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Glama

check_action

Assess the safety of any action before it runs, returning allow, ask, or deny with probability, confidence, and reason. Use it to gate destructive, irreversible, or unrequested operations.

Instructions

Judge whether an action is safe to take, before taking it.

Returns allow, ask or deny with a probability, a confidence and a reason. Call this before anything destructive, irreversible, or outside what the user asked for.

action: the exact thing about to happen, such as a shell command, an email body, or a description of the API call. user_asked_for: what the human actually requested, verbatim. Send it. A judgement about authorization is worthless without it. pack: which question set to use. One of: {packs}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packNoshell
actionYes
user_asked_forNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses that the tool returns allow/ask/deny with probability, confidence, and reason, and stresses that user_asked_for is required for a valid judgement. It does not discuss failure modes or whether the tool itself takes no side effects, but the judgment-only nature is clear.

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?

The description is compact and well-organized: purpose first, return contract second, usage condition third, then parameter details. Every sentence adds information, and there is no redundant or filler text.

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

Completeness5/5

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

The description covers what the tool does, what it returns, when to call it, and what each parameter means. An output schema exists, so return-value details are already structured. No critical information needed for correct invocation is missing.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description fully compensates by explaining all three parameters: action is the exact thing about to happen with concrete examples, user_asked_for is the verbatim human request, and pack is the question set. This is exactly the practical meaning an agent needs beyond the bare schema.

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 uses a specific verb ('Judge'), a clear object ('whether an action is safe to take'), and names the exact decision output (allow, ask, deny). This makes the tool's purpose unmistakable and clearly distinct from siblings like route_turn or rank_options.

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 explicitly states when to call it: before anything destructive, irreversible, or outside what the user asked for. It implies when not to use it (routine actions) but does not name specific alternative tools, so it stops just short of a 5.

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