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cold_chain

Analyze temperature-controlled shipments for cold-chain compliance, thermal excursion risk, and lowest-total-cost mode and packaging. Compares ocean reefer, passive packaging, and air options with expected loss assessment.

Instructions

Cold-chain / pharma (GDP) compliance for a TEMPERATURE-CONTROLLED shipment — beyond a reefer setpoint. Give the lane + the product (e.g. 'pharma vaccines 2-8°C', 'frozen seafood', 'bananas') or a sensitivity class, and it returns the temperature requirement, the THERMAL-EXCURSION risk across the transit, the recommended MODE + thermal packaging, and the GDP datalogger/chain-validation needs. The core insight: excursion risk RISES with transit DURATION. It reads the iter3 transit p90 for the ocean routing and runs a survival model per packaging option (ocean active reefer, ocean qualified-passive PCM/VIP, active air) — a long Cape-diverted reefer accumulates far more deviation exposure (and a gen-set/fuel/plug failure tail) than a 3-day air leg. Each option is totalled = freight + packaging premium + monitoring + EXPECTED THERMAL LOSS (excursion × loss-fraction × cargo value), and the lowest-total option wins. Proves: pharma 2-8°C on a long transit → high excursion risk → fly it with active cooling OR use qualified passive packaging; a frozen load on a short lane → ocean reefer is fine. For GDP cargo it mandates continuous data-logging, pre-cool, a validated lane and a documented chain. Honest (regla 7): INDICATIVE GDP/cold-chain model — excursion probabilities, MKT, packaging performance and loss fractions are modeled typicals, NOT a GDP qualification, stability statement or QA release. PREMIUM: pay per call with x402 (USDC on Base) or a prepaid key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
origin_portYesOrigin port (city name, UN/LOCODE, or 'City, Country').
dest_portYesDestination port.
container_typeNoContainer '20ft'/'40ft'/'40HC'. Optional; default '40ft'.
ship_dateNoShip date (YYYY-MM-DD) — selects the transit/diversion state. Optional; default today.
productNoProduct description — 'pharma vaccines 2-8°C', 'frozen seafood', 'bananas', 'fresh produce', 'insulin'. Sets the temperature requirement & sensitivity.
sensitivityNoExplicit sensitivity class — ambient | cool | chilled | frozen | pharma | pharma-critical. Overrides the product match. Provide this OR 'product'.
cargo_value_usdNoTotal cargo value (USD) — drives the expected-loss economics. Optional; a class default is used if omitted.
unit_value_usdNoPer-unit value (USD) — with 'units', an alternative to cargo_value_usd. Optional.
unitsNoNumber of units (with unit_value_usd). Optional.
ocean_freight_usdNoOverride the ocean all-in freight per container (USD). Optional — derived if omitted.
air_freight_multipleNoAir freight as a multiple of ocean (default ~6-7×). Optional.
Behavior5/5

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

No annotations provided, so description carries full burden. It is highly transparent: explains the survival model, expected total cost calculations, assumptions, and includes a disclaimer about the indicative nature. Even mentions payment method.

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 long but well-structured: purpose first, then details, then disclaimer. It is packed with information but could be slightly more concise. Front-loads key 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?

Given 11 parameters, no output schema, and no annotations, the description is very complete. It explains the model, economics, inputs, outputs, and limitations. No obvious gaps.

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?

Schema coverage is 100% with descriptions for all 11 parameters. The description adds value by explaining how parameters like cargo_value and product are used in economic analysis, beyond basic schema definitions.

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 it provides cold-chain/pharma compliance for temperature-controlled shipments, returning specific outputs like temperature requirement, excursion risk, recommended mode and packaging. It is distinct from sibling tools which cover other logistics functions.

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?

The description explicitly says when to use: for temperature-controlled shipments beyond a reefer setpoint, and gives examples of products and sensitivity. It does not explicitly state when not to use, but the context implies it is specialized for cold chain.

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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