greenhouse-pipeline-search

greenhouse-pipeline-search is a skill for Claude Code, Codex from Comradery64/open-greenhouse-mcp. It costs 153 tokens per session (774 once invoked), scanned A, original, MIT.

A recruiting workflow for searching Greenhouse pipelines, which are lists of candidates moving through hiring stages, using filters such as skills, experience, location, or stage.

In plain words
What is it for?
Use it to find matching candidates across one or more Greenhouse pipelines, or across all pipelines.
Why use it?
It avoids manually scrolling through candidates when looking for people who match specific requirements.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find matching candidates across one or more Greenhouse pipelines, or across all pipelines.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Comradery64/open-greenhouse-mcp --skill greenhouse-pipeline-search
Clone the repo
git clone --depth 1 https://github.com/Comradery64/open-greenhouse-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for greenhouse-pipeline-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search/github.svg)](https://agentmods.dev/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search)
Your own site
<a href="https://agentmods.dev/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search"><img src="https://agentmods.dev/badge/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for greenhouse-pipeline-search

Your own site · 80×15
<a href="https://agentmods.dev/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search"><img src="https://agentmods.dev/badge/skills/comradery64/open-greenhouse-mcp/greenhouse-pipeline-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 153 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 774 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00153 $0.00774
Opus 5 $0.00077 $0.00387
Sonnet 5 $0.00031 $0.00155
Haiku 4.5 $0.00015 $0.00077

Measured 11d ago against content hash 54ad68b9e427, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

greenhouse-pipeline-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/greenhouse-pipeline-search/SKILL.md · 40 lines

How it starts

The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Finds candidates across a pipeline (or across all pipelines) matching criteria the recruiter cares about, without them having to manually scroll through Greenhouse.

When this applies

Trigger when the user is looking for candidates that match some filter — a skill, years of experience, location, current stage, source, or a combination. If they name one specific person, that's greenhouse-candidate-screening instead. If they want you to review an entire unfiltered batch of resumes for a role (no specific filter, just "look at everyone"), that's greenhouse-resume-batch-review.

How to do it

  1. Clarify scope if it's ambiguous: which job/pipeline (or "all"), and what the actual filter criteria are. If the user says something vague like "find good candidates," ask what "good" means for this search (specific skills? years of experience? something else?) rather than inventing criteria — a wrong guess wastes their time reviewing results that don't match what they meant.
  2. Use search_pipeline_candidates for criteria-based search within a pipeline, or scan_pipeline_resumes when the match criteria live in resume content itself (e.g. specific technologies, certifications, or experience described in free text rather than structured fields).
  3. If the user's criteria span multiple pipelines/jobs, run the search per job and combine — don't silently narrow to just one job because it's easier.
  4. Rank or order the results in a way that's actually useful — e.g. best-match first, or by pipeline stage — rather than returning them in raw API order.

Output format

## Pipeline search — [criteria] in [job/pipeline scope]

Found N matching candidates:

| Candidate | Stage | Why they match |
|---|---|---|
| [name] | [stage] | [specific evidence from resume/profile, not a generic restatement of the criteria] |

If zero candidates match, say so plainly and suggest loosening the criteria — don't pad the response with near-misses unless you also label them clearly as near-misses.

Read the full file on GitHub · 40 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 40 lines · 153 tokens per session scan A 54ad68b9e427

Subscribe to this mod's changes

greenhouse-pipeline-search is a skill published in the GitHub repository Comradery64/open-greenhouse-mcp (0 stars, last pushed 8d ago), licensed MIT. It adds 153 tokens to every session and 774 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens