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ClockNext

ClockNext MCP Server

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by ClockNext

ClockNext: get customer usage

clocknext_get_customer_usage
Read-only

Check a customer's recent usage logs to confirm a signal landed and verify the recorded model, tokens, and cost.

Instructions

Read back a customer's recent usage logs (most recent first). Use it to CONFIRM a signal landed — e.g. after running the product's code so it fires a real signal, check the event shows up here with the expected model, tokens, and cost. For a signal you fire directly, clocknext_record_usage already returns the priced log inline, so this is mainly for signals sent by the running codebase.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe ClockNext customer id.
limitNoMax usage rows to return (most recent first).
Behavior4/5

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

Annotations already mark readOnlyHint=true and openWorldHint=true, and the description adds useful context: logs are returned most recent first, and you can check for expected model, tokens, and cost. It doesn't describe edge cases like missing IDs, but for a read-only tool this is sufficient.

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?

Three sentences, front-loaded with the core purpose. Each sentence adds distinct value: what it does, when to use it, and how it differs from a sibling. No fluff or repetition.

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 simple read tool with two well-documented parameters and no output schema, the description explains the use case, the expected content of the logs, and the alternative. It could mention default limit behavior or empty results, but overall it is complete enough for an agent to select and invoke correctly.

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 descriptions already cover both parameters 100% (customer id and limit). The description repeats 'most recent first' and adds value by explaining what the logs contain (model, tokens, cost), but it doesn't add new parameter-level meaning beyond what the schema provides.

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?

Description clearly states the verb ('Read back') and resource ('a customer's recent usage logs'), with ordering ('most recent first'). It also differentiates from sibling clocknext_record_usage by explaining this tool is for confirming signals from the running codebase, not for directly fired signals.

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?

Explicitly says when to use: to CONFIRM a signal landed after running the product's code. It also names the alternative (clocknext_record_usage) and explains why this tool is mainly for signals sent by the running codebase, giving clear when/when-not 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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