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list_engine_approvals

List pending engine transition approvals for operator review, including engine, entity, stop reason, and approval impact. Output as markdown or JSON.

Instructions

List pending company-engine transition approvals, rendered for an operator.

Each item shows which engine wants which transition on which entity, why the engine stopped, and what approving does. Freshness against the persisted state is checked by the SDK's InboxOperator, which also resumes the engine after a decision; this tool renders and never decides. output="json" returns the sealed inbox (items with their engine bindings) instead of markdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.1

TDQS

A3.8/5.0
Behavior4/5

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

The description explicitly states 'this tool renders and never decides,' clearly indicating it is a read-only operation. It also mentions the underlying InboxOperator mechanism for freshness, providing useful behavioral transparency beyond the absent annotations.

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 description is moderately verbose and repeats similar phrasing ('renders' appears twice, 'inbox' is mentioned in multiple places). While not excessively long, it could be tightened to reduce redundancy while retaining essential details.

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?

The description provides sufficient context about the tool's purpose, the content of each item, the parameter, and its non-decision-making behavior. It does not explicitly address relation to sibling tools or error handling, but for a simple list tool it is reasonably complete.

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?

The description explains the 'output' parameter by showing that setting it to "json" returns the sealed inbox instead of markdown, giving meaningful insight into the parameter's effect. However, it does not enumerate all possible values or provide formal schema-level documentation.

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?

The description clearly states the tool lists pending company-engine transition approvals, with a specific verb ('List') and resource ('pending company-engine transition approvals'). It also details what each item shows, making the purpose unambiguous.

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?

The description lacks explicit guidance on when to use this tool versus alternatives like list_pending_approvals. It does not mention when to prefer this tool or what distinguishes it from sibling tools, leaving the agent to infer usage context.

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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