Skip to main content
Glama
DatalisHQ

ZuckerBot

by DatalisHQ

zuckerbot_capi_status

Retrieve 7-day and 30-day CAPI delivery stats including events sent, type breakdown, match quality, and attribution to verify CAPI functionality and event matching.

Instructions

Get 7-day and 30-day CAPI delivery statistics for the business: total events sent, events by type (Lead/Contact/Purchase), match quality breakdown, and attribution counts. Use this to confirm CAPI is functioning and that events are being matched by Meta.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
business_idNoOptional business ID override
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly indicates a read-only operation that returns statistics, with no mention of destructive actions. It could explicitly state it is read-only, but the behavior is well implied.

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 two sentences with no waste. The first sentence lists the data returned, and the second states the purpose. Every sentence is necessary and well-structured.

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?

Given no output schema, the description adequately explains the return values: total events, events by type, match quality breakdown, attribution counts. It lacks format details but is sufficient for a status tool. Minor gap: no mention of possible errors or limits.

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?

There is only one optional parameter (business_id), and its schema description is already clear. The description adds no extra meaning beyond 'for the business,' which is implicit. With 100% schema coverage, the baseline is 3.

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 the tool retrieves CAPI delivery statistics for 7-day and 30-day periods, listing specific data like total events, event types, match quality, and attribution. It is distinct from sibling tools, none of which seem to provide similar statistics.

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

Usage Guidelines4/5

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

The description explicitly says 'Use this to confirm CAPI is functioning and that events are being matched by Meta,' providing a clear use case. It does not mention alternatives or when not to use, but the context is sufficient for an agent to decide.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DatalisHQ/zuckerbot'

If you have feedback or need assistance with the MCP directory API, please join our Discord server