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build_tender

Build an ocean freight RFP structure by submitting lanes and volumes. Get market-rate bands, service requirements, award criteria, bid sheet, timeline, and total spend.

Instructions

Build the structure of a freight RFP / TENDER to put your ocean network out to bid. Pass your lanes with annual volumes and it returns, per lane, the volume + a modeled MARKET-RATE BAND (from our all-in rate engine, server-side) so you walk in knowing the credible price — the anchor that lets you spot a low-ball. Plus: the standard service requirements (fixed-day sailings, equipment commitment, reliability target, transparent surcharge formulas, free time), the AWARD CRITERIA weighted by your priority (cost / reliability / balanced), the BID SHEET columns carriers fill in, the RFP timeline (issue → Q&A → bids → evaluate → BAFO → award), and the modeled total annual spend. Pair with evaluate_bids to score the answers. Honest (regla 7): market bands are modeled, not filed tariffs. PREMIUM: pay per call with x402 (USDC on Base) or a prepaid key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lanesYesThe lanes to tender. Each: { origin_port, dest_port, annual_volume, container_type? }.
priorityNoAward weighting: 'cost', 'reliability' or 'balanced' (default).
Behavior4/5

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

No annotations exist, so the description carries full burden. It transparently explains return values (market-rate bands, model limitations with 'Honest (regla 7)'), the process timeline, and pricing model. It does not cover auth needs or rate limits but sufficiently discloses behavioral traits for a read-like build operation.

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 verbose yet well-structured, front-loading the core purpose and then detailing outputs. Every sentence adds value, justifying the length. Minor reduction for not being as tight as possible.

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 no output schema and two straightforward parameters, the description fully explains return values (per-lane details, criteria, bid sheet, timeline, total spend) and even links to evaluate_bids. It is complete for an agent to understand tool usage.

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%, but the description adds meaningful context: lanes are explained as 'your lanes with annual volumes' and priority as 'cost, reliability, balanced'. It also hints at optional container_type, enhancing schema documentation.

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 starts with a clear verb+resource: 'Build the structure of a freight RFP / TENDER to put your ocean network out to bid.' It distinctly defines the tool's purpose and differentiates it from siblings like evaluate_bids, which scores answers rather than constructing the framework.

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

Usage Guidelines3/5

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

Usage is implied: provide lanes and volumes to get a tender structure. The description mentions pairing with evaluate_bids but lacks explicit when-to-use vs alternatives or when-not-to-use guidance. Sibling context shows many related tools, but no comparative advice is given.

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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