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Rank Sites

rank_sites
Read-onlyIdempotent

Deterministic multi-site ranking/optimization under constraints — the normalization contract that lets you compare sites across separate analyze_site calls WITHOUT dropping into code. Pass candidates you already enriched (each an object with lat/lng + metric fields like risk_resilience, water_stress, fiber_km — pull these from analyze_site + get_refined_queue and pass site_evaluation_handoff through untouched), hard constraints, and weighted objectives; get back entity=ranked_sites: top_k ranked with rank, objective_score, per-field normalized{} (0-100 relative to the set), and normalization_basis. objectives use SIGNED weights: +weight maximizes a field (e.g. risk_resilience:1), -weight minimizes it (e.g. water_stress:-0.6, fiber_km:-0.4). constraints are hard filters, fail-closed on a missing field. Use for "pick the best N sites under constraints"; for one site use analyze_site; to get the candidate set first use get_refined_queue. SCORING MECHANICS (2026-07-11): a candidate missing a validated objective is weight-RENORMALIZED over the objectives it carries and the gap is DECLARED in missing_objectives (never silently scored 0); a candidate carrying none scores null and ranks last. percentile=true fields without a population baseline fall back to RELATIVE in-batch scoring (basis reported per-objective in objective_status). CANDIDATE CONTRACT: candidates may be {candidate_id: "cand…"} entries from get_refined_queue — frozen identity (lat/lng/capacity_mw/fiber_km/iso) loads from the mint, your metrics overlay the rest; expired/unknown ids are dropped AND declared in candidate_contract, never re-resolved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_kNoHow many top-ranked sites to return (1-50, default 3)
absoluteNofalse (default) = min-max normalize within THIS batch (best-in-set, NOT stable across runs). true = score on a FIXED 0-100 scale for CROSS-RUN-STABLE, auditable scores — use ONLY when the objective fields are already 0-100 (analyze_site scores like risk_resilience/fiber_connectivity), not raw distances like fiber_km
candidatesNoArray of candidate objects. PREFERRED: {candidate_id: "cand_…", <your metric fields>} using ids from get_refined_queue — frozen coordinates/capacity/fiber_km load from the mint (zero transcription drift), your enrichments (e.g. overall_score from analyze_site) overlay. Legacy: {id?, lat?, lng?, <metric fields>} flat objects also work. Omit if using shortlist_name
objectivesNoWeighted objectives {field: signedWeight} — +weight maximizes, -weight minimizes. e.g. {"water_stress": -0.6, "fiber_km": -0.4}. Omit with shortlist_name to reuse the shortlist's saved objectives; required with candidates
percentileNotrue = score each objective as its PERCENTILE against the viable-site POPULATION ("better than X% of viable sites") — the strongest cross-run + cross-region comparability. Works for fields with a maintained baseline (analyze_site metrics: overall_score, risk_resilience, fiber_connectivity, power_infrastructure, market_conditions, gas_pipeline_access, fiber_km, power_cost); other fields fall back to absolute (listed in unbaselined_fields). Takes precedence over absolute
constraintsNoHard filters {field: {min?, max?}} — a candidate missing a constrained field is dropped (fail-closed). e.g. {"risk_resilience": {"min": 70}, "estimated_ttp_months": {"max": 34}}
shortlist_nameNoAlternative to candidates: re-rank a SAVED shortlist (created via save_to_shortlist) in one shot — loads its sites (scoped to your API key) + reuses their saved objectives if you pass none, and re-scores against the current baseline
require_completeNotrue = DROP any candidate missing one or more of your (validated) objectives — dropped candidates are DECLARED in excluded_incomplete, never silent. Default false keeps incomplete candidates ranked on their carried objectives with missing_objectives flagged. Recommended true for autonomous take-rank-1 workflows (an incomplete candidate can otherwise top the ranking on its single best metric).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier).
_entityNoPayload class (facility|market|iso_grid|queue_results|deal|report|response); branch on it.
citationNoHow to attribute DC Hub: {source, url, license, cite_as, retrieved_at}, or the attribution line as a string.
provenanceNoSource, method, as_of, verification_counts, license, cite_as; quote it when citing.
_front_doorNoFirst-tool hint: plan_query(intent) returns the ordered plan.
_return_loopNoNext-session delta call (get_changes).
site_evaluation_handoffNoFollow-up calls [{tool, parameters, why}] when the payload carries coordinates.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  4. Changed5 schema fields changed
    • removedOutput schema / properties / citation / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / citation / anyOf
      Added value: +[
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  },
      +  {
      +    "type": "string"
      +  }
      +]
    • changedOutput schema / properties / citation / description
      Previous value: -"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload."New value: +"Machine-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."
    • removedOutput schema / properties / citation / properties
      Removed value: -{}
    • removedOutput schema / properties / citation / type
      Removed value: -"object"
  5. Changed1 schema field changed
    • addedOutput schema / properties / _front_door
      Added value: +{
      +  "additionalProperties": {},
      +  "description": "In-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.",
      +  "properties": {},
      +  "type": "object"
      +}
  6. Changed5 schema fields changed
    • removedOutput schema / properties / site_evaluation_handoff / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / site_evaluation_handoff / anyOf
      Added value: +[
      +  {
      +    "items": {
      +      "additionalProperties": {},
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "type": "array"
      +  },
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  }
      +]
    • changedOutput schema / properties / site_evaluation_handoff / description
      Previous value: -"Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates."New value: +"Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
    • removedOutput schema / properties / site_evaluation_handoff / properties
      Removed value: -{}
    • removedOutput schema / properties / site_evaluation_handoff / type
      Removed value: -"object"
  7. Changed4 schema fields changed
    • changedInput schema / properties / top_k / description
      Previous value: -"How many top-ranked sites to return (default 3)"New value: +"How many top-ranked sites to return (1-50, default 3)"
    • changedInput schema / properties / top_k / maximum
      Previous value: -9007199254740991New value: +50
    • changedInput schema / properties / top_k / minimum
      Previous value: --9007199254740991New value: +1
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": {},
      +  "description": "DC Hub envelope: structuredContent mirrors the JSON payload in content[0].text — tool-specific data fields ride at the top level alongside these envelope keys.",
      +  "properties": {
      +    "_entity": {
      +      "description": "Payload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.",
      +      "type": "string"
      +    },
      +    "_return_loop": {
      +      "additionalProperties": {},
      +      "description": "Suggested next-session delta call (get_changes since=24h) so you pull only what changed.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "citation": {
      +      "additionalProperties": {},
      +      "description": "Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "provenance": {
      +      "additionalProperties": {},
      +      "description": "Collection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "quota": {
      +      "additionalProperties": {},
      +      "description": "Caller quota state (remaining calls, tier) when available.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "site_evaluation_handoff": {
      +      "additionalProperties": {},
      +      "description": "Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates.",
      +      "properties": {},
      +      "type": "object"
      +    }
      +  },
      +  "type": "object"
      +}
  8. Changed2 schema fields changed
    • changedInput schema / properties / objectives / description
      Previous value: -"Weighted objectives {field: signedWeight} — +weight maximizes, -weight minimizes. e.g. {\"water_stress\": -0.6, \"fiber_km\": -0.4}"New value: +"Weighted objectives {field: signedWeight} — +weight maximizes, -weight minimizes. e.g. {\"water_stress\": -0.6, \"fiber_km\": -0.4}. Omit with shortlist_name to reuse the shortlist's saved objectives; required with candidates"
    • removedInput schema / required
      Removed value: -[
      -  "objectives"
      -]
  9. Changed1 schema field changed
    • changedInput schema / required
      Previous value: -[
      -  "candidates",
      -  "constraints",
      -  "objectives"
      -]New value: +[
      +  "objectives"
      +]
  10. Changed1 schema field changed
    • addedInput schema / properties / require_complete
      Added value: +{
      +  "description": "true = DROP any candidate missing one or more of your (validated) objectives — dropped candidates are DECLARED in excluded_incomplete, never silent. Default false keeps incomplete candidates ranked on their carried objectives with missing_objectives flagged. Recommended true for autonomous take-rank-1 workflows (an incomplete candidate can otherwise top the ranking on its single best metric).",
      +  "type": "boolean"
      +}
  11. Changed1 schema field changed
    • changedInput schema / properties / candidates / description
      Previous value: -"Array of candidate objects, each {id?, lat?, lng?, <metric fields>} — pre-enriched from analyze_site/get_refined_queue; carry site_evaluation_handoff through so the winners stay pipeable. Omit if using shortlist_name"New value: +"Array of candidate objects. PREFERRED: {candidate_id: \"cand_…\", <your metric fields>} using ids from get_refined_queue — frozen coordinates/capacity/fiber_km load from the mint (zero transcription drift), your enrichments (e.g. overall_score from analyze_site) overlay. Legacy: {id?, lat?, lng?, <metric fields>} flat objects also work. Omit if using shortlist_name"
  12. Changed2 schema fields changed
    • changedInput schema / properties / candidates / description
      Previous value: -"Array of candidate objects, each {id?, lat?, lng?, <metric fields>} — pre-enriched from analyze_site/get_refined_queue; carry site_evaluation_handoff through so the winners stay pipeable"New value: +"Array of candidate objects, each {id?, lat?, lng?, <metric fields>} — pre-enriched from analyze_site/get_refined_queue; carry site_evaluation_handoff through so the winners stay pipeable. Omit if using shortlist_name"
    • addedInput schema / properties / shortlist_name
      Added value: +{
      +  "description": "Alternative to candidates: re-rank a SAVED shortlist (created via save_to_shortlist) in one shot — loads its sites (scoped to your API key) + reuses their saved objectives if you pass none, and re-scores against the current baseline",
      +  "type": "string"
      +}
  13. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already establish the safe read-only/idempotent profile, and the description goes well beyond them: it discloses the normalization contract, signed-weight semantics, weight-renormalization of incomplete candidates with gaps declared in missing_objectives, percentile-baseline fallback, and that expired/unknown candidate ids are dropped and declared rather than silently re-resolved. This is rich behavioral disclosure of failure modes and edge cases.

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 core purpose and scope are front-loaded in the first sentence, and given the tool's complexity most sentences carry genuine content. However, it is dense, ALL-CAPS-heavy, and repeats mechanics (constraints fail-closed, missing_objectives) across the description, so it is not maximally tight.

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?

For an 8-parameter, high-complexity tool with an output schema, the description still covers the return shape (_entity=ranked_sites with rank, objective_score, normalized{}, normalization_basis) and the key edge cases (missing objectives, percentile fallback, candidate contract). Nothing essential to correct invocation appears to be missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds integration-level meaning beyond the schema: it explains where candidate metric fields come from (analyze_site + get_refined_queue, passing site_evaluation_handoff untouched) and the frozen-identity contract. It largely reinforces rather than extends the per-parameter docs, so it lands above baseline but not at the top.

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+resource (deterministic multi-site ranking/optimization under constraints) and explicitly distinguishes itself from siblings by naming analyze_site (one site) and get_refined_queue (candidate set). An agent can tell what this does and where it sits in the workflow without opening the schema.

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?

Gives an explicit trigger phrase ("pick the best N sites under constraints") plus when to use alternatives: analyze_site for a single site and get_refined_queue to obtain the candidate set first. This covers when-to-use, when-not, and the routing to siblings.

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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