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approval-rules: check_action

approve_check_action

[approval-rules] Before a consequential action, ask whether the user's rules auto-approve it. Returns auto_approve, needs_approval (with a plain-English approval card and a link the user can tap) or deny. Free plan is watch-only: it reports what it WOULD decide and logs it for the weekly report, but nothing counts as approved, so ask your user as you normally would.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesThe action your agent wants to take.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers well: it enumerates the three return states (auto_approve, needs_approval, deny), describes the approval card and tappable link, and crucially discloses the free-plan watch-only behavior (nothing counts as approved, logged for the weekly report). It omits error/edge handling and any rate or auth context, keeping it just short of exhaustive.

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?

Three tight sentences, front-loaded with the purpose, then returns, then the plan caveat. None of it is redundant with the schema and every sentence carries actionable information.

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?

There is no output schema, and the description usefully names the three outcome states plus the plan-gated behavior, which is the key context an agent needs. It stops short of detailing the fields inside an approval card or decision response, but the essentials are present.

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 description coverage is 100% and every sub-field of the nested 'action' object (type, target, summary, amount_usd, reversible) is already documented in the schema. The description adds no parameter-level meaning beyond that, so the baseline of 3 applies despite the nested-object complexity.

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?

States a specific action ('check whether the user's rules auto-approve' a consequential action) with the resource and the pre-action timing. This clearly distinguishes it from siblings like approve_get_rules (reads rules) and approve_get_decision (retrieves a decision already made), since this tool is the pre-flight check.

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?

'Before a consequential action' gives an explicit trigger condition, and the free-plan sentence directs the agent to 'ask your user as you normally would' in that context. It does not, however, name alternatives such as approve_get_decision for reading an existing decision, so the routing is implied rather than spelled out.

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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