Data Model

A Skill Card consists of four files. scoutica.json is the entry point; it points consumers to the other three files.

File relationships

scoutica.json
  └── discovers → profile.json
                    ├── has → skills[]
                    ├── has → tools_and_platforms[]
                    ├── has → certifications_and_licenses[]
                    └── speaks → spoken_languages[]

rules.yaml
  ├── engagement → allowed_types, compensation
  ├── remote → policy, hybrid_locations
  ├── filters → blocked_industries, stack_keywords, soft_reject
  └── privacy → zone_1_public, zone_2_paid, zone_3_private

evidence.json
  └── items[]
        ├── type, title, url, description
        └── skills_demonstrated[]

---

scoutica.json

The discovery file. Place this at the root of any GitHub repository to declare that it contains a Scoutica Protocol card.

Field	Type	Required	Description
scoutica	string	✅	Protocol version (e.g. "0.1.0")
card_url	string	✅	Base URL for fetching the other card files
name	string	✅	Display name of the card owner
title	string	—	Professional title
seniority	string	—	Seniority level (e.g. "senior")
domains	string[]	—	Primary domains (e.g. ["Backend Engineering"])
availability	string	—	Availability status (e.g. "in_2_weeks")
entity_type	string	—	Entity type: human, ai_agent, service, robot, team, organization
updated	string	—	ISO 8601 date of last update

{
  "scoutica": "0.1.0",
  "card_url": "https://raw.githubusercontent.com/user/my-card/main",
  "name": "Alex Chen",
  "title": "Senior Full-Stack Engineer",
  "seniority": "senior",
  "domains": ["Backend Engineering", "Cloud Infrastructure"],
  "availability": "immediately",
  "entity_type": "human",
  "updated": "2026-03-23"
}

---

profile.json

The candidate’s professional profile. This is the primary data file.

Field	Type	Required	Description
schema_version	string	✅	Schema version (e.g. "0.1.0")
name	string	—	Full professional name
title	string	✅	Current professional title
seniority	string	✅	Seniority level: entry, junior, mid, senior, lead, manager, director, executive
years_experience	integer	—	Total years of professional experience
availability	string	—	One of: immediately, in_2_weeks, in_4_weeks, in_8_weeks, not_looking
primary_domains	string[]	✅	Top-level professional domains (min 1 item)
skills	string[]	✅	Professional skills as a flat list (min 1 item)
tools_and_platforms	string[]	—	Tools, equipment, software, platforms used
certifications_and_licenses	string[]	—	Professional certifications or licenses
specializations	string[]	—	Niche areas of deep expertise
spoken_languages	object[]	—	Languages spoken; each item has language (string) and level (native|fluent|professional|basic)
education	string	—	Highest relevant education or training
summary	string	—	2–3 sentence professional summary (max 1000 chars)

{
  "schema_version": "0.1.0",
  "name": "Alex Chen",
  "title": "Senior Full-Stack Engineer",
  "seniority": "senior",
  "years_experience": 10,
  "availability": "immediately",
  "primary_domains": ["Backend Engineering", "Cloud Infrastructure", "API Design"],
  "skills": ["Python", "TypeScript", "Go", "REST API Design", "CI/CD Pipelines"],
  "tools_and_platforms": ["FastAPI", "React", "Kubernetes", "Docker", "AWS", "PostgreSQL"],
  "certifications_and_licenses": ["AWS Solutions Architect Associate"],
  "specializations": ["Event-Driven Architecture", "Infrastructure as Code"],
  "spoken_languages": [
    {"language": "English", "level": "native"},
    {"language": "Mandarin", "level": "fluent"}
  ],
  "education": "BSc Computer Science, UC Berkeley",
  "summary": "Full-stack engineer with 10 years building cloud-native applications."
}

---

rules.yaml

The candidate’s Rules of Engagement. Agents must evaluate these before contacting a candidate.

Field	Type	Required	Description
schema_version	string	✅	Schema version
engagement.allowed_types	string[]	✅	Accepted engagement types: permanent, contract, fractional, advisory, internship
engagement.compensation.minimum_base_eur	object	—	Min compensation by type: permanent (annual), contract (daily), advisory (hourly)
remote.policy	string	✅	One of: remote_only, hybrid, flexible, on_site
remote.hybrid_locations	string[]	—	Acceptable locations for hybrid roles
filters.blocked_industries	string[]	—	Industries the candidate refuses to work in
filters.stack_keywords.preferred	string[]	—	Preferred tech keywords for match scoring
filters.soft_reject.weak_stack_overlap_below	integer	—	Min keyword matches; below this → SOFT_REJECT
privacy.zone_1_public	string[]	✅	Fields visible to everyone (free)
privacy.zone_2_paid	string[]	✅	Fields visible after micro-fee payment
privacy.zone_3_private	string[]	✅	Fields shared only after candidate ACCEPT

schema_version: "0.1.0"

engagement:
  allowed_types:
    - permanent
    - contract
  compensation:
    minimum_base_eur:
      permanent: 80000
      contract: 600

remote:
  policy: "remote_only"

filters:
  blocked_industries:
    - "gambling"
    - "weapons"
  stack_keywords:
    preferred:
      - "Python"
      - "Kubernetes"
  soft_reject:
    weak_stack_overlap_below: 3

privacy:
  zone_1_public:
    - title
    - seniority
    - primary_domains
    - availability
  zone_2_paid:
    - full_profile
    - evidence
  zone_3_private:
    - email
    - phone
    - exact_salary

---

evidence.json

Verifiable links that prove the candidate’s skills.

Field	Type	Required	Description
schema_version	string	✅	Schema version
items	array	✅	List of evidence items
items[].type	string	✅	Type: github_repo, website, portfolio, certificate, article, review, reference, photo, video, case_study, publication, other
items[].title	string	✅	Display name of the evidence
items[].url	string	✅	Public URL to the evidence
items[].description	string	✅	What this evidence proves about the candidate
items[].skills_demonstrated	string[]	✅	Skills this evidence proves (min 1 item)

{
  "schema_version": "0.1.0",
  "items": [
    {
      "type": "github_repo",
      "title": "CloudDeploy — Kubernetes Deployment Toolkit",
      "url": "https://github.com/alexchen/cloud-deploy",
      "description": "Open-source Kubernetes deployment toolkit with GitOps workflow.",
      "skills_demonstrated": ["Kubernetes", "Go", "CI/CD Pipelines"]
    },
    {
      "type": "certificate",
      "title": "AWS Solutions Architect Associate",
      "url": "https://www.credly.com/badges/example-badge-id",
      "description": "Validates expertise in designing distributed systems on AWS.",
      "skills_demonstrated": ["AWS", "Cloud Infrastructure"]
    }
  ]
}

---

Schema validation

All card files have corresponding JSON Schema definitions:

File	Schema	Location
profile.json	candidate_profile.schema.json	protocol/platform/01_schemas/
rules.yaml	roe.schema.json	protocol/platform/01_schemas/
evidence.json	evidence.schema.json	protocol/platform/01_schemas/
scoutica.json	scoutica_discovery.schema.json	schemas/

Validate your card with the CLI:

scoutica validate ./my-card/

Or programmatically with jsonschema:

import json, jsonschema

with open('protocol/platform/01_schemas/candidate_profile.schema.json') as f:
    schema = json.load(f)

with open('profile.json') as f:
    profile = json.load(f)

jsonschema.validate(profile, schema)  # raises ValidationError if invalid