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smallest-inc

Smallest MCP Server

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by smallest-inc

get_credit_ledger

Retrieve your organization's credit transaction history including purchases, usage deductions, bonuses, and adjustments. Filter by date, type, or scope to audit credits.

Instructions

Get the credit transaction history (ledger) for your organization. Shows purchases, usage deductions, bonuses, admin adjustments, coupon credits, and more. Supports filtering by date range, transaction type, and scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax entries to return (default 50)
offsetNoOffset for pagination (default 0)
fromNoStart date filter (ISO 8601, e.g. '2025-01-01')
toNoEnd date filter (ISO 8601, e.g. '2025-01-31')
typeNoFilter by transaction type
scopeNoFilter by product scope
Behavior3/5

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

No annotations exist, so the description carries the burden. It states 'Get' implying read-only, but doesn't confirm auth needs, rate limits, or pagination behavior beyond parameters. Lacks explicit safety guarantees, but adequately describes what the tool returns.

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?

Two sentences efficiently convey purpose and key features. Front-loaded with the primary action (Get credit transaction history) and then details. No unnecessary words, though slight structure improvement could combine ideas.

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

Completeness2/5

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

Despite 6 parameters and no output schema, the description omits return format, default sorting, pagination details, and any behavioral caveats. Given sibling diversity, more context (e.g., response structure) is needed for robust usage.

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 description coverage is 100%, so the schema already documents each parameter well. The description adds only a high-level mention of filtering, not deeper meaning. Baseline score 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 the tool retrieves credit transaction history (ledger) and lists specific transaction types (purchases, usage deductions, etc.), which distinguishes it from sibling tools like get_credit_balance and get_credit_usage.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives (e.g., get_credit_balance, get_credit_usage). It doesn't mention prerequisites or scenarios where this tool is preferred, leaving the agent to infer context.

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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