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optimize-overseas

LACRM MCP Server

Get Emails For Contact

get_emails_attached_to_contact

Retrieve all logged emails for a contact with full field data, or use count_only mode to get just the total count and breakdowns.

Instructions

Retrieve all logged emails for a specific contact. RETURNS FULL DATA: Each result includes all email fields - no need to call get_email afterward. Use count_only=true for accurate counts without returning the full result set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination
contact_idYesThe ContactId to get emails for
count_onlyNoWhen true, auto-paginates and returns only total count and breakdowns (no results array).
max_resultsNoMax results (default 500)
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 discloses that all email fields are returned and that count_only changes the response shape, which is useful. However, it omits other behavioral details such as pagination semantics, ordering, or potential rate limits, making it adequate but not thorough.

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?

Three sentences, each earning its place: first states the core purpose, second delivers the key call-saving benefit, third gives a conditional usage hint. No filler or redundancy.

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?

With no output schema, the description partially covers return values by noting full email fields and count_only's count/breakdowns. It also implicitly covers pagination via schema params. For a 4-parameter read tool, this is reasonably complete, but it does not detail the count breakdown structure or pagination defaults, leaving some gaps.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying the effect of count_only (returns total count and breakdowns, no results array) and emphasizing full data return, which helps the agent understand parameter trade-offs without re-reading schema.

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?

Description clearly states the verb 'Retrieve' and resource 'all logged emails for a specific contact', making the tool's purpose unambiguous. It distinguishes from sibling tools like get_email (single email) and search_emails (search across contacts) by scoping to a contact and returning all emails.

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

Usage Guidelines5/5

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

Explicitly tells the agent not to call get_email afterward ('RETURNS FULL DATA... no need to call get_email afterward'), and provides a specific conditional for when to use count_only=true for count-only use cases. This gives clear when-to-use and when-not-to-use guidance relative to a sibling tool.

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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