Mechanize, Inc. is a software company that builds reinforcement learning (RL) environments and evaluations for frontier coding agents and sells them to leading AI labs. In its environments, models carry out software engineering work such as building a feature, deploying an application or debugging an unfamiliar codebase, and a grader scores the result for use as RL training signal and evaluation. Its published work includes GBA Eval, a benchmark measuring whether coding agents can write a Game Boy Advance emulator from scratch in 24 hours. Mechanize publishes no public API, developer documentation or pricing on its website.
Mechanize is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Reinforcement Learning, AI Evaluations, and Benchmarks.
Mechanize’s developer surface includes engineering blog, support, and 9 more developer resources.
Regulatory Posture applies to this provider. Its tags matched the
Horizontal (data, software, accessibility, platform) regime, so
Regulatory Posture carries 15 points of the composite.
If this regime is wrong for your business, say so on your
provider repo — the
applicability map is public and we will correct it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero:
never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and
several others — scorable at all.
The six quality facets above are damped to 85 points between them,
because the conditional facet above carries the other
15. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 85% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
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<a href="https://apis.io/providers/mechanize-work/"><img src="https://apis.io/badge/mechanize-work/card.svg" alt="Mechanize on APIs.io — Kin Score by API Evangelist"></a>
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Agent readiness — checks not met, largest first (exact, from this profile):
Machine-Readable Auth+10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency+9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
A2A Agent Card+8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
12 more unmet checks in the Agent Readiness table above.
Kin Score — facets with the most composite points still available (weight × headroom):
aid: mechanize-work
name: Mechanize
description: Mechanize, Inc. is a software company that builds reinforcement learning (RL) environments and evaluations for
frontier coding agents and sells them to leading AI labs. In its environments, models carry out software engineering work
such as building a feature, deploying an application or debugging an unfamiliar codebase, and a grader scores the result
for use as RL training signal and evaluation. Its published work includes GBA Eval, a benchmark measuring whether coding
agents can write a Game Boy Advance emulator from scratch in 24 hours. Mechanize publishes no public API, developer documentation
or pricing on its website.
url: https://artifacts.apis.io/mechanize-work/apis.yml
x-type: company
x-source: harvest:direct-request
x-tier: profiled
x-tier-reason: enrichment pass 2026-10-27 (modular-v1; was harvest)
specificationVersion: '0.20'
created: '2026-10-27'
modified: '2026-10-27'
tags:
- Company
- Artificial Intelligence
- Reinforcement Learning
- AI Evaluations
- Benchmarks
- Coding Agents
- Software Engineering
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
- FN: APIs.json
email: info@apis.io
image: https://www.mechanize.work/social-card-square.png
common:
- type: Hosts
url: hosts/mechanize-work-hosts.yml
- type: Vendors
url: vendors/mechanize-work-vendors.yml
- type: DomainSecurity
url: security/mechanize-work-domain-security.yml
- type: Website
url: https://www.mechanize.work/
- type: Blog
url: https://www.mechanize.work/blog/
- type: Blog
url: https://www.mechanize.work/technical-blog/
name: Technical blog
- type: Newsroom
url: https://www.mechanize.work/press-releases/
name: Press releases
- type: Newsroom
url: https://www.mechanize.work/press/
name: Press
- type: Podcast
url: https://www.mechanize.work/podcast/
- type: Careers
url: https://www.mechanize.work/apply/
- type: Support
url: https://www.mechanize.work/contact.html
name: Contact
apis: []
x-coverage:
state: covered
reason: identity-verified
detail: Website www.mechanize.work self-identifies as Mechanize, Inc. (title, meta description). No API, developer docs,
pricing, terms or privacy pages are published; GitHub org github.com/mechanize-work exists but does not link to the site,
so it was not recorded.
evidence:
- url: https://www.mechanize.work/
status: 200
- url: https://www.mechanize.work/blog/
status: 200
- url: https://www.mechanize.work/technical-blog/
status: 200
- url: https://www.mechanize.work/press-releases/
status: 200
- url: https://www.mechanize.work/press/
status: 200
- url: https://www.mechanize.work/podcast/
status: 200
- url: https://www.mechanize.work/apply/
status: 200
- url: https://www.mechanize.work/contact.html
status: 200
- url: https://www.mechanize.work/social-card-square.png
status: 200
x-enrichment:
date: '2026-10-27'
status: enriched
artifacts_added: 9
pass: modular-v1
engine: identity=anthropic,contract=anthropic,surfaces=anthropic,docs=anthropic,regulatory=anthropic
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