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Agent Broker

by dev.hatchloop

check_quota

Read-onlyIdempotent

Returns the caller's current quota state: how many operations have been used today, how many remain, the daily limit, the tier (free / credits / unlimited), and when the quota resets. Read-only and free. Works with any valid X-Agent-Identity token; returns tier='anonymous' for keyless callers with the anonymous daily limits.

EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "How many API calls do I have left today?" -> call check_quota({}) user: "Check my quota before sending messages" -> call check_quota({}) user: "When does my rate limit reset?" -> call check_quota({})

WHEN TO USE: Call at session start or before a batch of write operations to confirm you have enough remaining quota. Use when a user asks how many API calls they have left today. Also useful after a rate_limited error to understand when the quota resets. WHEN NOT TO USE: Do not call on every single tool invocation — quota is also injected into every write-tool response in the 'quota' field. Only call proactively when you need the current state without performing an operation. COST: free - no key required LATENCY: ~5ms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds meaningful context beyond those annotations: it is free, works with any valid X-Agent-Identity token, returns tier='anonymous' for keyless callers, and includes cost and latency information. No contradiction exists.

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

Conciseness4/5

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

The description is well-organized with a clear opening, example queries, usage guidance, and cost/latency sections. It is slightly longer than necessary because the three example user queries are near-duplicates and 'free' is mentioned both in the body and in COST, but this is minor redundancy.

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 there is no output schema, the description fully enumerates what the agent can expect: used operations, remaining operations, daily limit, tier, and reset time. It also covers authentication, anonymous behavior, cost, and latency, making the tool complete for a zero-parameter read-only call.

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 tool has zero parameters, so the schema fully covers the input surface. With 0 params, the baseline is 4, and the description appropriately focuses on output and usage behavior rather than parameter details.

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 'Returns the caller's current quota state' and enumerates the exact fields: operations used, remaining, daily limit, tier, and reset time. This distinguishes it from sibling tools, none of which are quota-focused, so an agent can confidently separate it from business-action tools.

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 includes explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections. It tells the agent to call at session start or before write batches, not on every invocation, and explains that quota is already injected into write-tool responses. This is strong routing guidance with a clear alternative.

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

A3.9/5.0
Disambiguation4/5

Most tools target distinct resource+action pairs (find_business vs verify_business, check_booking_link vs import_booking_url, get_status vs get_outcome). The main confusable pairs are send_message vs send_transactional_confirmation and verify_business vs verify_company_record, but their descriptions draw clear boundary lines.

Naming Consistency4/5

The set overwhelmingly follows lower_snake_case verb_noun naming (call_business, check_quota, find_business, send_message, verify_company_record). Minor deviations like self_test and mint_key, plus inconsistent verb choices (lookup_ vs get_ vs find_), prevent a perfect score.

Tool Count3/5

At 23 tools, the server falls into the heavy range and bundles several unrelated domains: SMB booking/messaging, trade and sanctions compliance, company verification, and platform operations. Each tool is individually reasonable, but the set feels like multiple servers merged into one.

Completeness3/5

Core SMB workflows are well covered: find/verify/import/book, messaging with conversation handling, and compliance preflights. Notable gaps include no consent-record management even though send_message requires consent_record_id for marketing, no update/delete lifecycle for leads or businesses, and no webhook configuration despite webhooks being referenced.

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