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Hassann
Hassann

Posted on • Originally published at apidog.com

How to Let an AI Agent Update Your API Spec with the Apidog CLI

Editing an API spec by hand is error-prone: rename a field, add an enum value, or change a required flag, and every dependent endpoint must remain valid. With the Apidog CLI, an AI agent can make these changes with guardrails: validate before writing, work in an isolated branch, and submit changes for review.

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This is the mutation companion to letting an agent create API documentation. Documentation generation is additive and relatively low-risk. Updating an existing API contract needs a safer workflow.

What “update the spec” means in the CLI

An Apidog project contains endpoints and data schemas. You typically update a spec with one of these commands:

  • endpoint update: Change a path, parameter, request, or response.
  • schema update: Change a data model referenced by endpoints.
  • import: Reconcile an entire OpenAPI file with the project.

Before giving an agent access to these commands, establish two rules:

  1. update is a full replacement, not a patch.
  2. The agent should work in an isolated AI branch.

Critical behavior: update replaces the full object

Apidog CLI update commands are not JSON Patch operations.

If you submit only one item from a parameters array, the CLI does not merge that item into the existing array. It replaces the entire array with the value you submitted. Any omitted parameters are removed.

Use a full read-modify-validate-write loop every time:

# 1. Fetch the complete current resource
apidog endpoint get <endpointId> --project <projectId>

# 2. Edit the complete structure locally.
# Keep every field that should remain unchanged.

# 3. Get the payload schema and validate the complete object
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
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Put this directly in the agent instructions:

Never send a partial object to update. Always fetch the full resource, modify it, validate it, and send it back as a complete object.

Skipping get can silently remove fields. Running cli-schema validate before writing catches malformed payloads locally.

Safe workflow: use an AI branch

Avoid granting an agent direct write access to main when starting out. Use an AI branch instead.

An AI branch isolates agent changes from the source branch. Nothing reaches main until you review and merge it.

Step 1: Create an AI branch 

apidog branch create --project <projectId> --type ai \
  --from main --name "ai/20260713-from-main-refund-fields"
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Use a name that makes the source and purpose obvious:

ai/YYYYMMDD-from-source-feature
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The --from branch must be main or a normal sprint branch, not a general branch.

An AI branch with no differences from its source is automatically archived after 24 hours, which keeps abandoned experiments from accumulating.

Step 2: Import existing resources into the branch

An AI branch starts empty. It does not automatically clone all resources from its source branch.

Before an agent can modify an existing endpoint or schema, import that resource using pick-to:

apidog branch pick-to --project <projectId> --type ai \
  --from main --to "ai/20260713-from-main-refund-fields" \
  --endpoint-ids <ids>
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Use pick-to only for existing resources the agent needs to edit or delete. Resources created from scratch on the AI branch do not need to be picked first.

Step 3: Run the full update loop on the AI branch

Point each command to the branch:

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
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The agent can make changes, validate them, and retry as needed without modifying main.

Step 4: Review and merge

AI branch changes are not merged automatically. Review the diff first.

For protected targets, use a merge request rather than a direct merge:

apidog merge-request --help

apidog branch merge --project <projectId> --type ai \
  --from "ai/20260713-from-main-refund-fields" \
  --to main --endpoint-ids <ids>
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A direct CLI merge requires direct-edit permission on both source and target branches. If main is protected, open a merge request and approve it in the Apidog client.

Worked example: rename a schema field safely

Suppose you need to rename amount to amountCents in a Refund schema and change the type to an integer.

Tell the agent:

Rename the amount field on the Refund schema to amountCents and make it an integer.

First, fetch the complete schema from the AI branch:

apidog schema get <refundSchemaId> --project $PID \
  --branch "ai/20260713-from-main-refund-fields"
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Then update the full jsonSchema, preserving properties that are not changing:

{
  "name": "Refund",
  "jsonSchema": {
    "type": "object",
    "required": ["orderId", "amountCents"],
    "properties": {
      "orderId": { "type": "string" },
      "amountCents": { "type": "integer" },
      "reason": { "type": "string" }
    }
  }
}
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Do not send only the changed property. Send the complete schema so orderId and reason remain intact.

Validate and update the AI branch:

# Validate the complete payload
apidog cli-schema validate schema-create --file ./refund-full.json

# Update the schema on the AI branch
apidog schema update <refundSchemaId> --project $PID \
  --branch "ai/20260713-from-main-refund-fields" \
  --file ./refund-full.json
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Review the resulting diff, confirm that only the intended field changed, and then merge it.

Require breaking-change detection before merging

Renaming a required field is a breaking change. Clients sending amount will fail validation after the change.

Make the agent classify each change before it opens or completes a merge:

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.
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The AI branch makes this checkpoint meaningful: the change remains isolated until a human approves it.

Updating from an OpenAPI file

When the change already exists in an OpenAPI file—for example, generated from code or supplied by another team—import it into the AI branch instead of applying individual field updates:

apidog import --project <projectId> --format openapi --file ./openapi.json \
  --branch "ai/20260713-from-main-refund-fields"
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import supports OpenAPI 3.x, Swagger 2.0, Postman, and more. Import into an AI branch first so you can inspect the resulting changes before they reach main.

After merging, export the reconciled spec to verify the result:

apidog export --project <projectId> --format openapi \
  --oas-version 3.1 --output ./openapi.json
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Use this approach when the source of truth lives outside Apidog and you are syncing it in. Use endpoint update or schema update when Apidog is the source of truth and the change is surgical.

Roll back an unwanted agent change

An AI branch makes rollback simple. If you reject the changes, do not merge them. Archive the branch:

apidog branch archive "ai/20260713-from-main-refund-fields" \
  --project <projectId> --type ai
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Because main was never modified, no hand-reversal is required. The branch is your undo button.

Permissions

If an update or import command is blocked, External AI Edit Permissions may be disabled for the project.

The AI branch workflow is designed for this situation: let the agent edit an isolated branch, then approve the merge manually.

To grant direct edits instead, configure the setting in:

Project Settings → Feature Settings → AI Feature Settings
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This setting is available in Apidog client 2.8.32+.

When an agent encounters a permission restriction, have it report the issue rather than silently attempting a workaround.

Common snags

Partial update removed fields

update replaces rather than merges. Fetch the full object, modify it, validate it, and write the complete payload back.

The agent cannot find a resource on an AI branch

AI branches start empty. Run pick-to before editing an existing endpoint or schema.

The AI branch was created from the wrong source

The --from branch must be main or a sprint branch, not a general branch.

Validation was skipped

Run apidog cli-schema validate before every write. It catches malformed payloads before the agent makes an API call.

A breaking change was merged without review

Require the agent to classify changes and stop on renamed or removed fields, newly required fields, and tightened types.

FAQ

Can an agent edit main directly?

Yes, if you enable External AI Edit Permissions. However, AI branches are safer because changes do not reach main until you approve a merge. Reserve direct edits for low-risk, high-trust automation.

What is the difference between branch merge and merge-request?

branch merge writes changes immediately and requires direct-edit permission on both branches.

merge-request creates a reviewable request, which is the better option when main is protected.

Does the agent need the Apidog desktop app?

No. The CLI is standalone. The desktop app is only needed to configure External AI Edit Permissions.

How do I prevent hallucinated field names?

Use the schema validation loop:

apidog cli-schema get schema-create
apidog cli-schema validate schema-create --file ./refund-full.json
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An invented or malformed field fails local validation before it reaches the project.

Wrap up

Agent-driven API spec updates are safe when you enforce three practices:

  1. Work in an isolated AI branch.
  2. Treat every update as a complete read-modify-write operation.
  3. Require human approval before merging, especially for breaking changes.

That makes spec maintenance an auditable diff instead of a risky direct edit. Download Apidog to get the CLI, then pair this workflow with agent-generated API documentation for a complete authoring and maintenance loop.

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