Developers do not read API documentation. They locate the endpoint, parameter, and the code that the API returned. The rest of the documentation is irrelevant (scaffolding). The only reason to write this is to answer a question beyond the scope of the documentation.
Our writers use the OpenAPI file you provided, sample API calls that you provide, and the source, when you provide it. In the final form of the documentation, each field name and status code can be traced back to those inputs.
A single error in prose takes a reader a minute to read over. A single error in a reference takes them an afternoon because they think the document takes precedence over their code, and so they continue searching in the wrong spot. Accuracy in these fields is field by field: type, required or not, default, constraints, and the exact error that the API returns when a constraint is broken.
Models follow patterns, and REST APIs are just that: patterns. Because of this, it is easy to imagine an include_metadata flag appearing on an endpoint which previously did not have it, and it is equally as easy to document a 429 response code when the service actually responds with a 503. The reference looks excellent until the first request via an integrator fails.
The starting point is the spec file, not the end point. The writer develops the endpoint one by one and requests them. They also generate a comprehensive list of everything the spec misses, e.g., undocumented enum values, unwritten rate limits, schematic fields that are optional, but end up being required. This list reaches your engineers before you start writing.
Reviews are performed against the API in order to validate each field of the Adourc and against the internal logic of the draft. Schema matching is performed for each field and example requests are made and their respective responses are included in the review. Each status code mentioned in the review is a status code actually returned by the service. Anything that cannot be verified is flagged in the review rather than ignored.
One rate, whatever the format: $10 per 100 words. You are paying for the writer’s time and judgement, so the price scales with the words rather than with a package tier.
| Typical API doc | Words | Writing | Fee (1%) | You pay |
|---|---|---|---|---|
| Single reference | 800 | $80 | $0.80 | $80.80 |
| Standard doc set | 2,000 | $200 | $2 | $202 |
| Full documentation | 5,000 | $500 | $5 | $505 |
The writer receives 100% of the writing price. Our 1% fee is added on top of it, and 0.5% is donated to tree planting. Full pricing breakdown.
A named human writer with a background in this kind of work. No model drafts, outlines, edits or researches any part of it, and nothing is run through an AI humanizer. Every draft is checked against multiple detectors before it reaches you.
A named human writer with a background in this kind of work. No model drafts, outlines, edits or researches any part of it, and nothing is run through an AI humanizer. Every draft is checked against multiple detectors before it reaches you.
What your tooling already does is generate parts and do it rather well. We provide the write-up for the other parts which describe why an endpoint exists, what sequences of calls are needed to perform a task, what the fields mean despite looking awkward, and where a specification and the service deviate from one another.
Yes, assuming we’re on the same page with what concurs with the page’s caveat. The writer notes down the date and build that documentation was checked against and notes the endpoints that are unstable. Your two revision rounds could fit into the 14-day window to allow the release to settle, which is typical.
Completely. Copyright transfers to you on delivery, with no attribution requirement and no licence back to us. Nothing written for you is resold, repurposed or republished.
Reviews from completed, paid orders in this category.
Most writers omit error response text, or post the status codes with no surrounding context. Ours explained what they thought the caller did wrong with a short response per status. Because of this explanation, our support queue for that endpoint has gone quiet.
Before drafting, the client sent over eleven questions. Two of the questions asked about failure states that we had never documented before. Responding to these questions took me a morning to complete, but now the internal notes have improved. The guide is the second best thing that came from this order.
The steps are detailed and match interface options precisely. I thought images were included, but they aren’t, and it even says that. It just wasn’t obvious where. It took a day to add them, which is still better than the vendor supplied documentation.
We do not ask you to take the no-AI promise on trust. Each draft is run through these platforms and the reports are attached to your delivery email.
Originality.aiAI detection + plagiarism
GPTZeroAI detection
TurnitinAI detection + similarity
CopyleaksAI detection + plagiarism
Winston AIAI detection
ZeroGPTAI detection
SaplingAI detection
Content at ScaleAI detection
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$10 per 100 words · all of it to the writer · 0.5% to trees