AvelinLabs Examples
Complete executable examples are maintained in the official AvelinLabs API examples repository.
The repository is the executable companion to these docs. It contains complete cURL and Python workflows, payloads, sample responses, Postman assets, Customer Grounding files, MCP configuration, and a local interactive demo. The documentation explains the decision concepts; the repository demonstrates how to call them.
If you are using examples to test fit in a product workflow, follow Evaluate AvelinLabs in your workflow alongside the sample payloads and responses.
For practical strong, weak, ambiguous, vague, and noisy input comparisons, see Input quality examples.
During beta, onboarding is API-first: register through the Platform API, verify your email, create a runtime API key, and use that key on product endpoints.
Example Categories
Section titled “Example Categories”Current public examples cover:
- platform onboarding
- runtime API key usage
- job analysis
- job classification
- occupation intelligence
- occupation alignment
- skill evidence
- confidence, uncertainty, and review-routing signals
- weak-signal and ambiguity handling
- labor market intelligence
- market context where available
- runtime authentication patterns
- Customer Grounding examples for authorized Runtime API Key contracts
- customer-operated MCP stdio configuration and tool calls
- a local interactive Customer Grounding demo
- API error handling
- readiness checks
Current Public Example Files
Section titled “Current Public Example Files”- payloads/job-analyze.json
- payloads/job-classify.json
- payloads/hr-service-role-intake.json
- payloads/occupation-candidates.json
- curl/occupation-candidates.sh
- python/occupation_candidates.py
- responses/occupation-candidates.example.json
- responses/job-analyze.example.json
- responses/job-classify.example.json
- responses/occupation.example.json
- responses/market-top.example.json
- responses/market-overview.example.json
- responses/health-ready.example.json
- responses/error-invalid-api-key.example.json
- docs/annotated-job-analyze-response.md
Customer Grounding Examples
Section titled “Customer Grounding Examples”Customer Grounding examples apply when the Runtime API Key contract includes /api/v1/grounding. They cover the source lifecycle, text and supported file ingestion, grounded Role Intelligence, evidence, traces, errors, cleanup, and the customer-operated MCP adapter.
The controlled-beta example collection includes:
- Customer Grounding example guide
- Python workflow
- cURL workflow
- Synthetic TXT, Markdown, PDF, and DOCX files
- MCP stdio launch guide
- MCP client configuration
- MCP tool calls
- Local interactive Customer Grounding demo
The examples do not imply production GA, connectors, OCR, vector retrieval, SDK support, a hosted MCP service, a production customer UI, or automated hiring decisions.
How to Read AvelinLabs Output
Section titled “How to Read AvelinLabs Output”confidence
Section titled “confidence”- Meaning: Overall confidence signal for the top result.
- Use it for: Routing and review, not as absolute truth.
trust_score
Section titled “trust_score”- Meaning: Trust-oriented score combining result strength and quality support.
- Use it for: Deciding whether the selected output has enough evidence behind it.
uncertainty.total
Section titled “uncertainty.total”- Meaning: Combined uncertainty signal.
- Use it for: Identifying inputs or matches that may need review.
decision.decision
Section titled “decision.decision”- Meaning: Routing label such as
AUTO_ACCEPT,REVIEW,REJECT, orAMBIGUOUS. - Use it for: Deciding whether to display, review, reject, or request more input.
job_signals
Section titled “job_signals”- Meaning: Skill, tool, task, or domain signals detected from the input.
- Use it for: Seeing what evidence the analysis used.
results[].onet_code
Section titled “results[].onet_code”- Meaning: Standard O*NET occupation code for a ranked candidate.
- Use it for: Storing, comparing, or enriching the occupation consistently.
matching_skills
Section titled “matching_skills”- Meaning: Skills or capabilities supporting the selected match.
- Use it for: Helping reviewers and client-facing teams explain why the result is relevant.
explanation.why_match
Section titled “explanation.why_match”- Meaning: Plain-English explanation for the candidate match.
- Use it for: Reviewing and presenting the output in context.
For a fuller field-by-field walkthrough, read docs/annotated-job-analyze-response.md.
For practical field-by-field usage guidance in the public docs, see the Response Field Reference.
For practical batch and workflow measurements, see Metrics you can derive from AvelinLabs responses.
Controlled-Beta Guidance
Section titled “Controlled-Beta Guidance”Use synthetic or explicitly approved customer-safe content. Store Runtime API Keys outside committed files and screenshots. The local demo is an evaluator tool, not a hosted product UI.
Contract Rule
Section titled “Contract Rule”Examples should not invent fields, endpoints, or response shapes. If an API area is early-stage or subject to change, the example should say so directly.