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company_approvals

Review or progress approvals through their lifecycle; supplied proofs are verified while provider effects remain external.

Instructions

Inspect or advance approvals through its scoped lifecycle; supplied proofs are verified and provider effects remain external.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nowNo
engineNo
operationNolist
entity_refNo
project_idYes
bundle_jsonYes
payload_jsonNo{}

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

C2.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose two traits — supplied proofs are verified, and provider effects remain external — which is genuine, non-obvious context. However, it never explains what 'advance' does to the approval (approve/reject/escalate?), whether it is reversible, or what consequences verification failure has, leaving the mutating path under-disclosed.

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 a single compact sentence with the core action front-loaded, which is structurally economical. But the trailing clause ('supplied proofs are verified and provider effects remain external') is dense jargon that costs clarity far more than the brevity saves.

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?

The output schema covers return values, but this is a multi-operation tool (operation defaults to 'list') with seven parameters, zero schema descriptions, and zero annotations. The description leaves operation values, the lifecycle scope, proof semantics, and required payload structure unexplained — clearly insufficient for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for seven undocumented parameters, but it barely does. 'Supplied proofs' loosely maps to payload_json or bundle_json and 'advance' loosely maps to the operation field, yet project_id, bundle_json, payload_json, entity_ref, engine, and now are never explained, and the required bundle_json's structure is entirely undefined.

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 ('Inspect or advance approvals') and hints at a lifecycle, so it is not a tautology. However, 'through its scoped lifecycle' is vague — the scope is never defined — and the description does not distinguish this from siblings like list_pending_approvals, list_engine_approvals, get_approval_details, or decide_engine_approval, all of which plausibly overlap.

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 guidance on when to use this tool versus the many approval siblings in the list (list_engine_approvals, stripe_approve, decide_engine_approval, approve_task, etc.). The phrase 'scoped lifecycle' implies a delimiting condition but never states it, so an agent cannot infer the appropriate selection 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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