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approve_rule

Idempotent

Promote a rule discovered by discover_patterns into Blueprint-ready form.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesGeodesicAI API key (gai_...)
rule_idYesDiscovered rule ID from discover_patterns
blueprintNoBlueprint name (workflow_name) to usedefault

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / api_key / description
      Added value: +"GeodesicAI API key (gai_...)"
    • addedInput schema / properties / blueprint / description
      Added value: +"Blueprint name (workflow_name) to use"
    • addedInput schema / properties / rule_id / description
      Added value: +"Discovered rule ID from discover_patterns"
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare idempotentHint=true and destructiveHint=false, so the safety profile is known. The description adds that this is a promotion action on discovered rules, but does not disclose additional behavioral traits such as reversibility, side effects, or required permissions. No contradiction with annotations.

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

Conciseness5/5

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

A single sentence that is front-loaded with the action and resource, then specifies the target state. Zero wasted words; every phrase contributes to understanding the tool's purpose.

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 straightforward state-change tool with full schema coverage and idempotency annotations, the description is sufficiently complete. It doesn't explain output format or failure modes, but those are not essential for the core promotion action. The source-to-target relationship is clearly stated.

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% — every parameter has a description in the schema, including api_key format, rule_id origin, and blueprint default. The description itself does not discuss parameters, but the schema carries the full burden. Baseline 3 is appropriate.

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

Purpose5/5

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

'Promote' is a specific verb, and the description clearly defines the resource ('a rule discovered by discover_patterns') and the outcome ('Blueprint-ready form'). This distinguishes it from sibling tools like reject_rule or create_blueprint, making the tool's purpose unmistakable.

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?

The description implicitly indicates the tool should be used on rules that came from discover_patterns, which provides clear context for when to invoke it. It doesn't explicitly point to alternative tools or state when not to use it, but the prerequisite is unambiguous and sufficient for most usage scenarios.

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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