Pohang University of Science and Technology
Pohang University of Science and Technology (POSTECH) is a private research university in Pohang, North Gyeongsang, South Korea, founded in 1986 by the steelmaker POSCO and consistently ranked inside the QS world top 100. POSTECH operates no developer portal, no open-data program and no API it authored itself — but it is not empty, and three genuinely institution-operated machine-readable surfaces were verified live on 2026-08-30, all of them on POSTECH's own network (141.223.0.0/16). The OASIS institutional repository serves a fully anonymous OAI-PMH 2.0 harvesting endpoint over a corpus of 106,805 records in twelve metadata formats across 163 sets, reaching back to 2014. POSTECH runs its own SAML 2.0 identity provider at idpass.postech.ac.kr, registered in the KAFE federation since 2017 and resolvable through eduGAIN, supporting the REFEDS Research and Scholarship entity category and asserting SIRTFI — machine-readable institutional infrastructure that almost nothing in this cohort catalogues. And POSTECH's LMS publishes a live, public LTI 1.3 Advantage platform keyset and OAuth 2.0 token endpoint, which most institution-hosted Moodles keep unreachable. Everything else is a login wall or someone else's platform: the PODIUM portal, admissions and certificate systems are gated; the DSpace REST interface sits behind a JavaScript bot challenge that returns 200 with a challenge shell; and the thesis pipeline runs through postech.dcollection.net, a tenancy on the KERIS-operated national dCollection platform, recorded here as a relationship rather than as POSTECH's engineering.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Pohang University of Science and Technology the way a machine reads it — 11 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Pohang University of Science and Technology scores 34.6/100 (thin), with a separate agent-readiness read of 26/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-09-08 · rubric v0.20.0
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How we profile Pohang University of Science and Technology
Each block below is one kind of artifact we hold for Pohang University of Science and Technology. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 5
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
POSTECH OASIS Repository OAI-PMH
Anonymous OAI-PMH 2.0 metadata harvesting over the POSTECH Library OASIS institutional repository. Verified live on 2026-08-30: repositoryName "OASIS Repository@POSTECHLIBRARY",...
POSTECH SAML 2.0 Identity Provider
POSTECH's own SAML 2.0 identity provider, entityID https://idpass.postech.ac.kr/idp/simplesamlphp, registered in KAFE (the Korea Access Federation, run on KREONET) since registr...
POSTECH LMS (PLMS) LTI 1.3 Advantage Platform
POSTECH's learning management system is an institution-hosted Moodle (coursemos distribution) acting as an LTI 1.3 Advantage platform, and unusually for this cohort its platform...
POSTECH LMS (PLMS) Moodle Web Services
The Moodle Web Services REST interface is enabled on POSTECH's LMS and is publicly reachable, but every anonymous call returns the moodle_exception errorcode invalidtoken. Token...
POSTECH dCollection Thesis Repository (KERIS tenancy)
POSTECH's tenancy on dCollection, the Korea Education and Research Information Service national digital thesis and dissertation distribution system. The relationship is evidence...
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the things the Kin Score reads for access clarity — renamed from commercial clarity in rubric 0.12, because a free statutory interface has access terms and no commercial ones.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Postech Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Postech Finops
FINOPSSemantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Postech Context
JSON-LDSecurity Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Pohang University of Science and Technology — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Design & Contract 3
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 1
Status, limits, changes, and where to get help
Commercial 4
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 3
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/postech · machine-readable index on apis.io
This is an independent, third-party profile of Pohang University of Science and Technology, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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