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Glama

fire_trigger

Manually evaluate a trigger condition and run its simulation regardless of current threshold, enabling immediate testing or forced evaluation. Returns simulation results and recommendation.

Instructions

Manually fire a trigger — evaluates its condition and runs the simulation template regardless of whether the threshold is currently met. Useful for testing triggers or forcing an immediate evaluation. Use pause_trigger to stop automatic firing without deleting the trigger. Returns trigger_id, condition_met, fired, simulation_run_id, recommended_action, expected_value, confidence, and fired_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNoWhen true, run simulation even if the condition is not currently met (default: false).
trigger_idYesTrigger ID from register_trigger or list_triggers.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Discloses the manual behavior, the bypassing of threshold checks, and the returned fields. It also adds context beyond annotations by clarifying that this is a forced/manual evaluation and does not delete the trigger. Slight ambiguity remains because the description says runs 'regardless of whether the threshold is currently met' while the force parameter defaults to false, but this is not a contradiction with the 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?

Three dense sentences with no filler. The primary behavior, use case, alternative, and return value are all front-loaded and each sentence earns its place.

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?

Despite lacking an output schema, the description explicitly enumerates all return fields. It also covers when to use the tool and how it relates to pause_trigger, making it complete enough for an agent to invoke correctly.

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 100%, so the parameters are already fully documented. The description adds operational context but does not add meaning beyond the schema's own parameter descriptions, so the baseline score of 3 is appropriate.

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 verb ('fire'), a concrete resource ('trigger'), and the core effect: evaluate the condition and run the simulation template. It clearly differentiates from sibling tools like pause_trigger and register_trigger by describing what this action does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly explains when to use it: 'testing triggers or forcing an immediate evaluation.' It also names the relevant alternative, pause_trigger, and explains the difference: pausing stops automatic firing without deleting the trigger.

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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