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FlowCastle

by ai.flowcastle

get_broadcast_analytics

Read-only

Return engagement analytics for a broadcast: delivery breakdown by status plus per-message-block sent and clicked counts for its flow, over an optional date window. Read-only. Sent counts reflect messages attempted, not confirmed deliveries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateNoEnd of the reporting window, same format as startDate. Defaults to now.
startDateNoStart of the reporting window, as a date string parsable by Date (ISO 8601 such as "2026-07-01" or "2026-07-01T00:00:00Z" is safest). Defaults to the broadcast's creation time.
broadcastIdYesRequired. Broadcast id, as returned by list_broadcasts.
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

A4/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint=true), the description adds important behavioral nuance: 'Sent counts reflect messages attempted, not confirmed deliveries.' This clarifies the meaning of the returned data.

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 concise (two sentences plus a clarifying note) and front-loaded with the core purpose. Every sentence adds value without redundancy.

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

Completeness4/5

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

For a read-only analytics tool with 4 well-documented parameters and no output schema, the description is fairly complete. It provides the key behavioral nuance and date window context, though it omits error conditions or pagination details.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all parameters. The description adds minimal extra meaning beyond referencing 'optional date window' for startDate/endDate. The baseline of 3 is appropriate.

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 clearly states it returns engagement analytics for a broadcast with delivery breakdown and per-message-block counts. It distinguishes from sibling tools like get_broadcast_details by specifying analytics and delivery breakdown.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives. It implies usage for analytics over a date window but lacks when-not-to-use guidance.

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