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accelo_list_request_threads

List request threads grouped with their activity and linked objects. Filter by standing, type, staff, or date to retrieve specific threads.

Instructions

List request threads on the deployment.

A request thread groups a request with its activity thread. Returns a "requests" array plus a "linked_objects" array of objects linked to those requests.

Args: filters: Filter dict. Keys: standing, request_type_id (the request type_id), interact_from_staff (staff_id), date_created_before/after page: Page number (0-indexed) limit: Results per page (max 100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
filtersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully describes the return structure (a 'requests' array and a 'linked_objects' array) and notes that the page is 0-indexed and limit has a max of 100. However, it doesn't disclose any permission requirements, rate limits, or error behaviors.

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?

The description is appropriately sized and front-loaded with the core purpose and return information. The 'Args' section is a standard, readable structure. There is little wasted text, making it easy for an agent to parse.

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?

For a read-only list tool with no output schema, the description is nearly complete. It explains the return format and the key input constraints. It could be improved by including pagination behavior (e.g., whether the response includes a total count) or basic usage examples, but it covers the essentials well.

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

Parameters4/5

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 does so effectively by detailing the `filters` dictionary keys (`standing`, `request_type_id`, `interact_from_staff`, `date_created_before/after`) and their expected value types, plus clarifying that `page` is 0-indexed and `limit` has a max. This adds significant meaning beyond the bare schema.

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?

The description uses a clear verb+resource ('List request threads') and adds valuable conceptual context by defining what a request thread is ('groups a request with its activity thread'). This helps distinguish it from `accelo_list_requests` and `accelo_list_activity_threads`, though it doesn't explicitly name those siblings.

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?

The description states what the tool does but provides no guidance on when to use it versus alternatives. An agent must infer its use case from the definition alone, with no explicit 'use this when...' or 'for X, use Y instead' instructions.

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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