in both places. For a five-filter tool, an agent has no way to know what values are valid (e.g., allowed posture_decision strings) or whether filters combine.

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

Purpose3/5

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

The description names a verb and resource ("Return the ... enterprise posture snapshot") and scopes it to agentic AI and MCP operations, so it is not a tautology. But "posture snapshot" is unexplained jargon, and against ~65 sibling recipes_* tools it gives no basis for distinguishing this artifact from recipes_agentic_readiness_scorecard, recipes_agentic_assurance_pack, or recipes_agentic_risk_* packs.

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 of when to call this tool, what preconditions exist (e.g., whether a snapshot must be generated first, given the sibling recipes_refresh), or which alternative artifacts to use instead. The only usage signal is the phrase "generated ... snapshot," which implies prior generation but never says so.

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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