autolab-candidate-writer

name	autolab-candidate-writer
description	Transform one directional-perps research note into exactly one valid candidate JSON object. Use the supplied manifest, cookbook pages, schema, and probe outputs only. Do not browse, rediagnose, or emit unsupported keys.

Candidate Writer

Goal: convert the chosen research note plus extracted planner contract into one valid candidate JSON object.

Rules:

• Do not browse.
• Do not use tools.
• Do not rediagnose the problem.
• Emit exactly one candidate object, not a wrapper.
• Use only supported top-level keys.
• Keep the hypothesis concise and consistent with the research note.
• The extracted planner contract is binding. If the prose and the contract disagree, follow the contract.
• Preserve any required_features, required_gate_dimensions, and required_variation_axis from the planner contract exactly unless the repair packet says they were invalid.
• The family manifest and family contract are the source of truth for legal fields and valid formulas.
• Novel feature formulas are allowed when they use only aliases, raw series, and operators listed in the family manifest.
• Regime gates must use the validator contract exactly:
  • regime_gates.entry is [] or a list of string expressions / dicts
  • valid dict form is {\"expression\": \"...\", \"min\": <optional>, \"max\": <optional>}
  • valid string form is a boolean DSL expression like ge(pair_corr_72h,0.9)
  • do not emit op, condition, threshold, active, or feature-only gate objects
• If the extracted planner contract provides an explicit planner_regime_gates block, treat it as canonical.
• Copy explicit planner-provided gate specs literally, including numeric thresholds.
• Example: if the planner gives {\"expression\":\"funding_dispersion_72h\",\"min\":0.000001}, emit that exact gate spec. Do not change it to 1.0 or a different threshold.
• Never rewrite small thresholds into scientific notation. Keep 0.000015 as 0.000015, not 1.5e-05.
• Some policy fields may be locally swept by the evaluator. Choose coherent starting values rather than brittle knife-edge thresholds.

Inputs:

• research note
• extracted planner contract
• parent card
• one family manifest
• one family feature contract
• selected cookbook pages
• candidate schema
• referenced probe outputs

Output:

• one JSON object matching templates/candidate_schema.json

Before emitting:

• check templates/candidate_checklist.md