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assess_supply_chain_redundancy

PAID (400 credits) — checks whether two supposedly-redundant sites (e.g. two "backup" suppliers/warehouses/data centers) are actually independent: real geodesic distance between them + each site's own multi-source hazard profile (seismic + FEMA + NOAA) side by side, plus any FEMA disaster incident types they share in the last 10 years. No invented "redundancy score" — the caller judges independence from the real data. CAVEAT: FEMA disaster history is STATE-level, not point-level — two sites in the same state usually share most incident types regardless of true distance, so distance_km is the more reliable independence signal for same-state comparisons. Requires Authorization: Bearer and sufficient credits balance. Returns JSON: {ok, distance_km, site_a, site_b, shared_fema_incident_types_10y, note}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_aYes
site_bYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It explicitly notes the tool is PAID (400 credits), requires Authorization and sufficient balance, and returns a specific JSON structure. It also discloses the FEMA state-level limitation, which is a significant behavioral nuance beyond what annotations would likely cover.

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 information-dense but every sentence earns its place: purpose, methodology, caveat, auth requirement, and return format. It is front-loaded with the core action and includes no fluff.

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?

The description covers purpose, methodology, caveats, authentication, and return fields, which is robust given the presence of an output schema. The main gap is input coordinate format clarity, but overall it is highly complete for a geospatial analysis tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions for site_a and site_b (0% coverage), so the description must compensate. It clarifies that these two parameters represent the two sites being compared, but does not specify coordinate format (e.g., lat/lng order, GeoJSON) or units. This leaves ambiguity for a geospatial tool.

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's function: it checks whether two supposedly-redundant sites are actually independent, using geodesic distance, multi-source hazard profiles, and shared FEMA incident history. This specific verb+resource combination distinguishes it from the many sibling assess_* tools.

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 implies usage context: evaluating redundancy for backup suppliers, warehouses, or data centers. It also provides a critical caveat about FEMA state-level data, advising that distance_km is more reliable for same-state comparisons. However, it does not explicitly mention when not to use the tool or name alternative tools.

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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