Skip to main content
Glama
Aggrete

Aggrete

Official

hr__recent_joiners

Identify recent hires on a team by listing employees who joined within a specified look-back window, with email, employee ID, and start date.

Instructions

[hr-personnel] List the people who joined a team within the last N months, with each person's email, employee id and start date. Use it to find recent hires on a team.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYesTeam name to report on, for example 'platform', 'sre' or 'sales-emea'.
monthsNoLook-back window in months (1 to 60). Defaults to 18.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changedv0.5.4
    • addedInput schema / properties / months / description
      Added value: +"Look-back window in months (1 to 60). Defaults to 18."
    • addedInput schema / properties / months / maximum
      Added value: +60
    • addedInput schema / properties / months / minimum
      Added value: +1
    • addedInput schema / properties / team / description
      Added value: +"Team name to report on, for example 'platform', 'sre' or 'sales-emea'."
  2. First observedv0.5.2

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that this is a listing operation and names the returned fields, which is useful. It does not mention ordering, pagination, whether 'joined' refers to team membership vs hire date, or any access/authorization considerations.

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?

Two short sentences with no filler. The primary action and resource are front-loaded, and the use-case sentence earns its place by guiding selection.

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?

For a simple read-only list tool with two parameters and no output schema, the description is largely sufficient: it states inputs, purpose, and expected output fields. It could be slightly more complete by clarifying edge cases around the time window or result ordering, but nothing critical is missing for correct invocation.

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 description coverage is 100%, so both parameters are already documented with examples and constraints. The description mostly restates the time-window concept ('within the last N months') and does not add significant new meaning beyond the schema.

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?

The description uses a specific verb ('List') and resource ('people who joined a team within the last N months'), and clarifies the returned fields: email, employee id, and start date. It is clearly distinct from sibling tools by topic, though it does not explicitly contrast itself with any sibling.

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 states a clear use case: 'Use it to find recent hires on a team.' This gives an agent a direct trigger condition for selecting the tool. It does not, however, list exclusions or explicitly contrast with nearby HR tools like hr__start_here or hr__leave_balance.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Aggrete/aggrete'

If you have feedback or need assistance with the MCP directory API, please join our Discord server