OpenAI API by OpenAI

# Fix list: OpenAI API

From Anchor Terminal's listing at https://www.anchorterminal.com/tools/openai-api, the October 2026 research run, assessed 1 October 2026. Grade A, 82.8 out of 100.

This is everything the published grade says the listing lacks, the biggest possible gain to the total first. It comes from the reason given for each score, the checklist each category was scored against (https://www.anchorterminal.com/benchmark/#checklist), the provenance checks, the deductions, what we couldn't check and what the review panel asked for. A fix counts at the next check, once it's public.

For a coding agent working on OpenAI API: work through the items below in the product, its docs and its public pages. Each category gives the reason for its score, with the points each checklist item earned, and the checklist itself, so the gap is the items that earned less than their points. Change the product, not the wording, and keep a note of what you changed and where it's published.

## 1. Payments & pricing, 30 out of 100, up to 8.8 more on the total

Why it scored 30: No machine payment protocol (0). Per-token prices published without a login (20). The rate-limits page lists a Free tier in allowed countries with a $100 monthly cap, but the GPT-6 model pages say Free isn't supported, so half (10). Signing up and making a key need a person in a browser (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-payments):

The published rubric, also on the [x402 page](https://www.anchorterminal.com/x402/).

- 40, a machine payment protocol (x402, MPP or L402) on the tool's own endpoints. 10 to 30 when it covers only some endpoints or only goes through a third party, and the note says which.
- 20, per-call or per-unit pricing published without a login. 10 for public plan-only pricing, 0 for "contact sales" or prices behind a login.
- 20, a free tier or trial that doesn't need a card.
- 20, autonomous onboarding, meaning an agent can get access without a person signing up in a browser (keyless use, x402, a programmatic key API).

Payment platforms and agent wallets rarely charge for their own API over a machine protocol, so the first line has steps for them, and the highest one that applies counts. 40 when x402, MPP or L402 runs on all their own endpoints, 30 when it runs on part of their own API, 25 when their merchants can accept one, 20 for running a facilitator, 15 for paying as a buyer, and 0 when the only protocol is their own. Merchant acceptance sits above a facilitator because the platform's own customers can charge agents through it, while a facilitator settles for sellers who wire up the protocol themselves. The counter-argument (a facilitator does more for the protocol as a whole) has a point. Each note says which step applied.

Open-source software you run yourself is scored on its hosted or paid option if it has one. A free, self-hosted package with nothing to buy gets 20, 20 and 20 for the last three lines, and 0 to 40 for the first only if it ships a payment protocol.

## 2. Reliability, 70 out of 100, up to 6 more on the total

Why it scored 70: Status page at status.openai.com with component history (20). Several API-wide error incidents in the last 90 days, elevated errors across ChatGPT, Codex and the API for about 5 hours 20 minutes on 29 September, elevated error rates across API models for about 90 minutes on 17 September, and widespread elevated errors on 25 July, so several majors (0). Tier limits published per model with reset headers (15). 429 guidance covers `Retry-After`, backoff with jitter and a ramp rule of 50% every 15 minutes, and since 2 September splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales (10). Responses and Chat Completions are GA (10).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-reliability):

Hosted APIs, MCP servers, models and platforms.

- 20, a public status page with component history (Statuspage, Instatus, BetterStack or the vendor's own).
- 0 to 30, the incident record for the last 90 days on that page. 30 for a clean record or trivial incidents only, 20 for minor incidents only, 10 for one major outage (an hour or more of a core API down, or errors across the board), 0 for several. 5 when there's no history we could read, and the note says so.
- 15, rate limits documented with numbers.
- 15, documented 429 or overload handling (Retry-After, backoff guidance), and idempotency keys or safe-retry guidance where writes are involved.
- 10, an SLA published for any paid tier.
- 10, the surface agents use is generally available, not beta or preview.

Local packages, SDKs, frameworks and stdio MCP servers.

- 20, installs from an official package with supported runtimes stated.
- 25, a public CI and test suite, passing on the default branch.
- 0 to 25, open crash or regression issues relative to activity (25 for few and handled, 0 for many, old and unanswered).
- 15, semver discipline and breaking changes called out in a changelog.
- 15, version 1.0 or later, or declared stable.

Protocols are read from their reference implementations, the public facilitators or servers, spec stability and test vectors.

## 3. Transparency & trust, 85 out of 100, up to 1.3 more on the total

Made of editorial 70, provenance 100.

Why it scored 85: Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide gives retention periods per endpoint, the training default and the ZDR route, and they agree with each other. We didn't read the DPA (25 of 30). Deprecations page with announcement and shutdown dates (20). Data residency regions listed (US, EU, UK, Japan, India and six more). The subprocessor list wasn't checked in this run (10 of 20).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-transparency):

- 0 to 30, source availability and licence clarity. 30 for open source under an OSI licence, 15 for closed with clear terms, 0 for unclear terms.
- 0 to 30, data handling and retention statements that agree with each other (privacy policy, DPA, retention periods, subprocessors).
- 0 to 20, a deprecation policy or notices with dates.
- 0 to 20, telemetry disclosed with an opt-out (local software), or subprocessors and data locations disclosed (hosted).

The other half of Transparency and trust is the provenance score, computed from checked facts (below). The category score is the mean of the two.

## 4. Maintenance & community, 91 out of 100, up to 0.8 more on the total

Why it scored 91: Model reading. GPT-6 Sol and Luna on 22 September and further changelog entries on 25 and 29 September (30). Published minimum notice of 6 months for GA models, 3 months for specialised variants, as little as 2 weeks for previews (12 of 12). Two model shutdown dates in the last 90 days, preview models on 23 July and `gpt-5.4-cyber` on 1 October, so 4 of 8. Dated changelog several times a month and a help centre (15 of 15). openai-python has 215 open issues and the newest open one dates from 27 July, replies not sampled (5 of 10). Current official SDKs, PyPI `openai` 3.22.1 on 30 September and npm `openai` 7.25.0 (15). Supported runtimes stated, Python 3.10 to 3.14 (10).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-maintenance):

- 0 to 30, time since the last release, or the last published model or API change for a closed service. 30 within 30 days, 20 within 90, 10 within 180, 0 older.
- 20, at least three releases or dated changelog entries in the last 90 days.
- 0 to 25, responsiveness. Issues and pull requests answered on GitHub (the open issues and how recent the replies are). For closed services, a public changelog and a support or community channel that answers, 0 to 15.
- 15, presence in the official MCP registry under a verified namespace (MCP servers), or current official SDKs (APIs and models).
- 10, package health, current dependencies and CI.

Models are read for deprecation notice periods and model churn rather than release counts.

## 5. Agent ergonomics, 98 out of 100, up to 0.3 more on the total

Why it scored 98: Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra calls tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x, $0.01 per million on Luna (15). 1.05M context on the default model, Sol (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-ergonomics):

- 0 to 25, context cost. For MCP, the number and size of the tool definitions (25 for ten or fewer compact tools, 15 for 11 to 30, 5 for more than 30, plus up to 10 back for toolsets, dynamic loading or read-only subsets). For APIs, whether responses can be sized (field selection, limits, summaries).
- 20, pagination, filtering and output-size controls.
- 20, actionable, documented error responses, codes and messages an agent can recover from.
- 20, idempotency or safe retries, and for MCP the `readOnlyHint` and `destructiveHint` annotations.
- 15, sensible defaults, few required parameters, and official SDKs in at least two languages.

Models are read for tool use, structured output, prompt caching, context length, batch and SDKs. Frameworks for how much code and how many defaults a tool-calling agent with MCP needs.

## What we couldn't check

What we couldn't read counted as absent. Publishing it on a page a plain HTTP fetch can read (not only in a browser) lets the next check count it.

- The changelog mentions a GPT-6.1 Sol on 29 September. We couldn't confirm its id or price, so the models list is unchanged
- Whether `gpt-5.4-cyber` counted as a specialised variant (3 months' notice under the policy) or a preview (2 weeks). It got 20 days
- Whether the Free tier needs a card, and which models it reaches
- The subprocessor list and the DPA weren't read in this run

## Weaknesses

- Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026
- Heavy migration calendar. Assistants API gone on 2026-08-26, Agent Builder, Evals and `v1/prompts` on 2026-11-30, GPT-5 and o3 on 2026-12-11
- GPT-6 models aren't available on the Free tier, so a card and prepaid credit come first in practice
- GPT-6 Astra has no custom temperature, no logprobs and no tool calling outside the Responses API

## What costs an agent a turn today

The notes we give agents before they call it. Each one is a workaround an agent shouldn't need.

- Build on the Responses API. Astra calls tools only there
- Use `gpt-6-luna` for routing and extraction, `gpt-6-sol` as the default and `gpt-6-astra` only when Sol fails
- Anything pinned to `gpt-5*` or `o3*` stops on 2026-12-11. Move before then
- Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent
- Prompts over 272K tokens cost double on input. Trim before you pay for it

## What the review panel asked for

- Machine payment route
- State verification rules
- Keyless trial route
- GPT-6 on Free tier
- State what Astra does with a rejected temperature
- reconcile Free tier pages
- logprobs on Astra
- A public SLA for self-serve tiers
- audit logs below enterprise
- model stage shown on each deprecation
- Reconcile the free-tier statements

## When it's done

Send what changed and where it's published as a dispute (https://www.anchorterminal.com/builders/#disputes, or `POST https://www.anchorterminal.com/api/v1/contact` with `"kind": "dispute"`). Disputes are answered in public, and the listing is checked again by the same checklist. Paying for an audit or a listing claim changes nothing here.