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Ledger

get_ledger
Read-onlyIdempotent

Every movement of money on the account, newest first: top-ups, each campaign's price (set aside and charged at launch), refunds. The balance after each row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return, default 100
apiKeyYesYour Clearvoyance API key (cv_live_… or cv_test_…), from create_account

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description correctly aligns with a non-destructive, read-only operation. It adds behavioral detail beyond annotations by specifying the exact content (top-ups, campaign prices with set-aside and launch-charge semantics, refunds) and the ordering (newest first) plus the running balance after each row. This enriches the agent's understanding of what to expect without contradicting annotations.

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 concise sentences that front-load the core purpose ('Every movement of money on the account') and then enumerate the transaction types and the balance-after-each-row detail. Every word earns its place; there is 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?

Given the presence of an output schema (as indicated), the description does not need to detail the return structure. It covers the essential domain semantics (transaction types and ordering) and aligns with the read-only safety profile. However, it omits any mention of pagination or behavior with large result sets, though the limit parameter partially addresses that. Overall, it is complete enough for an agent to call the tool 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?

The input schema provides complete descriptions for both parameters: apiKey explains the key format and source, and limit includes default and range. With 100% schema description coverage, the description adds no additional parameter meaning. Baseline of 3 is appropriate since the schema carries the semantic load.

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 a ledger of all money movements (top-ups, campaign prices, refunds) with balance after each row, sorted newest first. It uses a specific verb-like framing ('Every movement of money') and distinguishes from siblings like get_account or check_topup by focusing on transactional history rather than balances or single operations.

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 is provided on when to use this tool versus alternatives. It does not mention that it is the go-to for viewing transaction history, nor does it exclude cases like checking a specific top-up (check_topup) or account details (get_account). The agent must infer usage from context, and there are no explicit conditions or alternatives cited.

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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