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azmartone67

DC Hub — Data Center & Energy Intelligence

Get Fiber Readiness

get_fiber_readiness
Read-onlyIdempotent

Assess fiber connectivity for a specific site: get near-net distance, number of reachable carriers, and single-carrier risk verdict from lat/lon.

Instructions

Use when you need the FIBER-READINESS / connectivity verdict for ONE parcel or site (lat/lon): near-net distance to a carrier-served facility, how many distinct fiber carriers are reachable, and whether there is single-carrier risk (no path diversity). This is the parcel connectivity answer engineering site-selectors screen on. Example: "Is this Loudoun County parcel fiber-ready and how many carriers can serve it?" — get_fiber_readiness lat=39.04 lon=-77.48 radius_km=50. Params: lat (-90..90, required), lon (-180..180, required), radius_km (search radius in km, default 50, range 5-200). Returns: {score 0-100, near_net_bucket ("on-net"|"near-net"|"acceptable"|"build-required"), nearest_carrier_km, carrier_count, top_carriers:[{carrier, distance_km}], single_carrier_risk (bool), fiber_coverage_km, verdict_short}. Do NOT use to map carrier ROUTES between metros (use get_fiber_intel) or for a full multi-factor site suitability score (use analyze_site).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoSite latitude in decimal degrees (-90 to 90, required), e.g. 39.04
lngNoAlias for lon — either name works
lonNoSite longitude in decimal degrees (-180 to 180, required), e.g. -77.48
latitudeNoAlias for lat — either name works
longitudeNoAlias for lon — either name works
radius_kmNoSearch radius in km for reachable fiber carriers (default 50, range 5-200)

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?

Beyond annotations (read-only, idempotent, non-destructive), the description discloses the exact output structure (score, near_net_bucket, nearest_carrier_km, carrier_count, etc.), the single-parcel scope, and the risk of single-carrier no path diversity. This adds significant behavioral context not present in the annotations.

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 front-loaded with the core purpose, then provides an example, parameter summary, return shape, and exclusions. Every sentence earns its place; there is no redundancy or filler, and the structure is logical.

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 is fully self-contained: it explains the use case, scope, output schema, exclusions, and alternatives. Even though an output schema exists, the description adds extra clarity by naming the return fields and the specific verdict buckets, making it complete for an agent.

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 coverage is 100%, so baseline is 3. The description repeats parameter ranges and defaults (lat -90..90, lon -180..180, radius_km default 50 range 5-200) but adds no meaning beyond the schema, which already documents these fully. The example does not clarify any ambiguity.

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 purpose: it returns a fiber-readiness verdict for ONE parcel/site, including near-net distance, carrier count, and single-carrier risk. It explicitly distinguishes from siblings by saying 'Do NOT use to map carrier ROUTES between metros (use get_fiber_intel) or for a full multi-factor site suitability score (use analyze_site)'.

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?

It provides explicit when-to-use guidance: 'Use when you need the FIBER-READINESS / connectivity verdict for ONE parcel or site'. It also gives a concrete example query and explicit exclusions with alternative tools, satisfying the when-not-to-use requirement.

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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