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Dry-run a draft through the guardrail to see if it passes, gets held, or is blocked, with reasons. Fix issues before posting without bypassing the guard.

Instructions

Dry-run a draft through the casserole guardrail WITHOUT posting: returns whether it would pass, be held, or be blocked, and why. Use it to fix a draft before posting or scheduling. This is a linter, never a way to bypass the guard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
aiGeneratedNo

Schema Changelog

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

  1. First observedv0.1.3

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description fully carries the behavioral disclosure burden. It clearly communicates the non-destructive nature ('WITHOUT posting', 'linter'), what it returns (pass/held/blocked and why), and the guardrail caveat. It omits authentication or rate-limit details, but for a dry-run linter this is strong transparency.

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?

Two sentences, front-loaded with the core action and constraints. Every clause earns its place: the dry-run behavior, return value, intended use case, and the warning that it is not a bypass. No fluff.

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?

Given the simple 2-parameter schema, no annotations, and no output schema, the description covers the essential context: purpose, when to use, return value, and safety. The only notable gap is the undocumented aiGenerated parameter, preventing a perfect score.

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. It relates the required 'text' to 'a draft', but the optional 'aiGenerated' boolean is never mentioned. The agent gets no guidance on when or how to set that parameter, leaving a meaningful gap.

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 states a specific verb ('Dry-run'), the resource ('a draft through the casserole guardrail'), and the exact outcome ('returns whether it would pass, be held, or be blocked, and why'). 'WITHOUT posting' and the linter framing clearly distinguish it from siblings like post_now.

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 gives explicit timing ('before posting or scheduling') and a clear when-not ('never a way to bypass the guard'). It does not name alternative sibling tools explicitly, but the context makes it obvious that actual posting requires a different tool.

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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