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get_chokepoint_traffic

Monitor real-time vessel traffic and congestion at critical maritime chokepoints — Suez Canal, Panama Canal, Strait of Malacca, Strait of Hormuz, Bab el-Mandeb, and other strategic waterways. Returns total vessel count, average speed, count of slow or stationary vessels, and a congestion score with severity level. When chokepoints congest or close, global shipping routes reroute within days — this data detects that signal in real time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior4/5

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

With empty annotations, the description carries the full burden. It transparently states the tool monitors and returns data, listing output fields (vessel count, average speed, slow/stationary count, congestion score). It also adds the behavioral context of detecting rerouting signals. However, it does not explicitly mention whether the operation is read-only, but 'monitor' and 'returns' imply it. No side effects are suggested, and the real-time aspect is disclosed.

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 three sentences: the first states the core purpose and scope, the second lists the return fields, and the third provides the rationale. It is front-loaded with the key idea, contains no redundant words, and is well-structured.

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?

For a tool with no parameters, no output schema, and no annotations, the description is quite complete. It names the specific chokepoints, lists the return metrics, and explains the signal it detects. It could add details about the time window or data units, but these are minor gaps for a real-time monitor.

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?

There are 0 parameters, so the baseline is 4. The description does not need to explain parameter semantics because there are none. It instead focuses on the tool's output and purpose, which is appropriate.

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 uses the specific verb 'monitor' and clearly identifies the resource: 'real-time vessel traffic and congestion at critical maritime chokepoints'. It lists concrete examples (Suez Canal, Panama Canal, etc.), which distinguishes it from sibling tools like 'port_congestion_monitor' that focus on ports. The return fields are also named, making the purpose unmistakable.

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 provides clear context for when to use the tool: 'When chokepoints congest or close, global shipping routes reroute within days — this data detects that signal in real time.' This implies a use case but does not explicitly contrast with alternatives or state when not to use it. It gives enough guidance without explicit exclusions.

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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TDQS

A4/5.0
Disambiguation4/5

Most tools have distinct purposes targeting specific supply chain dimensions like commodity prices, port congestion, or manufacturing indicators, with clear boundaries. However, some overlap exists between tools like 'get_commodity_volatility_alerts' and 'commodity_price_monitor', which both focus on commodity price changes, potentially causing confusion in tool selection.

Naming Consistency4/5

Tool names follow a consistent 'verb_noun' pattern (e.g., 'get_action_signals', 'get_air_cargo_disruptions'), with minor deviations like 'commodity_price_monitor' and 'manufacturing_output_indicator' using noun-based naming. This maintains readability but slightly breaks the overall convention.

Tool Count2/5

With 25 tools, the count feels excessive for a single server, likely overwhelming users and agents. The server covers a broad domain, but many tools could be consolidated (e.g., multiple commodity-related tools) to reduce complexity and improve focus.

Completeness5/5

The tool set provides comprehensive coverage of the supply chain domain, including risk assessment, real-time monitoring, predictive analytics, and executive reporting. It supports full lifecycle management from data retrieval to actionable insights, with no obvious gaps in functionality.

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