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Glama

accelo_get_context

Retrieve Accelo object model, relationships, and query guide to construct correct multi-step queries. Call before complex queries to traverse linked companies, jobs, issues, and tasks.

Instructions

Get the Accelo object model, relationships, and query guide.

Call this FIRST before making complex queries. Returns:

  • Object hierarchy (how companies, jobs, issues, tasks, etc. relate)

  • The 'against' pattern (how objects link to their parents)

  • How to resolve any activity back to its company

  • Field selection syntax (_fields parameter)

  • Filtering and pagination conventions

  • Common query patterns (time by staff, issues by company, etc.)

This context enables you to correctly traverse relationships and construct multi-step queries across the Accelo data model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

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?

With no annotations, the description carries the full burden. It discloses the tool's output content in detail (hierarchy, against pattern, field selection, filtering, pagination, common patterns) and frames it as read-only retrieval, but it does not explicitly state read-only safety, side effects, auth needs, or rate limits.

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 front-loaded with the purpose and the critical 'Call this FIRST' instruction, then uses a tight bullet list for the return contents. Every sentence earns its place and the structure makes scanning easy.

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?

Given the tool's zero-parameter, context-guide nature and the presence of an output schema, the description is complete enough. It explains what the tool is, when to call it, and what kind of information it returns, leaving nothing essential missing for an agent to use it correctly.

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?

The tool has zero input parameters, so the baseline is 4. The description mentions the '_fields parameter' only as part of the query guide returned, not as an input to this tool, so there is no parameter semantics to add or misuse.

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 states a specific verb (Get) and resource (Accelo object model, relationships, and query guide), making its purpose unmistakable. It is clearly a meta/context tool that is distinct from all the CRUD and listing siblings, so an agent can identify it without opening other schemas.

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 explicitly says 'Call this FIRST before making complex queries,' which gives clear when-to-use guidance. However, it does not state when not to use it (e.g., simple queries) or name alternative context tools like describe_object, so it stops short of the full when/when-not/alternatives standard.

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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