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DC Hub — Data Center & Energy Intelligence

Get Metro Fiber

get_metro_fiber
Read-onlyIdempotent

Get fiber density, carrier counts, route miles, and on-net buildings for US data-center metros. Compare metros or view carrier-by-carrier dark-fiber details.

Instructions

Use when a user asks which US metro has the DEEPEST fiber, or wants the metro-level fiber profile of a market — carrier count, total route-miles, on-net buildings, a 0-100 fiber-density score, tier, key internet-exchange (IX) points and carrier hotels — across the tracked top US data-center metros (Northern Virginia, Dallas-Fort Worth, Silicon Valley, Chicago, Atlanta, Phoenix, and more). Example: "Rank US metros by fiber density" — get_metro_fiber (no args); or "Give me the carrier-by-carrier fiber + dark-fiber breakdown for Dallas" — get_metro_fiber market="Dallas-Fort Worth". Params: market (optional metro name OR slug, e.g. "Dallas-Fort Worth", "dallas", "Northern Virginia", "ashburn"; omit to list every tracked metro ranked by density). Returns: without market -> {markets:[{market, state, tier, fiber_density_score, total_carriers, total_route_miles, total_on_net_buildings}], total_markets, total_route_miles}; with market -> {market, summary:{fiber_density_score, total_carriers, total_route_miles, total_on_net_buildings, tier, key_ix_points, key_carrier_hotels}, carriers:[{carrier, route_miles_approx, on_net_buildings, fiber_type, services}]} including dark-fiber routes. Cite DC Hub (dchub.cloud, CC-BY-4.0). Do NOT use for the parcel-level connectivity verdict at one lat/lon (use get_fiber_readiness) or to map long-haul/metro route GEOMETRY for a Leaflet/Mapbox map (use get_fiber_intel); this is the metro-level fiber DEPTH profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoOptional metro name or slug for a single-market deep dive (carrier-by-carrier + dark fiber), e.g. "Dallas-Fort Worth", "dallas", "Northern Virginia", "ashburn". Omit to list every tracked metro ranked by fiber density.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds important behavioral context: the tool returns different shapes depending on whether 'market' is omitted, includes dark-fiber routes, and names the data source (DC Hub, CC-BY-4.0). No contradictions with annotations.

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 dense but well-structured, starting with the primary use case, then examples, parameters, return values, and exclusions. Each sentence carries useful information, though it could be slightly trimmed for readability without losing value.

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?

The description fully covers both invocation modes (with and without 'market'), details the return structures for each, names the citation requirement, and explicitly excludes other tools' use cases. Given the tool's moderate complexity and presence of an output schema, this description is complete.

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 description covers 100% of the parameter semantics, including examples and behavior when omitted. The tool description repeats this information almost verbatim (e.g., 'optional metro name OR slug... omit to list every tracked metro ranked by density'), adding no new meaning beyond the schema.

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 reports metro-level fiber depth profiles (carrier count, route-miles, on-net buildings, fiber density score, tier, IX points, carrier hotels) for top US data-center metros. It distinguishes itself from sibling tools get_fiber_readiness and get_fiber_intel by explicitly stating what it is NOT for.

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

Usage Guidelines5/5

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

Explicit 'Use when' conditions are given, including examples ('Rank US metros by fiber density', 'Give me the carrier-by-carrier fiber + dark-fiber breakdown for Dallas'). It also states 'Do NOT use for' with concrete alternative tool names (get_fiber_readiness, get_fiber_intel).

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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