Internal API documentation usually fails quietly. The endpoint exists, the README exists, the OpenAPI file may even exist, but the usable context is scattered across pull requests, incident notes, Slack threads, migration docs, and the memory of the one person who last touched the service.
That is fine until someone needs to change it. Then the real questions arrive: which client depends on this field, why does the webhook retry this way, what happens if the upstream returns a partial response, and who owns the job that backfills the missing data?
Docapybara works well for this kind of documentation because service knowledge is rarely just a schema. It is a mix of contract, examples, decisions, gotchas, and recent operational evidence. Put that material in one markdown-native vault and Capy can search it, edit it, and help turn rough notes into documentation you can use during the next change.
Start with the service, not the template
Templates are useful, but they can make API docs feel more complete than they are. Start with one internal service and write the plain-English version first: what the service owns, who calls it, what data it accepts, what data it returns, and what breaks when it is wrong.
For example, a billing events service might need four paragraphs before any table appears: it receives checkout events, normalizes them, writes them to Postgres, emits webhook notifications, and feeds a nightly reconciliation job. That story gives the endpoint list a home. Without it, every route is a little island.
This is the same reason Architecture Decision Records, Kept Where Your Agent Can Read Them works as a companion habit. API docs explain the current contract. ADRs explain why the contract looks that way. You want both close enough that Capy can read across them.
Keep contracts and lived behavior together
The contract says POST /events accepts an event type, timestamp, customer ID, and payload. The lived behavior says the service also tolerates duplicate event IDs, rejects timestamps in the future, and sends a warning when a deprecated payload shape appears. Engineers usually learn those details by breaking something once.
Put the formal contract and the lived behavior on the same page. Keep an endpoint section with request and response examples, then add a notes section for edge cases, client expectations, retry behavior, and known quirks. If an incident revealed the quirk, link the incident note. If a pull request changed it, paste the relevant explanation.
The point is not to replace generated API docs. Generated docs are good at showing what the code declares. Your Docapybara page is where the code, operations, and human explanation sit together.
Use one small database for service inventory
Once you have more than a few services, create an internal service index with an inline database via the :::database::: directive. Keep it small enough that people will maintain it. Good columns are service name, owner, environment, primary datastore, external dependencies, status, and documentation link.
Avoid turning the index into a second CMDB. If a column does not change how you debug, review, or plan, leave it out. The best service index is boring and frequently opened.
The inline database gives you a scan of the system. The pages give you the nuance. A row can say "billing-events, backend, Postgres, active." The linked page can explain why a 202 Accepted response still might not mean the downstream notification was delivered.
Capture decisions while they are still warm
Most useful API documentation is written in the messy middle: during a migration, after a failed deploy, while adding a client, or immediately after a design review. That is when the reasoning is still available.
When you change an internal API, add a short "Change log" section to the service page. Date it. Name the change. Add the reason. Link the ADR if one exists. If the decision happened in a meeting, record the meeting when appropriate and let Docapybara turn the audio into text with speaker labels. Then ask Capy to draft the documentation update from the transcript and the existing service page.
For broader engineering memory, How to Document Institutional Knowledge Before People Walk Out the Door covers the same habit outside the API layer. The smaller version here is simple: do not wait for a documentation sprint. Update the service page while the change is still visible.
Ask Capy the questions a new engineer would ask
After the page has enough material, use Capy as a patient reviewer. Ask questions like: "What would a new engineer need before changing this endpoint?" "Find undocumented edge cases in these incident notes." "Compare this OpenAPI snippet with the service page and tell me what is missing." "Draft a client migration note from these decisions."
Those prompts keep Capy close to your evidence. It is not guessing a generic best practice. It is reading the pages in your vault, the notes you captured, and the documentation you already trust.
This pairs naturally with Notes as Context for AI Tools, especially if your AI coding tool needs project context that is not in the repository. The API page becomes a source your assistant can consult instead of a memory you have to retype.
Make examples first-class
Internal APIs often fail at the example layer. The contract lists fields, but a real client needs to know what a "normal" payload looks like, what an error response looks like, and what a weird-but-valid payload looks like.
Keep examples in fenced code blocks and label them by scenario. Add one happy path, one validation error, one retryable upstream failure, and one historical weird case if the service has one. For each example, write one sentence explaining when it appears.
Do the same for internal workflows around the API. If the billing service has a manual replay command, document the command and the safety checks beside the endpoint docs. If the search index has a backfill script, keep the script notes beside the index update endpoint. Someone will search for it later at an inconvenient time.
Review docs before changing the service
The useful habit is not "keep docs updated someday." It is "read the service page before changing the service." Before a migration or endpoint change, ask Capy to summarize the service page, related ADRs, open incidents, and any pages that mention the route.
That review is a guardrail. It catches the old client, the migration note, the unusual retry behavior, and the reason a field exists. It also makes the documentation valuable to the person doing the work, not just to an imaginary future reader.
If your change process includes code reviews, Store AI Prompts Like Code is a useful adjacent pattern: keep the prompts that check docs, draft migration notes, or summarize service behavior in the same vault so they can improve over time.
Start with one service page
Pick one service people keep asking about. Create a page with the service story, endpoint summaries, examples, edge cases, ownership, dependencies, and a short change log. Add it to the service index. Ask Capy to find missing context from nearby notes and help draft the rough sections.
Then use the page before the next change. If it helps you avoid a repeated explanation or remember a strange edge case, keep going. If a section feels ornamental, cut it. Internal API docs should make the next change calmer, not give you another shrine to maintain.
Try Docapybara free when you want your internal service docs, decisions, examples, and operational notes in one place where Capy can read them with you.