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DC Hub — Data Center & Energy Intelligence

Save To Shortlist

save_to_shortlist

Save data center sites to a persistent, named shortlist that survives across conversations. Then re-score them later against the evolving baseline.

Instructions

Save a site into a PERSISTENT, named shortlist that survives across conversations (Phase 5 statefulness). Snapshots the site's objectives + its current percentile objective_score, so you can re-score it later against the evolving national baseline. Use to build a durable siting shortlist across days/weeks; the list is scoped to your API key. Pair with get_shortlist to re-score + see drift. MINIMAL call: save_to_shortlist(shortlist_name="my-targets", site={site_ref, lat, lng, capacity_mw}) — objectives are optional. If you DID rank the site (analyze_site / rank_sites), pass those metric fields inside site and your objectives map too, and the re-scoring reuses them. Requires an API key so the list is private to you and survives to your next conversation: call claim_free_key first if you have none.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite object. MINIMAL form is enough: {site_ref, lat, lng, capacity_mw}. Richer is better — add any analyze_site metric fields (risk_resilience, fiber_connectivity, water score…) and those become what gets re-scored later.
notesNoOptional free-text note, e.g. "strong fiber, acceptable water"
objectivesNoOPTIONAL {field: signedWeight} map (+maximize/-minimize) if this site was ranked under explicit objectives — stored so re-scoring reuses the same criteria. Omit it and DC Hub weights the site's own metric fields equally.
shortlist_nameYesName of the shortlist, e.g. "Q3-2026-1GW-targets" — created if new. REQUIRED.

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?

The description discloses rich behavioral traits beyond annotations: persistence across conversations, snapshot of objectives and percentile objective_score, re-scoring against evolving national baseline, API-key scoping/private access, and the optional-objectives default behavior ('Omit it and DC Hub weights the site's own metric fields equally'). No contradiction with annotations (readOnlyHint=false) since the description correctly implies a write operation.

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 dense but every sentence earns its place: purpose, mechanism, use case, companion tool, minimal call example, optional enrichments, and prerequisite. It is well-structured with a logical flow from 'what' to 'how' to 'when'. No redundant phrases or filler.

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?

Given the tool's complexity (4 params, nested site object, stateful behavior), the description is complete. It covers the minimal invocation, optional enrichments, default behavior, API key requirement, and integration with get_shortlist. The presence of an output schema means return-value details need not be in the description, but the description still gives enough context to use the tool correctly.

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

Parameters5/5

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

Though schema coverage is 100%, the description adds significant semantics: a minimal call example, explanation of what 'site' fields are used for re-scoring ('add any analyze_site metric fields... those become what gets re-scored later'), the purpose of 'objectives' and the consequence of omission, and that 'shortlist_name' is created if new. This goes beyond the schema's field descriptions.

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 opens with a specific verb+resource: 'Save a site into a PERSISTENT, named shortlist that survives across conversations.' It clearly differentiates from siblings by referencing 'Pair with get_shortlist' and distinguishing from save_site/analyze_site/rank_sites contexts. The scope ('scoped to your API key') and statefulness ('Phase 5 statefulness') add precision.

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 when-to-use guidance: 'Use to build a durable siting shortlist across days/weeks.' Conditions are provided: 'If you DID rank the site (analyze_site / rank_sites), pass those metric fields...' It also names the companion tool (get_shortlist) and prerequisite ('call claim_free_key first if you have none'). This is model clarity.

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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