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get_scorecard

Read performance scorecards for carriers, suppliers, or lanes. Get on-time percentage, delay, damage rates, reliability score, and trend to identify best and worst performers for award decisions.

Instructions

Read your accumulating supplier/carrier/lane SCORECARD — the KPIs you've fed with record_performance. Returns, per subject, on-time %, average delay, damage/discrepancy/rollover rates, a 0-100 reliability score and an improving/declining/stable TREND, ranked best-OTP-first, with the best & worst performer. Omit 'subject' for the whole network or pass one to drill in. The standing performance history that turns freight-pulse into a recurring decision tool (who do I award next year's volume to?). Honest (regla 7): your own empirical log, small samples flagged. PREMIUM: pay per call with x402 (USDC on Base) or a prepaid key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectNoDrill into one carrier/supplier/lane. Optional — omit for the whole scorecard.
subject_typeNo'carrier' (default), 'supplier' or 'lane' — disambiguates the subject.
Behavior4/5

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

With no annotations, the description implies read-only via 'Read', discloses cost details, and mentions that data is based on own empirical logs with small samples flagged, adding transparency.

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

Conciseness3/5

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

The description contains multiple sentences with some marketing language and could be more concise, though it front-loads the core purpose.

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?

Comprehensively describes the return fields (on-time %, delay, rates, reliability score, trend, ranking, best/worst performer), no output schema exists, and includes data source and cost context.

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 description adds value beyond the schema by explaining how to use the 'subject' parameter (omit for whole network, pass one to drill in) and mentions disambiguation via 'subject_type'. Schema coverage is 100%.

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 reads a scorecard of KPIs for suppliers, carriers, or lanes, distinguishing it from other analytics tools by specifying it's based on data from record_performance.

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

Usage Guidelines4/5

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

Provides guidance on using the optional 'subject' parameter to drill down into a specific entity or omit for the whole network, but does not explicitly mention alternatives or when not to use the tool.

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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