Inside Doco, an AI agent is described as a scoped operator: it gathers evidence, makes a targeted change only when authorized, then checks the authoritative document and related views. The workflow is browse → search → read → traverse → edit → watch—not download a whole knowledge base and rewrite it from incomplete context.
This is Doco builder Harry Smart’s account of the product’s designed workflow, not an independent test of its implementation. The example below is illustrative; it does not report an executed change.
What does an agent do after connecting to a knowledge base?
It works through six stages, each intended to reduce guesswork before an action and verify what happened afterward. Doco’s article describes this sequence for knowledge-base work.
1. Browse to establish scope
The agent first identifies the connected workspace or knowledge base, whether it is local, staging, or production, what permissions its token has, and the target’s actual IDs and place in the hierarchy. This is how it avoids acting on a guessed identifier or the wrong environment.
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2. Search for the current fact
It searches for the relevant phrase and assesses whether the returned results cover the question. Doco’s article describes structured full-text search, not an all-knowing semantic search. If results are incomplete, that is not evidence that the knowledge base contains no answer; the agent needs more context or must say its coverage is incomplete.
3. Read the surrounding evidence
The agent inspects an outline and nearby blocks so that it understands the target statement and its constraints. Doco’s article describes continuation cursors for requesting more context without mixing document versions.
4. Traverse relationships
It follows relevant links or dependencies to additional evidence. For example, before saying a rollback plan is still valid, it needs to inspect that plan. A relationship can be stale or dangling, so following it identifies evidence to check; it does not establish that the evidence is current.
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5. Edit one stable target
Before writing, the agent reads the current block and version, then makes the smallest change supported by the evidence. Doco’s article describes attaching an If-Match precondition to guard against overwriting a version that has changed since it was read. Under RFC 9110, section 13.1.1, a server evaluates this HTTP condition against the current representation; if the condition fails, the client must not assume its stale edit was applied. A conflict calls for rereading and reconsidering the change, not blindly retrying it.
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After the write, the agent reads the authoritative document back to confirm the intended value and check that nearby blocks remain intact. It then checks whether derived views—such as search results, indexes, summaries, and related evidence—have caught up. Doco’s article says that if change history is incomplete, the agent should synchronize fully rather than claim it has a complete delta.
What would that look like for a release-window change?
Doco’s example request is to change a production release window from 20:00 to 20:30 and confirm that the rollback plan remains valid. The workflow would be:
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- Confirm the connected knowledge base is production, inspect the token’s permissions, and identify the correct release guide.
- Search for the release-window statement, then read its block and surrounding context to understand what it applies to.
- Follow the guide’s relationship to the rollback plan and inspect the plan before describing it as valid.
- Read the target block’s current version and, if authorized, make only the 20:00-to-20:30 change with a version precondition.
- Read the guide back to check the actual value and neighboring content, then check whether search and other dependent views reflect the change.
This example explains the intended method; it is not evidence that Doco performed this particular production edit.
Does an agent need write access to use Doco?
No. Doco’s article says a read-only agent can browse, search, inspect outlines, follow relationships, and watch changes. It needs write access to change content. Keeping discovery and review separate from editing lets an agent gather and validate evidence without granting it authority to alter documents.
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Doco’s article describes MCP, CLI, and REST API as connection options that share documents, block IDs, versions, permissions, and errors. It characterizes MCP as making tools discoverable to compatible clients, CLI as suited to terminal workflows, and REST as the integration foundation. The choice of interface does not remove the need to scope access, check versions, or verify a result.
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The Model Context Protocol tools specification, dated June 18, 2025, describes tools as actions a model can discover and invoke, while leaving interface patterns to implementations. Its guidance says: “For trust & safety and security, there SHOULD always be a human in the loop with the ability to deny tool invocations.” This is protocol guidance; it does not mean every MCP implementation presents consent in the same way.
What can go wrong, and what should the agent do?
- Search misses relevant material: Treat incomplete results as incomplete coverage, not proof that no answer exists. Read further or qualify the answer.
- A version conflict occurs: The source changed after the agent read it. Reread the current content and decide whether the proposed edit is still appropriate. A 409 conflict does not merge competing intentions or decide which one is correct.
- A relationship or summary looks current: Treat it as a route to evidence, not proof of currency. Inspect the linked source and check whether derived views have caught up.
- The write returns success: Do not equate a successful HTTP response with the intended final state. Read the authoritative document back and check the relevant projections.
- Change history is incomplete: Do not claim a complete delta; synchronize fully before making that claim.
Doco’s article also says that a transient cursor for an API-connected agent’s pending block edit remained future work at the time of publication. That is a time-sensitive, first-party product statement, not a protocol guarantee.
Why prefer a small, version-aware edit?
A whole-document rewrite can alter material beyond the intended target and can rely on partial context. A stable-block patch narrows the intended change; a version precondition helps detect concurrent changes; an authoritative read-back checks what the source actually contains. These are workflow safeguards described by Doco’s article, not measured performance results or a guarantee that errors are impossible.
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