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sea-learn-loop

Build the abi CLI and exercise the SEA (Sparse Evidence Attention) self-learning completion path via `abi complete --learn`. Use when working on ai_learn / complete --learn / evidence recall, or to verify the SEA loop runs and persists. SEA is always linked in the Rust workspace; --sea is a compatibility no-op.

日本語の概要は準備中です。原文の説明を表示しています。

donaldfilimon/abiスター 19(GitHub 19 + cccskills 0)

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含まれるファイル(2)

  • SKILL.md3.6 KB
  • learn.sh2.8 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

sea-learn-loop — exercise the SEA self-learning completion

Driver: .agents/skills/sea-learn-loop/learn.sh (paths relative to repo root). CLI check — evidence is the RESULT: line and both passes' metadata lines.

SEA is always available in the Rust workspace. The default run exercises the real SEA path. The first pass starts with no evidence; the second must recall the first pass's persisted record after reopening the scratch store. Both must report successful persistence and adaptation. --sea is accepted for compatibility and does not change the build path.

Prerequisites

  • Pinned stable Rust 1.99.1 via ./tools/cargo.sh (never bare Homebrew cargo).

Run (agent path)

.agents/skills/sea-learn-loop/learn.sh                       # default SEA-on path
.agents/skills/sea-learn-loop/learn.sh "my custom prompt"    # custom input
.agents/skills/sea-learn-loop/learn.sh --sea                 # accepted; no-op on build path

It builds the locked CLI into the same target directory it executes, creates a unique scratch store under target/skill-scratch/ (never the live ~/.abi/), overrides inherited persistence settings and runs abi complete --learn -- "<input>" in two separate processes. It requires learn=true, local generation provenance, persisted=true, adapted=true, and nonzero second-pass evidence_count on the metadata line, not inside the generated response. Its own scratch directory is removed on exit; other runs' stores are untouched. Prints RESULT: PASS — SEA learning persisted, adapted and recalled across processes. (exit 0) or RESULT: FAIL (nonzero). Audit-vetoed prompts intentionally fail this acceptance smoke because they must not learn.

Gotchas

  • First-pass evidence_count=0 is expected in a new scratch store, but a zero second-pass count fails the cross-process recall check.
  • The requested-model line shows the catalog default (claude-fable-5) while provider=local and generation_engine=persona-template establish that --learn is not a live API call; no credentials are needed.
  • Every metadata field rides that one first line, including learn=true evidence_count=N adapted=B self_learn_cycle=... recall_ready=.... self_learn_cycle reports what actually happened (persistence+adaptation+recall only when the learning write committed, adaptation-only when it was skipped or disabled, adaptation-only+write-unknown when the outcome is unknown) — never a completed cycle that the adjacent persisted= and wdbx_status= fields contradict. Do not move the learn fields onto their own line: the smoke reads only the first line, which is the boundary that stops markers repeated in generated response text from satisfying a persistence check.
  • First build may compile the workspace; later ./tools/cargo.sh build -p abi-cli runs are incremental.
  • --learn is local persona-template learning, not live-provider or bridge inference. Combining it with --live or a local-bridge model is rejected; this does not train language-model weights.

Troubleshooting

SymptomFix
build FAIL./tools/cargo.sh build -p abi-cli, then ./tools/check.sh.
missing learn=truecomplete grammar drifted — check crates/abi-cli complete handler + --learn.

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