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Workforce-Cloud-Tech

Recruit CRM MCP Server

Get Pitch History

get_pitch_history
Read-only

Fetch pitch history for any Recruit CRM candidate or contact using their slug, returning compact pitch entries without sensitive fields.

Instructions

Fetches pitch history for one Recruit CRM candidate or contact by slug. Set entity_type to candidate for candidate pitch history, or contact for contact pitch history. Returns compact pitch entries without email, phone, resume, or profile image fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_slugYesCandidate slug when entity_type=candidate, or contact slug when entity_type=contact.
entity_typeYesEntity type for the pitch lookup.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
historyYes
entity_slugYes
entity_typeYes
returned_countYes
Behavior4/5

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

The annotations already declare read-only and non-destructive behavior. The description adds valuable context about the response format, specifically noting that it returns compact pitch entries without email, phone, resume, or profile image fields, which helps set expectations beyond what annotations provide.

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 concise, consisting of two sentences that front-load the core purpose and then provide essential parameter and response details. Every sentence contributes value without unnecessary verbosity.

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?

For a simple read-only lookup with two parameters and an output schema, the description is sufficiently complete. It covers the purpose, parameter behavior, and response characteristics, and no significant gaps are apparent for an AI agent to use the tool 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 schema already provides full descriptions for both parameters, achieving 100% coverage. The description further clarifies parameter semantics by explicitly stating that entity_type determines whether the lookup is for a candidate or contact, and that the lookup is performed by slug, adding meaningful guidance beyond the raw 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?

The description clearly states the tool fetches pitch history for a single candidate or contact by slug, using the specific verb 'Fetches' and identifying the resource as 'pitch history'. It distinguishes itself from sibling tools like get_candidate_details or get_pitched_records by focusing on pitch history for one entity.

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 explains how to use the entity_type parameter to choose between candidate and contact pitch history, providing clear context for when to use this tool. However, it does not explicitly mention alternative tools or when not to use this tool, so it stops short of full usage guidance.

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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