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Glama

dialog_policy

Destructive

Set automatic responses for browser dialogs by defining a session default or adding text-match rules for future dialogs. Already-seen dialogs stay recorded and are not affected.

Instructions

Answer dialogs from now on. match=None sets the session default; with a match, adds a rule for dialogs whose text contains it (an earlier rule with the same text is replaced). Applies to future dialogs only; dialogs already seen stay recorded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
matchNo
actionNoaccept

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations indicate destructiveHint=true, readOnlyHint=false, and the description adds valuable behavioral details: it applies only to future dialogs, existing dialogs stay recorded, and earlier rules with the same text are replaced. This goes beyond annotations and clarifies side effects. No contradiction with annotations.

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 three concise sentences, front-loaded with the core purpose ('Answer dialogs from now on') followed by precise rule semantics. No filler or redundancy; every sentence earns its place.

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 output schema exists (so return values are covered) and annotations provide safety hints, the description covers the key behavioral scoping (future-only, replacement) and explains the match parameter well. It omits a full list of possible actions and how to clear the policy entirely, but for a policy-setting tool this is arguably adequate. The session-scoped nature is mentioned via 'session default'.

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 coverage is 0%, so the description must compensate. It explains 'match' thoroughly: null sets the session default, a string adds a rule based on text containment, and replacements occur. However, 'action' is only mentioned via its default 'accept' and the phrase 'Answer dialogs'; possible values or their effects are not explained. This leaves a gap for the agent.

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's purpose: 'Answer dialogs from now on' – a specific verb and resource. It distinguishes itself from sibling 'dialogs' (which likely lists current dialogs) by focusing on setting future policy. The semantics of match and action are introduced, making the tool's role unambiguous.

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 clear context: it sets a session default or adds a rule, and applies to future dialogs only. It does not explicitly name alternatives or exclusions, but the purpose is distinct enough that an agent can infer when to use it (e.g., to automate dialog handling). No explicit 'when not to use' is given, but the context is sufficient.

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