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Comradery64

open-greenhouse-mcp

by Comradery64

list_applications

Retrieve job applications with filters for candidate, status, or date range. Use to monitor recruitment pipeline activity and incoming submissions.

Instructions

List applications with optional filters. Read-only.

Users say "show me applications for [job name]" or "what came in this week." To filter by job: list_jobs → find by name → use its job_id. To filter by candidate: search_candidates_by_name → candidate_id. For pipeline views grouped by stage, use pipeline_summary. For stale candidates, use stale_applications or candidates_needing_action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (starts at 1)
job_idNoFilter to applications on this job
statusNoFilter by status: 'active', 'rejected', or 'hired'
paginateNo'single' for one page, 'all' to auto-fetch every pagesingle
per_pageNoResults per page (max 500)
candidate_idNoFilter to applications for this candidate
created_afterNoISO 8601 datetime — only applications created after this
created_beforeNoISO 8601 datetime — only applications created before this
last_activity_afterNoISO 8601 datetime — only applications with activity after this

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the burden, and it clearly states 'Read-only.' This is a key behavioral trait. It also hints at date-range filtering via the example 'what came in this week,' adding practical context beyond the schema.

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 compact, front-loaded with the core purpose, and every sentence adds value: the read-only note, user intent examples, filtering workflow, and alternatives. No wasted words.

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?

Given the tool has an output schema and 100% parameter descriptions, the description covers the remaining context thoroughly: user scenarios, inter-tool dependencies, and sibling alternatives. It is complete for a list tool of this complexity.

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 meaning by explaining how to obtain job_id and candidate_id through list_jobs and search_candidates_by_name, which is not in the schema. This extra workflow guidance earns a 4.

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 'List applications with optional filters' with a specific verb and resource. It also distinguishes from sibling tools by naming alternatives like pipeline_summary, stale_applications, and candidates_needing_action.

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?

It provides explicit user phrasing examples ('show me applications for [job name]', 'what came in this week') and workflows for filtering by job or candidate. It also names alternative tools for pipeline views and stale candidates, giving strong when-to-use 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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