Install Jentic One Beta

Connect the HireLayer API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the HireLayer API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhirelayer.co%2Fhirelayer" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhirelayer.co%2Fhirelayer" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with HireLayer API.

Parse a resume into structured candidate fields from raw text or a file

Extract structured hiring criteria from a job description

Score how well a single candidate matches a given job

Rank a pool of candidates against one job opening

Resolve free-text skills to a normalized skills taxonomy

GET STARTED

Start building with HireLayer API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use HireLayer API for, with concrete tasks.

★ Resume Intake and Structuring

Convert incoming resumes into structured candidate records so an applicant tracking workflow can index skills, experience, and contact details automatically. The parser accepts raw text or a file and returns normalized fields synchronously, which removes the brittle regex parsing many teams maintain. Recruiting tools use this as the first step in an intake pipeline before matching or storage.

POST /api/v3/parser with the resume content and store the structured candidate fields the response returns.

Job-to-Candidate Matching

Rank a pool of candidates against a single role so recruiters see the strongest fits first. The API extracts structured criteria from the job description, then ranks candidates against it in one synchronous call per request. Hiring teams use this to shortlist applicants without hand-scoring every resume.

Call POST /api/v1/jobs/extract-criteria on the job description, then POST /api/v1/matching/job-candidates/rank with the candidate pool and return the ranked list.

Skills Normalization

Map free-text skills from resumes and job posts onto one consistent taxonomy so filtering and reporting stay comparable across sources. The API resolves raw skill strings to taxonomy entries and exposes the full taxonomy for reference. Data teams use this to deduplicate skill tags before loading candidate records into a search index.

POST /api/v1/skills/resolve with the raw skill strings and reconcile each result against the taxonomy returned by GET /api/v1/skills.

Agent-Driven Shortlisting

An AI agent builds a shortlist for an open role by parsing each applicant's resume and scoring it against the job, without a bespoke integration. Through Jentic the agent discovers the parsing and matching operations, loads their schemas, and chains the calls. This lets a recruiting assistant return a ranked shortlist directly from uploaded resumes.

Search Jentic for 'rank candidates for a job', parse each resume with POST /api/v3/parser, then POST /api/v1/matching/job-candidate to score and shortlist the strongest fits.

Key Endpoints

9 endpoints — the hirelayer api turns recruiting text into structured data: it parses resumes, extracts hiring criteria from job descriptions, scores and ranks candidates against a role, and resolves free-text skills to a shared taxonomy.

METHOD

PATH

DESCRIPTION

POST

/api/v3/parser

Parse a resume into structured fields

POST

/api/v1/jobs/extract-criteria

Extract hiring criteria from a job description

POST

/api/v1/matching/job-candidate

Score a candidate against a job

POST

/api/v1/matching/job-candidates/rank

Rank candidates for a job

POST

/api/v1/skills/resolve

Resolve free-text skills to the taxonomy

GET

/api/v1/skills

List the skills taxonomy

GET

/api/v1/me

Check an API key

POST

/api/v3/parser

Parse a resume into structured fields

POST

/api/v1/jobs/extract-criteria

Extract hiring criteria from a job description

POST

/api/v1/matching/job-candidate

Score a candidate against a job

POST

/api/v1/matching/job-candidates/rank

Rank candidates for a job

POST

/api/v1/skills/resolve

Resolve free-text skills to the taxonomy

GET

/api/v1/skills

List the skills taxonomy

GET

/api/v1/me

Check an API key

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring HireLayer by hand means attaching the X-API-Key header on every call and chaining the parse, extract-criteria, and ranking steps yourself. Through Jentic you install once, import HireLayer from the API Directory, store the key once, and your agent calls the recruiting operations in sequence.

Permission scoping

HireLayer sends resumes, jobs, and candidate pools inside the request body, so a rule bounds which operations your agent may call rather than which record. You can grant only the parser and matching operations and leave skills management out of the agent's reach.

Credential isolation

Your HireLayer API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'parse a resume' or 'rank candidates for a job', and Jentic returns the matching HireLayer operation with its input schema so the agent calls the right endpoint without reading the reference docs.

FAQs

Specific to using HireLayer API through Jentic.

Is there a HireLayer MCP server?

You do not need an MCP server to give your agent the HireLayer API. Jentic connects it directly from the API Directory: import HireLayer, store your API key once, and your agent calls the parsing and matching endpoints. Operations are discovered on demand, so no extra server's tool definitions load into the agent's context.

What authentication does the HireLayer API use?

The HireLayer API authenticates with an API key sent in the X-API-Key header, per its OpenAPI spec, and GET /api/v1/me lets you confirm a key is valid. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never reaches the agent's prompt or logs.

Can I rank candidates against a job with the HireLayer API?

Yes. POST /api/v1/matching/job-candidate scores a single candidate against a job, and POST /api/v1/matching/job-candidates/rank ranks a whole pool, both synchronously. You can first call POST /api/v1/jobs/extract-criteria to derive structured criteria from the job description.

What are the rate limits for the HireLayer API?

The HireLayer spec describes pricing in terms of credits, where a successful call costs one credit, rather than a fixed requests-per-minute ceiling. The spec does not publish a numeric rate limit, so check the HireLayer documentation at https://hirelayer.co/api-docs for current limits.

How do I parse a resume through Jentic?

Search Jentic with the query 'parse a resume', load the schema for POST /api/v3/parser, and execute it with the resume text or file to get structured fields back. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Can I limit what my agent is allowed to do with the HireLayer API?

Yes. HireLayer carries the resume, job, and candidate pool inside the request body, so a rule bounds which operations your agent may call rather than which record it touches. Allow only the operations the task needs, such as the parser and the matching endpoints, and every call the agent makes is logged.

HireLayer API

AI ReadinessAI-Aware (A-)70/100

See full scorecard

Official vendor OpenAPI document · agent-readyHR recruitingRecruiting AtsapiKey9 EndpointsREST

For Agents

Parse resumes, extract job criteria, score and rank candidates against a role, and resolve skills to a taxonomy, all behind one API key.

Use for: Parse this resume into structured fields, Extract the required skills and criteria from a job posting, Score how well a candidate fits this job, Rank these candidates for the open role

Not supported: Does not store candidates, schedule interviews, or post jobs to boards. Use for resume parsing, candidate matching, and skills resolution only.

The HireLayer API turns recruiting text into structured data: it parses resumes, extracts hiring criteria from job descriptions, scores and ranks candidates against a role, and resolves free-text skills to a shared taxonomy. Each call is synchronous and returns JSON, and five recruiting functions sit behind one API key. Use it to automate resume intake and candidate shortlisting without building separate parsing and matching services.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: ASignals: 4

98%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

25%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: A-Signals: 4

21%

Example Density

How richly the API is illustrated with examples.

93%

Example Validity

Percentage of examples that conform to their schemas.

72%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: B-Signals: 4

54%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

90%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: C-Signals: 1

50%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A-Signals: 1

78%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the HireLayer API to your agent

Capabilities

Start building with HireLayer API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

HireLayer API

Jentic AI Readiness Score

HireLayer API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness