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SKUit Network & Security Catalog

Search catalog platforms by port demand

catalog_search_platforms
Read-onlyIdempotent

Find published platforms that can serve a port demand (for example 60×100G plus 4×400G for a data-center top-of-rack switch), closest fit first: fewest spare ports, then fewest rack units, then least capacity headroom. Each result explains the fit and lists caveats (breakout cables, a non-default port mode, port-pairing rules) that you should pass on to the user. Also reports how many platforms of the use case meet the demand, how many could not be evaluated, and the nearest misses when nothing fits. Answers carry catalog_url (the public catalog page) and build_bom_url (Open in SKUit to build a full bill of materials; the builder requires a SKUit account).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many results (default 5, max 10).
vendorsNoOnly these vendors (case-insensitive).
form_factorNoOnly this form factor, e.g. "fixed" or "modular".
use_case_idYesDeployment role: "campus-access" (Campus access layer), "dc-tor" (ToR & Leaf), "dc-core" (DC core / spine), "wan-edge" (WAN edge / branch), "smb" (SMB / small campus), "campus-dist" (Campus distribution), "load-balancer" (Load balancer).
poe_requiredNoOnly platforms that supply PoE.
max_rack_unitsNoOnly platforms at most this many rack units tall.
port_requirementsYesThe ports needed, one row per speed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only cover read-only/idempotent safety, which the description does not repeat; instead it discloses the ranking algorithm (spare ports, then rack units, then headroom), the caveat payload, the aggregate counts, nearest-miss reporting when nothing fits, and the build_bom_url account requirement. This is unusually rich behavioral context beyond the structured fields.

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?

Single dense paragraph that front-loads the purpose and ranking rule before the result-payload detail, with essentially no filler. It is on the long side, but every clause carries information an agent can act on.

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?

There is no output schema, yet the description accounts for the return shape — fit explanation, caveats, meeting/unevaluable counts, nearest misses, and the two URLs — plus the account requirement for the builder. For a read-only search with 100% schema coverage, nothing an agent needs to call it correctly is missing.

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?

Schema description coverage is 100%, so all seven parameters are already documented in the schema and the baseline is 3. The description adds only an illustrative demand example (60×100G plus 4×400G), which conveys intent but no new syntax or constraint semantics.

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?

States a specific verb (Find) and resource (published platforms) scoped by a clear criterion (can serve a port demand), and the ranked-search behavior is plainly distinct from catalog_get_platform (single lookup) and catalog_find_alternatives. An agent knows immediately this is the demand-driven search entry point.

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?

Gives clear context for when to reach for it — when you have a port demand and want the closest-fitting published platforms — and tells the agent what to do with the results (pass caveats on to the user). It never names an alternative tool or states a when-not condition, so it stops short of full routing guidance.

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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