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get_retirement_headroom

Read-onlyIdempotent

Scans scheduled generator retirements to identify near-term transmission grid headroom, returning retiring plants that free injection capacity at their point of interconnection, with proximity to substations and county-level queue pressure.

Instructions

Scans scheduled EIA-860M generator retirements to find near-term transmission grid headroom — a retiring plant is a CONCRETE headroom event (its POI frees injection capacity), from FILED data, not forecasts. Returns _entity=retirement_headroom_results: retiring generators inside your horizon (name, MW, fuel, prime mover, retirement_date), representative_point, nearest substations with distance_km + count within 25 km, county-level queue_pressure (competing in-progress MW), iso_context (the generator's own EIA balancing-authority code), and a pre-filled site_evaluation_handoff (analyze_site + get_water_risk args, capacity_mw = YOUR target load). Try: get_retirement_headroom target_mw=50 horizon_months=18 region_iso=MISO — "50 MW opening near a substation inside 18 months, sidestepping the 4-7yr mega-queue." Honesty: meta.caveat flags that filed dates are subject to ISO reliability reviews (RMR extensions). Use to find WHERE capacity opens next; for what's already queued use get_refined_queue; for one site use analyze_site.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-500; default varies by tool)
target_mwYesMinimum required headroom in megawatts (MW) — filters to retiring generators at/above this size. Also passed through as the handoff's analyze_site capacity_mw (the DC you are siting).
region_isoNoOptional target region or ISO (e.g., 'MISO', 'PJM', 'ERCOT', 'SPP', 'CAISO', 'NYISO', 'ISONE'). Matches the generator's own EIA balancing-authority code — real market boundaries, not state lines. Comma-separated for a union.
fuel_filterNoOptional filter for retiring fuel categories, substring-matched (e.g., 'Coal', 'Natural Gas', 'Petroleum').
horizon_monthsYesTime horizon to look ahead for planned retirements (e.g., 12, 18, 36).
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds meaningful context: it uses 'FILED data, not forecasts', lists return fields, mentions the meta.caveat about ISO reliability reviews, and explains the handoff to analyze_site. 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 long but well-structured: purpose first, then return fields, example, caveat, and usage guidance. Every sentence adds value, though some repetition could be tightened (e.g., 'honesty:' could be integrated). Overall, efficient for the information conveyed.

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 no output schema, the description fully explains return values including _entity, fields, substation details, queue pressure, and handoff. It covers all 5 parameters effectively and provides example usage. No gaps remain for agent decision-making.

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 baseline is 3. The description adds value by explaining that target_mw is also passed as the handoff capacity_mw, clarifying region_iso uses actual ISO codes vs state lines, and noting fuel_filter uses substring matching. This goes beyond the schema 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 clearly states the tool's purpose: 'Scans scheduled EIA-860M generator retirements to find near-term transmission grid headroom'. It uses a specific verb ('scans') and resource ('retirements') and explicitly distinguishes from siblings like get_refined_queue and 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?

Provides an explicit example (target_mw=50 horizon_months=18 region_iso=MISO), explains when to use this tool vs alternatives ('Use to find WHERE capacity opens next; for what's already queued use get_refined_queue; for one site use analyze_site'), and includes a caveat about ISO review extensions.

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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