refactor(agentic): generalize agentic predictors via DomainConfig#1
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Pin the behaviour the domain-agnostic refactor must preserve: - AdaptiveSkillStore save/load/render/backup contract and the confirmation_threshold store parameter (shared-lib test with a minimal concrete state). - WtiStrategyState.build_markdown() renders the committed wti-strategy-trained artifact byte-identically (snapshot), plus the default oil skill name/title. - The five strategy mutation tools' evidence governance: observation/ hypothesis lifecycle, the graduation threshold guard, and the narrative-update rationale requirement. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…ainConfig Promote the shared agentic engine so a new target series can be configured without touching oil code, and drive the oil prompts/config from a single `DomainConfig`. Pure refactor: no new features, no study driver. Promoted to aieng/forecasting/methods/agentic/: - strategy_state.py: generic `StrategyState` (+ Observation/Hypothesis/ CalibrationCorrection/VersionEntry). Markdown title, default skill name, and frontmatter description are ClassVar params. Oil `WtiStrategyState` becomes a thin subclass pinning the WTI strings — committed SKILL.md renders identically. - adaptive_skill_tools.py: `build_skill_tools(strategy_dir, state_type, ...)` generic over any StrategyState subclass. No import-time singletons. Oil skill_tools.py delegates and re-exports the sub-models; STORE/WTI_SKILL_TOOLS removed (unused outside docstrings). - history.py: `compress_history` (was analyst_agent/agent.py); oil re-exports it. - outputs.py: generic `ScenarioCard` / `ScenarioAgentForecastOutput` with the scenario-card numeric fields parameterized via `scenario_card_template_extra`. Oil `tasks.py` subclasses them, preserving `wti_range_60d`/`point_estimate_60d` and modality="discrete". - domain.py: `DomainConfig` (identity, data/target, context-retrieval, strategy skill, skill dirs, vol-regime bands, tool bounds) plus render_* instruction templates and `build_analyst_config` / `build_adaptive_config`. Oil implementation: - energy_oil_forecasting/domain.py defines `OIL_DOMAIN`. - analyst/adaptive/starter agent instructions now render from OIL_DOMAIN; the `build_wti_*` factories are thin delegating wrappers. Rendered oil prompts are byte-identical to the originals (verified against captured goldens). Curriculum: `_vol_regime` vol bands extracted to a `bands` parameter with the 15/30/50 thresholds as `DEFAULT_VOL_REGIME_BANDS`. Invariants held: oil agent.name / predictor_id strings unchanged; committed skill artifacts render identically; nb05/nb06 import surfaces resolve. Regenerated the concierge catalog/artifacts to index the new modules. __init__ re-exports the promoted names; old oil import paths preserved. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
New PYSEC-2026 advisories against the locked versions fail CI's pip-audit step on every branch (main last passed 2026-07-07, before publication). Full test suite re-verified after the bump: 489 passed, 7 skipped. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Fork-side landing of upstream PR VectorInstitute#170 (CI-green there; full description and invariant verification in that PR). This fork is the home of the workshop-paper + live-evaluation work; the generalization merges here first and is promoted upstream after the bootcamp build phase.
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