ledger
Public delivery ledger: totals, delivered-or-refunded %, volume, countries, recent orders.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Public delivery ledger: totals, delivered-or-refunded %, volume, countries, recent orders.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral fact beyond that — the ledger is 'public', implying no authentication or account scoping — but says nothing about time range, freshness, or aggregation granularity, which matters for interpreting totals.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence with zero waste, and the most distinguishing detail ('public delivery ledger') is front-loaded. It loses a point for being a fragment rather than a clause with a verb, which slightly impairs scannability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no parameters, the description carries the burden of explaining what comes back, and its enumeration of totals, delivered-or-refunded %, volume, countries and recent orders does reasonable duty. It still omits the time window the totals cover and the response shape, which an agent needs to report results accurately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters and the schema is an empty object, so there is nothing for the description to disambiguate. Baseline 4 applies; the only minor gap is not clarifying that no filters (date range, country) are accepted, which the agent might otherwise assume from the listed metrics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific resource (a public delivery ledger) and enumerates the metrics it exposes, which distinguishes it from the transactional siblings (buy, quote, order_status). However, it is a bare noun phrase with no verb or scope statement, so the agent must infer that it retrieves a read-only aggregate report rather than performs any action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to call this versus alternatives such as order_status or verify_receipt, and no exclusions or prerequisites. The agent is left to guess that this is a summary/analytics endpoint rather than a per-order lookup.
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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