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sea

Plan abi SEA (Sparse Evidence Attention) self-learning work — evidence-augmented completion, 8-signal scorer, EMA modulator persistence, and constitution audit. Use when working on ai_learn / complete --learn / evidence recall. Routes to sea-learn-loop, abi-superpower-sea, abi-superpower-constitution, and sea-learning-controller.

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donaldfilimon/abi19 stars(GitHub 19 + cccskills 0)

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SKILL.md (original)

Review the instructions the agent will receive before you install.

sea

Entry point for abi's SEA self-learning loop (crates/abi-sea/src/). Routes:

You want to…Use
Drive abi complete --learn end-to-endsea-learn-loop
Deep-dive SEA scoring / adaptive modulationabi-superpower-sea
Constitution audit (observability-only)abi-superpower-constitution
Run learning or inspect the REPL's session-only /sea preferencesea-learning-controller

Facts that constrain any SEA plan

  • SEA = evidence-augmented self-learning completion with an 8-signal scorer + budgeted greedy selection. It classifies 7 task types; 3 currently apply non-baseline signal-weight deltas and 4 retain the baseline weights.
  • AdaptiveModulator weights (EMA, alpha=0.3, key modulator:weights) persist in WDBX only on the --learn/SEA path. Plain complete re-runs sentiment each turn with no EMA persistence.
  • Constitution audit (6 principles) is observability-only, not a gate — sets audit_passed / audit_vetoed / escore, warns via std.log on violation, but complete / run still return the response. Safety+privacy hard-veto only when either < 0.5.
  • The live EMA path runs through abi-sea::run_learn_loop; there is no separate public adaptive-routing command.

Honest boundary

No accuracy / energy / learning-gain claims without a repo benchmark.

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