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pre_deploy_check

Check audit findings against strict, standard, or lenient quality gates to decide if deployment can proceed. Returns gate decision with blocking findings and warnings.

Instructions

Evaluate audit findings against a pre-deployment quality gate profile.

Use this tool when the user asks to:

  • Check whether audit findings block deployment or meet quality criteria.

  • Validate findings against 'strict', 'standard', or 'lenient' governance gates.

Args: findings_json: List or JSON string of audit findings to evaluate. profile: Gate profile to evaluate against ("strict", "standard", "lenient").

Returns: Dict with gate decision (passed=True/False), blocking findings, and warnings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileNostandard
findings_jsonNo[]

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.11.0
    • removedInput schema / properties / findings_json / type
      Removed value: -"string"
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the return payload (gate decision, blocking findings, warnings), which is useful, but says nothing about side effects, permissions, or whether the check is purely read-only or has any deployment impact.

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?

The description is front-loaded with the core purpose, then uses clean labeled sections (usage bullets, Args, Returns) that make it easy to scan. It is slightly longer than strictly necessary given the output schema, but nothing is wasteful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter, zero-required, non-destructive evaluation tool, both parameters are described and the return shape is sketched (even though a real output schema exists). The only gap is the absence of any behavioral/permission context, which is minor for this kind of gate-check tool.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate, and it does: it documents both parameters, clarifying that findings_json accepts a list or JSON string, and enumerating the 'strict'/'standard'/'lenient' profile values that the schema leaves unspecified.

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 states a specific verb and resource ('Evaluate audit findings against a pre-deployment quality gate profile'), which is clear and actionable. It is reasonably distinguishable from siblings like audit_model_and_report, though it never explicitly contrasts itself with any of them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit 'use this tool when the user asks to' guidance with two concrete scenarios, which is stronger than most. However, it names no alternatives and gives no when-not-to-use conditions, so it falls short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.