Application Screening

Screen Every Applicant, Instantly

Use StackOne to connect your AI agent to your ATS, document stores, and messaging tools to automate application screening and shortlisting.

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AI Agents

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MCP and A2A to REST, SOAP, and proprietary APIs.

Optimize

Tool discovery, data shaping, and reliable execution.

Secure

Scoped permissions, audit trails, and observability.

StackOne Integration Layer

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StackOne Integration Layer

Connect

200+ connectors, build your own, and multi-protocol support.

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Optimize

Context, token, and speed optimization infrastructure.

Falcon execution engine →

Secure

Permissions API and prompt injection protection.

Agent governance and safety →

What Can AI Agents Do for Application Screening?

Your agent detects new applications, parses resumes, scores candidates against job criteria, and delivers a ranked shortlist to recruiters.

01

Detect New Applications

Monitor incoming applications across Greenhouse, Lever, Ashby, or Bullhorn. Capture new candidates as they arrive via ATS webhooks or inbox polling.

02

Parse Resumes and Applications

Extract structured candidate data — skills, experience, education — from resumes and application forms stored in the ATS or attached via Google Drive. Handle PDF, DOCX, and plain-text formats.

03

Deduplicate and Normalize

Standardize extracted fields and check for existing candidate records in the ATS to prevent duplicate profiles. Merge new data into existing records when a match is found.

04

Score and Rank Candidates

Compare candidate profiles against job requirements using weighted criteria — skill match, years of experience, education, location fit — and assign tier rankings with explainable rationale.

05

Deliver Shortlist to Recruiters

Push top candidates with scores and match rationale into the recruiter's ATS queue in Greenhouse, Lever, SmartRecruiters, or Teamtailor.

06

Notify the Recruiter

Send a summary alert via Slack or Gmail highlighting top matches, key strengths, and screening rationale so the recruiter can act immediately.

01

Detect New Applications

Monitor incoming applications across Greenhouse, Lever, Ashby, or Bullhorn. Capture new candidates as they arrive via ATS webhooks or inbox polling.

02

Parse Resumes and Applications

Extract structured candidate data — skills, experience, education — from resumes and application forms stored in the ATS or attached via Google Drive. Handle PDF, DOCX, and plain-text formats.

03

Deduplicate and Normalize

Standardize extracted fields and check for existing candidate records in the ATS to prevent duplicate profiles. Merge new data into existing records when a match is found.

04

Score and Rank Candidates

Compare candidate profiles against job requirements using weighted criteria — skill match, years of experience, education, location fit — and assign tier rankings with explainable rationale.

05

Deliver Shortlist to Recruiters

Push top candidates with scores and match rationale into the recruiter's ATS queue in Greenhouse, Lever, SmartRecruiters, or Teamtailor.

06

Notify the Recruiter

Send a summary alert via Slack or Gmail highlighting top matches, key strengths, and screening rationale so the recruiter can act immediately.

Why Building a Good Screening Agent Is Hard

Connecting to Many ATS Platforms

A screening agent needs connectors to Greenhouse, Lever, Ashby, Bullhorn, SmartRecruiters, and Teamtailor. Each has different APIs, auth flows, pagination logic, and rate limits. Building and maintaining each connector is a massive lift.

Auth Complexity Across Providers

Greenhouse uses API keys with per-endpoint permissions. Lever uses OAuth 2.0 with token refresh rotation. Bullhorn demands session-based authentication. Managing each method and refreshing credentials mid-screening adds serious engineering burden.

Token Cost Grows with Application Volume

Without a search-first approach, the agent pre-loads every ATS action definition — list candidates, get applications, move stages, download resumes — burning tokens before processing a single resume. The problem compounds at high application volume.

Resume Content Carries Prompt Injection Risk

Resumes are untrusted text. Malicious candidates embed hidden instructions in PDF metadata, white-on-white font, or invisible text to manipulate scoring logic or auto-promote themselves past screening criteria.

How StackOne Makes Screening Agents Possible

Everything your screening agent needs to parse applications, score candidates, and deliver shortlists — with the controls your team demands.

200+ connectors with 10K+ agent-optimized actions

Pre-built connectors for Greenhouse, Lever, Ashby, Bullhorn, SmartRecruiters, Teamtailor, and more — each with full native action coverage and agent instructions included.

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Managed Auth handles credentials across ATS providers

OAuth flows, API keys, and token refresh managed per tenant for every connected ATS — agents never touch raw credentials.

Search and execute finds the right action

Agent searches StackOne's action catalog by natural language and executes the matching ATS action — no pre-loading thousands of tool definitions into the context window.

Falcon handles pagination and rate limits

StackOne's execution engine manages retries, rate limiting, and pagination per ATS provider. One action call returns the complete candidate list with built-in back-off logic.

Connector Studio extends to any system

Build custom connectors for unsupported ATS platforms or internal screening systems via REST, SOAP, or GraphQL — no waiting on vendor support.

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Defender blocks prompt injection from resume content

StackOne Defender screens inbound resume text for injection attempts before the agent processes it, preventing adversarial content from corrupting screening decisions.

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You Control What the Agent Can Do

Scoped permissions define exactly which candidate fields the agent reads and which ATS actions it can trigger. Full audit trail of every operation for GDPR and EEOC compliance.

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Integrates with your entire recruiting stack. Whatever it is.

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Connect Any Agent to Automate Application Screening

Any Agent Framework

Claude, OpenAI, LangChain, Vercel AI SDK, CrewAI, Pydantic AI — StackOne works with every major agent framework out of the box.

Any Agent Builder

Whether you're building with code, a visual builder, or an enterprise platform — StackOne provides the integration layer your agent needs.

MCP REST API A2A

Any Protocol

Pick the protocol that fits your stack. Tool calling, direct API integration, agent-to-agent messaging, or structured action workflows — all supported out of the box.

Connect Your Agent to Your Recruiting Stack

Start building in minutes. MCP connectors to every ATS your agent needs.

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Frequently Asked Questions

The hardest part is connecting to every customer's ATS — Greenhouse, Lever, Ashby, and Bullhorn each have different APIs, auth flows, and pagination logic. Beyond connectors, the agent must parse resumes from proprietary file stores, score candidates against job criteria, and handle prompt injection hidden in resume text.

Three challenges dominate: integration breadth (each ATS has unique auth and endpoints), context window cost (tool definitions alone can consume 55,000+ tokens before processing a single resume), and security — staffing firms report finding hidden prompt injection text in roughly 10% of AI-scanned resumes.

Each system uses a different auth model. Greenhouse requires API keys with per-endpoint permissions, Lever uses OAuth 2.0 with token refresh rotation, and Bullhorn demands session-based authentication. Building and maintaining each connector — plus handling pagination and rate limits — typically costs $20,000-$50,000+ per integration.

Each customer authorizes their own ATS through a managed auth layer that handles OAuth flows, API key storage, and token refresh per tenant. The screening agent authenticates via a single scoped token regardless of whether the underlying system is Greenhouse, Lever, SmartRecruiters, or Teamtailor — no per-provider auth code required.

Instead of pre-loading every action definition — list candidates, get applications, move stages, download resumes — a search-first approach lets the agent query an action catalog by natural language and load only the tools it needs. This cuts token consumption from tens of thousands to hundreds per screening run.

Resumes are untrusted text. Candidates embed invisible instructions in PDF metadata, white-on-white font, or tiny text to manipulate scoring. A prompt injection guard inspects inbound resume content before it reaches the agent's reasoning loop, flagging payloads that attempt to override screening criteria or auto-promote candidates.

High-volume roles generate hundreds of applicants, and each ATS paginates differently — Greenhouse uses Link headers, Lever uses body cursors, Workable uses offsets. StackOne's execution engine abstracts pagination and rate-limit back-off per provider, so one action call returns the complete candidate list without the agent managing retries.

The agent should only access applications, candidates, and job records — never payroll or personal addresses. A scoped permissions model restricts readable and writable resource types per integration, and request-level observability logs every ATS call with endpoint, timestamp, and status for audit trails required by GDPR and EEOC reporting.