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Trigger Manage Tool

trigger_manage

Manage event-driven trigger rules to automate project execution based on signal conditions. Create, update, delete, list, and test rules that respond to signals from sources like Sentry, IMAP, or RSS feeds.

Instructions

Manage event-driven trigger rules. Actions: list, create (name, event, conditions, actions), update (trigger_id + fields), delete (trigger_id), test (trigger_id, sample payload — dry-run).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform: list, create, update, delete, test
statusNoFilter by status: active | paused
limitNoMax results (default 20, max 100)
nameYesDescriptive name for the rule
source_typeNoSignal source type to match (* = any). E.g. sentry, imap, telegram, rss*
project_idNoUUID of the project to trigger
conditionsNoConditions to match on signal payload. Keys are dot-notation field paths, values are {operator: value} objects. Operators: eq, neq, gte, lte, contains, not_contains, exists
input_mappingNoMap signal fields to project input_data. Keys are target fields, values are dot-notation source paths
cooldown_secondsNoSeconds between triggers (0 = no cooldown)
max_concurrentNoMax active runs before skipping trigger (-1 = unlimited)
rule_idYesUUID of the trigger rule
payloadNoSignal payload to test against. Use dot-notation to nest: {"metadata": {"severity": "error"}}
executeNoIf true, actually trigger the project run (default: false — dry run only)

Implementation Reference

  • The MCP gateway proxies all tool calls, including potential 'trigger_manage' requests, to the upstream FleetQ instance via HTTP/SSE. The actual logic resides on the server side of the FleetQ instance.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      return upstreamClient.callTool(request.params);
    });
    
    server.setRequestHandler(ListResourcesRequestSchema, async (request) => {
      return upstreamClient.listResources(request.params);
    });
    
    server.setRequestHandler(ReadResourceRequestSchema, async (request) => {
      return upstreamClient.readResource(request.params);
    });
    
    server.setRequestHandler(ListPromptsRequestSchema, async (request) => {
      return upstreamClient.listPrompts(request.params);
    });
    
    server.setRequestHandler(GetPromptRequestSchema, async (request) => {
      return upstreamClient.getPrompt(request.params);
    });
    
    const stdioTransport = new StdioServerTransport();
    await server.connect(stdioTransport);
Behavior3/5

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

Annotations are empty, so description carries full burden. It discloses 'dry-run' behavior for the test action, which is valuable. However, it omits mutation safety details (e.g., whether delete is permanent, if updates are atomic, or rate limits) that would typically appear in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely compact single-sentence structure with parenthetical action details. Information density is high with minimal redundancy. Minor deduction because the terminology shorthand (e.g., 'event' for source_type) sacrifices precision for brevity.

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

Completeness3/5

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

With 13 parameters, nested objects, and no output schema, the tool is complex. The description adequately covers the action dispatch pattern but fails to explain domain relationships (how triggers relate to projects/signals) or compensate for missing behavioral annotations. Terminology inaccuracies further reduce completeness.

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 coverage is 100%, providing baseline clarity. However, the description introduces terminology that conflicts with the schema: it references 'trigger_id' (schema uses 'rule_id'), 'event' (schema uses 'source_type'), and 'actions' (schema uses input_mapping/cooldown/max_concurrent). These mismatches could confuse parameter selection despite high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States clear verb-resource intent ('Manage event-driven trigger rules') and enumerates five specific actions (list, create, update, delete, test). However, it does not explicitly differentiate this tool from siblings like signal_manage or workflow_manage.

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

Usage Guidelines2/5

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

Lists available actions but provides no guidance on when to use this tool versus alternatives (e.g., signal_manage for ingestion vs trigger_manage for automation rules). No prerequisites, error handling, or selection criteria are mentioned.

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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