Editing an API spec by hand is fiddly work. Rename a field, add an enum value, tighten a required flag. Each change is small, but each one has to land in the right place without breaking the endpoints that reference it. It’s precise, mechanical, and exactly the kind of task you’d hand to an AI agent, if only you could trust it not to clobber the whole schema.
You can. The Apidog CLI gives an agent everything it needs to change a spec responsibly: schema validation before every write, an isolated branch to work on, and a merge request for you to review.
This is the mutation companion to letting an agent create API documentation. Creating is additive and low-risk; updating an existing contract is where the guardrails matter, so most of this guide is about doing it without breaking things.
What “update the spec” means at the CLI
Your spec in Apidog is the set of endpoints and data schemas in a project. Updating it means one of three commands:
endpoint update: change a path, a parameter, a response.schema update: change a data model that endpoints reference.import: bring in a whole new OpenAPI file to reconcile against the project.
Before you point an agent at any of them, there are two behaviors you have to understand, because getting them wrong is how a spec gets damaged. The first is a permission model, and the second is a gotcha that quietly deletes data.
The gotcha that will bite you: update is a full replace
This is the single most important thing to teach your agent. The CLI’s update commands are not JSON Patch. They submit the fields you provide directly; they do not merge array items by ID. If you send an update with a partial parameters array intending to change one parameter, you don’t edit that parameter. You replace the entire array with just the one you sent, and the rest are gone.
The correct sequence is always read-modify-write on the complete object:
# 1. Get the full current resource
apidog endpoint get <endpointId> --project <projectId>
# 2. Edit the complete structure locally (keep every field you're not changing)
# 3. Validate the whole object against the schema
apidog cli-schema get endpoint-create
apidog cli-schema validate endpoint-create --file ./endpoint-full.json
# 4. Write the complete object back
apidog endpoint update <endpointId> --project <projectId> --file ./endpoint-full.json
Put this in the agent’s instructions in plain terms: never send a partial object to update; always fetch the full resource, modify it, and send it back whole. An agent that skips the get step will silently drop fields. An agent that runs cli-schema validate first catches its own mistakes before they reach the project.
The safe path: let the agent work on an AI branch
You could give the agent direct-edit permission on your main branch. Don’t, at least not to start. Apidog has a purpose-built isolation mechanism, the AI branch, designed for exactly this: an agent modifies resources without touching the source branch, and nothing merges back until you say so. Think of it as a pull request for your API spec.
Step 1: Create the AI branch
apidog branch create --project <projectId> --type ai \
--from main --name "ai/20260713-from-main-refund-fields"
The naming convention is ai/YYYYMMDD-from-source-feature so the branch’s origin and purpose are legible at a glance. The --from value must be your main branch or a normal sprint branch, not a general branch. One handy detail: an AI branch with no difference from its source is auto-archived after 24 hours, so abandoned experiments clean themselves up.
Step 2: Import the resources the agent will edit
An AI branch starts empty. It does not clone the source branch automatically. Before the agent can edit an existing endpoint or schema, pull that resource into the branch with pick-to:
apidog branch pick-to --project <projectId> --type ai \
--from main --to "ai/20260713-from-main-refund-fields" \
--endpoint-ids <ids>
Resources the agent creates fresh on the branch don’t need this; only existing ones it intends to modify or delete. This is the step people forget: skip it, and the agent has an empty branch and nothing to edit.
Step 3: Let the agent make the change
Now the agent runs the read-modify-write loop from earlier, but with --branch pointing at the AI branch. Every edit is contained:
apidog endpoint get <endpointId> --project <projectId> \
--branch "ai/20260713-from-main-refund-fields"
apidog endpoint update <endpointId> --project <projectId> \
--branch "ai/20260713-from-main-refund-fields" \
--file ./endpoint-full.json
Your main branch is untouched this whole time. If the agent gets something wrong, the blast radius is one throwaway branch.
Step 4: Review, then merge
AI-branch changes are never written back automatically. When the agent finishes, you decide what happens. If the target is protected, open a merge request rather than merging directly:
apidog merge-request --help
apidog branch merge --project <projectId> --type ai \
--from "ai/20260713-from-main-refund-fields" --to main --endpoint-ids <ids>
Review the diff, approve, and the vetted change lands on main. Direct merge from the CLI requires direct-edit permission on both the source and target branch; if the main branch is protected, prefer merge-request and approve it in the Apidog client.
A worked example: renaming a field safely
Abstract rules are easy to nod along to and hard to apply. Here’s a concrete one. Say you want to rename amount to amountCents on the Refund data model, because you’re moving to integer cents.
You tell the agent: “Rename the amount field on the Refund schema to amountCents and make it an integer.” Following its rules, the agent:
# 1. Fetch the FULL current schema on the AI branch
apidog schema get <refundSchemaId> --project $PID --branch "ai/20260713-from-main-refund-fields"
It gets back the complete object and edits the whole jsonSchema, keeping every field it isn’t touching:
{
"name": "Refund",
"jsonSchema": {
"type": "object",
"required": ["orderId", "amountCents"],
"properties": {
"orderId": { "type": "string" },
"amountCents": { "type": "integer" },
"reason": { "type": "string" }
}
}
}
Note what did not happen: it didn’t send just the one changed property. It sent the entire schema with orderId and reason intact, because update replaces. Then:
# 2. Validate the complete object
apidog cli-schema validate schema-create --file ./refund-full.json
# 3. Write it back to the AI branch
apidog schema update <refundSchemaId> --project $PID \
--branch "ai/20260713-from-main-refund-fields" --file ./refund-full.json
You review the AI-branch diff (one field renamed, nothing else disturbed) and merge. That’s the entire discipline: full object, validated, on a branch, merged after review.
Flag breaking changes before you merge
Renaming a required field is a breaking change: any client sending amount will now fail validation. A good agent instruction set makes the model say so rather than merge silently. Add this to the agent’s rules:
Before merging any spec change, classify it:
- Non-breaking (new optional field, new endpoint, loosened constraint) → summarize and proceed to merge-request.
- Breaking (renamed/removed field, new required field, tightened type) → STOP.
Report the breaking change and the affected endpoints, and wait for explicit human approval.
The AI branch is what makes this safe to enforce: because nothing merges automatically, “stop and report” is a real checkpoint, not a race against a write that already happened.
Updating from an OpenAPI file instead
Sometimes the change already exists as an OpenAPI file, generated from code, edited elsewhere, or handed to you by another team. Rather than replaying edits field by field, the agent can import the file to reconcile it against the project:
apidog import --project <projectId> --format openapi --file ./openapi.json \
--branch "ai/20260713-from-main-refund-fields"
import accepts OpenAPI 3.x, Swagger 2.0, Postman, and more. Run it against an AI branch first so you can review what the incoming spec changes before it reaches main. After merging, export the reconciled spec back out to confirm the result:
apidog export --project <projectId> --format openapi --oas-version 3.1 --output ./openapi.json
This route is best when the source of truth lives outside Apidog and you’re syncing it in. The per-field update route is best when Apidog is the source of truth and you’re making a surgical change.
When the agent gets it wrong: rollback
The reason to work on an AI branch is that mistakes are cheap to undo. If the agent produces a change you don’t want, you never merged it, so main is already correct. Just archive the branch and move on:
apidog branch archive "ai/20260713-from-main-refund-fields" --project <projectId> --type ai
Because an AI branch with no accepted difference auto-archives after 24 hours anyway, even a forgotten experiment cleans itself up. Compare that to an agent editing main directly, where a bad update is live immediately and your only recourse is the recycle bin or a hand-reversal. The branch isn’t bureaucracy; it’s the undo button.
A note on permissions
If an update or import comes back blocked, the project has External AI Edit Permissions turned off. That’s a deliberate gate, and the AI-branch flow above is the answer to it: the agent edits an isolated branch and you approve the merge. If you’d rather grant direct edits, the switch lives in Project Settings → Feature Settings → AI Feature Settings (Apidog client 2.8.32+). When an agent hits a permission wall, don’t have it silently pick a workaround; surface the choice to a human.
Common snags
Partial update wiped fields. The most damaging and most common mistake. update replaces; it does not merge. Fetch the full object, edit it whole, validate, then write. If a field disappeared, the agent sent a partial payload.
Editing an existing resource on an AI branch without importing it. The branch starts empty. pick-to the resource in first, or the agent has nothing to edit.
Wrong --from for the AI branch. The source must be main or a sprint branch, never a general branch. The branch create command will complain if you get this wrong.
Skipping validation. cli-schema validate catches a malformed payload on your machine. An agent that writes without validating turns a typo into a failed API call, or worse, a bad merge.
Merging a breaking change silently. Without a classify-first rule, an agent will happily rename a required field and merge it. Make breaking-change detection an explicit checkpoint.
FAQ
Can I let the agent edit the main branch directly? You can, by enabling External AI Edit Permissions, but starting on an AI branch is safer: nothing lands on main until you approve a merge. Reserve direct edits for low-risk, high-trust automation.
What’s the difference between branch merge and merge-request? branch merge writes the change through immediately and needs direct-edit permission on both branches. merge-request opens a reviewable request, the right choice when main is protected.
Does the agent need the Apidog desktop app? No, the CLI is standalone. The app matters only for toggling the External AI Edit Permissions setting, which is a one-time configuration.
How do I make sure the agent doesn’t hallucinate a field name? The cli-schema get → validate loop is the guardrail. A payload with an invented field fails validation locally, before it ever reaches the project.
Wrapping up
Letting an agent update your API spec is safe when three things are true: it works on an isolated AI branch, it treats every update as a full read-modify-write rather than a patch, and a human approves the merge. The Apidog CLI gives you all three as commands, which means the whole loop (edit, validate, review) is scriptable and auditable, and a bad change is one archive away from gone.
Set up the AI branch, hand the agent the read-modify-write rule and the breaking-change checkpoint, and spec maintenance becomes a diff you approve instead of fiddly work you keep postponing. Download Apidog to get the CLI, and pair this with letting an agent create your docs to cover the full authoring-and-maintenance loop.
