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accelo_list_addresses

Find and filter Accelo addresses for companies or contacts by type, ID, postal or physical status, and location fields.

Instructions

List addresses from Accelo.

Addresses store location info for companies and contacts. Each address can be postal, physical, or both. Use filters against_type and against_id to find addresses for a specific company or contact.

Args: filters: Filter dict. Keys: id, against_type, against_id, physical, postal, country_id, state_id, zipcode, order_by_asc/desc (id, title) fields: Additional fields, e.g. "country(),state(),street1,city" page: Page number (0-indexed) limit: Results per page (max 100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
fieldsNo
filtersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It explains the address types (postal, physical, both) which is useful domain context, but does not disclose permission requirements, pagination behavior beyond limit, or whether results are sorted. Adequate but incomplete for a tool with zero annotation coverage.

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?

Front-loaded with purpose, then behavior, then parameter details in a clear Args section. Efficient, though slightly verbose in the filter key enumeration but that's necessary given 0% schema coverage.

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?

Covers purpose, domain context, filtering strategy, and parameter specifics. Missing explicit mention of return format or total count behavior, but for a list tool with no output schema, this is largely sufficient for an agent to call 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?

Schema description coverage is 0%, so the description must compensate, and it does well by listing filter keys (id, against_type, against_id, physical, postal, country_id, state_id, zipcode, order_by_asc/desc), explaining fields example syntax, and noting page is 0-indexed and limit max 100. This adds substantial meaning beyond the bare schema types.

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+resource ('List addresses from Accelo') and immediately explains what addresses are and how they relate to companies and contacts. Distinguishes itself from sibling get_address and create_address by clearly being the list operation.

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?

Explicitly tells the agent when to use filters ('Use filters against_type and against_id to find addresses for a specific company or contact'), which is clear context. However, it doesn't name alternatives or state exclusions (e.g., when to use get_address instead).

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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