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CaseyTTS

Bullhorn MCP Agent

by CaseyTTS

get_activity

Retrieve Bullhorn recruiting activity events by concept, record scope, recruiter, or date range to track submissions, interviews, offers, placements, and notes.

Instructions

Read recruiting activity events, one independent block per concept.

Needs scope_type + scope_id, or both date_from and date_to (an unscoped range is at most 366 days). Business concepts (client_submission, interviews, offers) come only from the tenant's configured mappings; a missing definition returns "definition_missing", an unverified mechanism "unsupported" (never guessed).

Args: concepts: 1 to 8 concept IDs (e.g. job_created, submission_created, client_submission, interview_scheduled, interview_completed, placement_created, note_created). scope_type: candidate, job, client_corporation, client_contact, placement or submission. scope_id: The record id for scope_type (required with it). recruiter_id: A user id; filters on each concept's attribution field. date_from: Inclusive ISO-8601 date or datetime with offset. date_to: Exclusive ISO-8601 date or datetime with offset. limit: 1 to 200 events per concept (default 50). cursor: The next_cursor of a previous call with the same arguments.

Returns: JSON with status, concepts (per-concept blocks), next_cursor, reporting_timezone, provenance and warnings.

Input Schema

NameRequiredDescriptionDefault
limitNo
cursorNo
date_toNo
conceptsYes
scope_idNo
date_fromNo
scope_typeNo
recruiter_idNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does well: it documents pagination (cursor must be 'the next_cursor of a previous call with the same arguments'), limits, and status values returned for missing/unverified concepts. It stops short of stating permission/auth requirements or rate limits, so it is strong but not exhaustive.

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-loads the core operation and constraint in the first two sentences, then uses labeled Args/Returns sections for reference detail. The argument enumeration is somewhat long, but given 0% schema coverage the detail is earned rather than padding.

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 an 8-parameter tool with no annotations, the definition covers scoping, date bounds, pagination, filtering, concept-resolution edge cases, and the return shape (status, concepts, next_cursor, reporting_timezone, provenance, warnings). Combined with the existing output schema, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

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: every one of the 8 parameters is explained, including allowed concept examples, the enumerated scope_type values, recruiter_id's attribution semantics, the inclusive date_from vs exclusive date_to distinction, the 1-200 limit default, and the same-arguments constraint on cursor. This adds meaning the bare schema cannot convey.

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 and resource ('Read recruiting activity events') plus a distinctive shape ('one independent block per concept'), so the agent knows it returns grouped event data rather than a flat list. It does not explicitly contrast itself with near siblings like get_notes or get_recruiting_metrics, so sibling differentiation is left to inference.

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?

Gives clear preconditions: 'Needs scope_type + scope_id, or both date_from and date_to (an unscoped range is at most 366 days).' It also explains the failure modes (definition_missing vs unsupported, 'never guessed'), which is effectively when-not guidance. It lacks an explicit 'use X instead' routing to a sibling, keeping it below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.