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FlowCastle

by ai.flowcastle

deploy_application

Idempotent

Publish the workspace to its bots — the API equivalent of the dashboard's Deploy button. This is the step that makes edits live. apply_actions writes to the DRAFT graph. Until this runs the connected bots keep serving the previously published version, so a change that looks applied has no effect for real users. Deploy after a batch of edits (and after run_flow_autotest passes), not after every single action. Publishes the ACTIVE version to every active bot of the application; pass botIds to publish to a subset. Rolling back to an older version is a dashboard action and is deliberately not available here. Delivery is asynchronous: a bot listed as "queued" was handed to the deploy queue, not confirmed restarted. Returns { deployed, versionId, bots[], queuedCount, failedCount, error } — check error and each bot's status, because a version can be marked published while no runtime received it. Safe to repeat: deploying twice republishes the same version rather than duplicating anything. It does change what real users see, so confirm with the user before publishing edits they have not reviewed. Requires the manage_automation permission.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
botIdsNoPublish only to these bots. Omit to publish to every active bot of the application (the dashboard default). Ids that are not active, non-preview bots of this application are reported back in unknownBotIds and otherwise ignored.
applicationIdNoApplication (workspace) id. Optional: an application-scoped key (app_...) defaults to its own application, but a personal key (usr_...) has no default and omitting it fails with MCP_APPLICATION_REQUIRED. Call list_applications to get the id.

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses critical runtime behavior beyond annotations: delivery is asynchronous, 'queued' means handed to the queue rather than confirmed restarted, and a version may be marked published before any runtime receives it. It also covers idempotency ('Safe to repeat'), permission requirements, and the impact on real users. No contradiction with annotations is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but densely informative; every sentence contributes either behavioral caveats, usage timing, return-value semantics, or permission requirements. It is front-loaded with the core purpose and then logically expands into when, how, and what to check.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, asynchronous delivery, and lack of an output schema, the description fully compensates by enumerating the return fields, telling the agent to check error and per-bot status, and covering permissions, idempotency, and safety. Nothing needed for correct invocation or result interpretation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers both parameters at 100%, so the baseline is 3. The description adds useful semantic context by clarifying that botIds publish to a subset and that the 'ACTIVE version' goes to every active bot, which complements the schema's detailed explanations without redundantly repeating them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Publish the workspace to its bots') and immediately anchors it as 'the API equivalent of the dashboard's Deploy button.' It also explicitly differentiates from a sibling by saying apply_actions writes to the DRAFT graph, so an agent can tell exactly what deploy_application does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit timing guidance: 'Deploy after a batch of edits (and after run_flow_autotest passes), not after every single action.' It also states what is deliberately not supported (rolling back is a dashboard action) and requires user confirmation before publishing unreviewed edits, which strongly signals appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0
Disambiguation4/5

Each get_/list_ tool targets a distinct resource and the descriptions carefully separate similar pairs like get_application_context vs get_workspace_summary and get_broadcast_details vs get_broadcast_analytics. The main ambiguity is apply_actions vs validate_actions, since one runs the other's validation, but the descriptions make that relationship explicit.

Naming Consistency4/5

Names consistently follow verb_object snake_case and use familiar verbs like create, get, list, and update. Minor deviations such as read_messages instead of list_messages, apply_actions/validate_actions with plural nouns, and run_flow_autotest are still predictable and readable.

Tool Count2/5

33 tools exceeds the 25-tool threshold and makes the surface feel heavy, even though the domain is broad. Many of the read-only getters are individually useful but could be consolidated, such as merging module catalog/details or workspace/application context.

Completeness4/5

Core workflows are covered: application lifecycle, flow editing through apply_actions, deployment, contacts, broadcasts, modules, and message/event reads. Minor gaps exist, such as no dedicated delete for contacts, applications, or broadcasts, and no rollback for deployments, but agents can work around or avoid these.

Resources