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Hiring report (Excel / CSV / data)

hiring_report

Build hiring reports for open vacancies with funnel by stage, hires, disqualifications, average rating, time to first reply, and candidates overdue for reply. Export as Excel, CSV, or JSON.

Instructions

Build a hiring report across all open vacancies (or the ones given): funnel per stage, hired, disqualified, average rating, time to first reply, and the list of candidates who have waited more than reply_sla_days without any reply. format=xlsx writes an Excel file (sheets: Summary, Needs reply, Active, All candidates); csv writes one flat table (easy to import into Google Sheets); json returns the data only, e.g. to push it into a Google Sheet with another connector.

Input Schema

NameRequiredDescriptionDefault
formatNoxlsx
output_pathNoAbsolute path. Default: ~/Documents/Homerun Reports/homerun-report-YYYY-MM-DD.<ext>
vacancy_idsNoDefault: all public and private vacancies
include_closedNo
reply_sla_daysNoFlag active candidates with no reply after this many days (default 5)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.9/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=false, destructiveHint=false, openWorldHint=true, so the safety profile is thin; the description compensates by disclosing the side effect (writing a file), the exact sheets produced for xlsx, and that returns data only for piping into another connector. It still omits permission/auth requirements and overwrite behavior for output_path.

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 the report's contents before the format mechanics; no filler sentences. The format explanation is dense but the long parenthetical with three format behaviors makes it slightly harder to scan.

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 usefully describes what each format returns, so an agent knows what it gets back. A mutation-adjacent tool (writes a file, sets readOnlyHint=false) would benefit from naming permission or overwrite expectations, but coverage is otherwise solid for its complexity.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 60%. The description adds real meaning for format (per-value output differences) and restates the reply_sla_days and vacancy-scope defaults, but leaves include_closed entirely undocumented in both schema and description, and says nothing about output_path semantics.

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 and resource ('Build a hiring report across all open vacancies') and enumerates the exact metrics produced: funnel per stage, hired, disqualified, average rating, time to first reply, and overdue candidates. This is well differentiated from siblings like pipeline_summary or list_job_applications.

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

Usage Guidelines3/5

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

The description explains what each format value does, which implies when to pick xlsx vs csv vs json, but it never contrasts this tool with candidates like pipeline_summary or says when not to use it. Usage is implied rather than stated.

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