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FERC Form 1 Plant Costs API v1

Generated from core.contract.describe_power_plant_costs_v1() and checked fixture-backed examples. Do not hand-edit the example JSON files.

Capability

What It Can Answer

Represented Facts

Data Point Contract

Does not answer:

REST Surface

MCP Surface

Local MCP Setup

Some MCP clients launch servers from the user's home directory or ignore a configured cwd. Use uv run --directory so the server always starts from the repository project.

{
  "command": "uv",
  "args": [
    "run",
    "--directory",
    "/absolute/path/to/OSINT",
    "python",
    "-m",
    "core.mcp_server"
  ]
}

Leave EXASCALE_PARQUET_BASE / EXASCALE_RAW_BASE unset: the one server hosts every data point's tools, and with no override it resolves each block's promoted snapshots and raw archive from the repository layout. Setting either env var points ALL tools at one directory — a per-block path breaks every other block's tools. They exist only for single-source sandboxes and tests.

Request Schema

Filters:

Group by:

Date range parameters:

Controls:

Ranking (how order_by / top_n / order join — order_by ranks groups by a metric, never a group_by dimension; top_n needs both a group_by and an order_by):

{
  "no_ranking": "Omit order_by and top_n to return all groups in group-key order.",
  "order": {
    "default": "desc",
    "valid_values": [
      "desc",
      "asc"
    ]
  },
  "order_by": {
    "accepts": "one of output.metrics",
    "note": "Ranks the groups by a metric (a measure). Not a group_by dimension \u2014 rows already come back grouped by each group_by field.",
    "requires": [
      "group_by"
    ],
    "valid_values": [
      "value",
      "source_record_count",
      "distinct_respondent_count",
      "distinct_plant_count"
    ]
  },
  "top_n": {
    "note": "Keeps the top N groups by order_by; the rest fold into one (other) remainder (additive metrics sum into it, non-additive ones are nulled) so the result still reconciles to summary.totals.",
    "requires": [
      "group_by",
      "order_by"
    ],
    "type": "positive integer"
  }
}

Output Schema

Aggregate metrics:

Metric groups:

{
  "as_filed_value": [
    "value"
  ],
  "entities": [
    "distinct_respondent_count",
    "distinct_plant_count"
  ],
  "records": [
    "source_record_count"
  ]
}

Response summary fields:

Accepted fact policy:

Metric metadata:

Metric Category Unit Aggregation Additive Across Groups Authoritative Total Definition
value as_filed_value source physical unit single fact only false summary.totals.value One as-filed Form 1 XBRL fact; inspect unit and measure before use.
source_record_count records count count source records true summary.totals.source_record_count Count of separately cited XBRL facts in scope.
distinct_respondent_count entities count count_distinct false summary.totals.distinct_respondent_count Count of distinct FERC respondent CIDs with facts in scope.
distinct_plant_count entities count count_distinct false summary.totals.distinct_plant_count Count of distinct respondent CID plus raw plant-name pairs in scope.

Rollup rules:

Detail record fields returned when include_records is true:

Row-level citation fields:

Aggregate citation fields:

Codebooks

Field Coverage Codes Examples Note

The complete machine-readable codebooks are included in capability-schema.json.

Checked Examples

Agent question Request params Checked output
What as-filed plant facts did respondent C001111 report for Steam Plant Alpha in 2025? {"plant_name_contains": "Steam Plant Alpha", "report_year": 2025, "respondent_id": "C001111"} respondent-plant-facts.json
Which separate production-expense line items were filed for respondent C001111? {"measure_category": "production_expense", "report_year": 2025, "respondent_id": "C001111"} separate-production-expenses.json
Which served Form 1 respondents have a raw states-served disclosure mentioning Texas? {"ercot_relevance": true, "report_year": 2025} ercot-relevance.json
Return one as-filed plant-cost fact with its exact XBRL fact citation. {"include_records": true, "limit": 1, "report_year": 2025} plant-cost-detail-with-citation.json
Verify the raw workbook row behind a returned citation citations[ref].verify (aggregate) or records[0].citation (detail) source-row-evidence.json
Dogfood the tool sequence as an agent list -> describe -> query -> evidence agent-dogfood-transcript.json

The checked schema output is capability-schema.json.

Agent Workflow

  1. Call list_capabilities_v1 and select power.plant_costs.
  2. Call describe_power_plant_costs_v1 to inspect valid filters, groupings, metrics, and citation fields.
  3. Call query_power_plant_costs_v1 with bounded JSON params.
  4. If the answer needs proof, pass a returned row-level citation object to get_source_evidence_v1.
  5. Answer with the resolved as_of and relevant citations. Present returned metrics as authoritative for their declared source, snapshot, grain, and aggregation.
Generated from the tested API contract. Compare with the live capability map ↗