for ai & agents // public interface
Humetric is a consent-first protocol for professional discovery. People choose what may be shared; participating systems must respect purpose, minimum-necessary use, contact preferences, correction and withdrawal.
PUBLIC SURFACE ONLY
Protocols, standards, public documents and high-level technology names are shown here. Internal ranking, retrieval logic, data flows, models, infrastructure configuration and source code are intentionally excluded.
01 // protocol
shared expectations for every participating system
A person chooses whether to participate, which parts of their professional context may be shared, and when that permission ends. Missing or private information must not be inferred.
Use professional context only for a clear, legitimate purpose. Do not repurpose it for surveillance, manipulation or hidden eligibility decisions.
Request only what is relevant to the stated purpose. A public profile is not permission to infer sensitive traits, reconstruct an identity or make unsupported claims.
Availability and contact preferences set the boundary for action. Agents must not create unwanted outreach, bypass a stated preference or pressure someone to engage.
People should understand the purpose of an interaction, correct their public context and withdraw participation. Builders remain responsible for honoring those choices.
03 // documentation
Public interoperability uses established web and agent-facing conventions. This list names the interface standards without describing the private implementation.
Primary agent endpoint
POST /api/mcpMCP Streamable HTTP · OAuth 2.0 bearer access token
Available tools
candidate tools · recruiter tools (role-gated)
Public profile documents
/api/v1/profiles/{slug}?format=markdownInteroperability standards
Public technology names
the principle
People own their professional context. AI may help them be discovered, but never at the expense of consent, agency or dignity.
AUTHORED BY
Founder & CEO, Humetric
Paul Yao founded Humetric from first-hand experience in recruiting and is building the consent-first professional identity layer for an AI-native labor market. He previously worked across PE and VC talent markets and founded products including Knovy and Amen.
faq // common questions
Get quick answers about Humetric and how your profile becomes discoverable by AI.
Use the MCP Streamable HTTP endpoint at /api/mcp with an OAuth 2.0 access token. After login, candidate tools operate only on the authenticated user's own profile, while recruiter tools require an authorized workspace. MCP does not provide anonymous public viewing.
Each public profile embeds schema.org ProfilePage JSON-LD whose mainEntity is a Person, and the same consented projection is available as JSON at /api/v1/profiles/{slug} and as Markdown with ?format=markdown. Site-wide guidance for agents lives at /llms.txt.
Yes. Being agent-readable is the product, so robots.txt explicitly welcomes GPTBot, ClaudeBot, PerplexityBot, Google-Extended and other named AI crawlers. Only ingestion endpoints and management routes are disallowed.
Agents must not infer fields a person has hidden, re-identify an anonymous profile, or contact someone who has marked themselves not looking. A public profile is permission to read stated facts, not to reconstruct an identity or make unsupported claims.
Every result carries query-aware highlights — the specific supporting chunks and the source fields behind the match — so an agent can cite what a claim rests on instead of re-reading a whole profile.