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MISO Capacity Accreditation (internal) API v1

Generated from core.contract.describe_power_capacity_accreditation_miso_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": [
      "avg_accreditation_ratio",
      "min_accreditation_ratio",
      "max_accreditation_ratio",
      "count_of_units",
      "source_record_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:

{
  "accreditation": [
    "avg_accreditation_ratio",
    "min_accreditation_ratio",
    "max_accreditation_ratio"
  ],
  "records": [
    "source_record_count"
  ],
  "units": [
    "count_of_units"
  ]
}

Response summary fields:

Accepted fact policy:

Metric metadata:

Metric Category Unit Aggregation Additive Across Groups Authoritative Total Definition
avg_accreditation_ratio accreditation fraction of one average false summary.totals.avg_accreditation_ratio Average MISO accreditation ratio over the current result scope.
min_accreditation_ratio accreditation fraction of one minimum false summary.totals.min_accreditation_ratio Minimum MISO accreditation ratio over the current result scope.
max_accreditation_ratio accreditation fraction of one maximum false summary.totals.max_accreditation_ratio Maximum MISO accreditation ratio over the current result scope.
count_of_units units count maximum false summary.totals.count_of_units Published MISO contributing-unit count over the current result scope.
source_record_count records count count source records true summary.totals.source_record_count Accreditation atom count over the current result 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
document_kind supported MISO accreditation PDFs 2 schedule53_class_average = Schedule 53 class-average ISAC/ICAP, dlol_indicative = Indicative DLOL UCAP/ICAP
class_family parsed MISO classes 12 fleetwide = fleetwide, hydro = hydro, nuclear = nuclear, other = other, solar = solar

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

Checked Examples

Agent question Request params Checked output
What preliminary Schedule 53 fleetwide summer ISAC/ICAP ratio did MISO publish for 2026-2027? {"document_kind": "schedule53_class_average", "include_records": true, "planning_year": "2026-2027", "resource_class": "Fleetwide Schedule 53", "season": "summer"} schedule53-fleetwide-summer.json
What indicative 2026-2027 DLOL storage ratios did MISO publish under Even Loss? {"document_kind": "dlol_indicative", "planning_year": "2026-2027", "resource_class": "Storage", "storage_variant": "Even Loss"} dlol-storage-even-loss.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.capacity_accreditation_miso.
  2. Call describe_power_capacity_accreditation_miso_v1 to inspect valid filters, groupings, metrics, and citation fields.
  3. Call query_power_capacity_accreditation_miso_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 ↗