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accelo

List issues (tickets)

list_issues
Read-only

List issues — support/service tickets. Accelo API: GET /api/v0/issues. Supports _page/_limit/_fields/_filters/_search. Returns { meta, response }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo_page: 0-indexed page number (default 0).
limitNo_limit: max objects to return (1–100, default 50).
fieldsNo_fields: comma-separated extra fields to include in each object, or "_ALL" for every available field.
searchNo_search: free-text search across the object's searchable fields.
filtersNo_filters: Accelo filter string, function-like and comma-separated. E.g. status(1), date_created_after(1704067200), order_by_desc(date_created), search(acme). Suffix _not for negation; combine with _OR(...)/_AND(...). Passed through verbatim as _filters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

readOnlyHint=true already establishes the safety profile, so the description is not burdened with that. It usefully adds the pagination/filtering mechanism (via _page/_limit/_filters) and the return envelope '{ meta, response }', which matters because no output schema exists. It still omits rate limits or default page size nuance.

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?

A single compact line: resource, endpoint, capability list, and return shape, with the core purpose front-loaded and no wasted phrasing.

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 5-param read-only list tool with fully documented schema, the description covers purpose, endpoint, filter mechanics, and the response envelope, compensating for the absent output schema. It stops short of usage routing or edge-case notes, but nothing critical is missing.

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 description coverage is 100%, so every parameter is fully documented in the schema itself; the description merely echoes the parameter names. Baseline of 3 is appropriate when the schema carries the semantic load.

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 a specific verb+resource ('List issues') and clarifies the resource domain as 'support/service tickets', plus the underlying API call GET /api/v0/issues. It does not differentiate itself from siblings such as get_issue or list_tasks, so it falls short of a 5.

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?

There is no guidance on when to use this versus get_issue or the other list_* siblings. The mention of supported query params is a capability statement, not a usage condition, leaving the agent to infer selection.

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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