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ai-plan

Plan abi AI work — model routing, completion, SEA self-learning, and training. Use when the user asks to plan AI orchestration, choose a model, run a completion, drive the SEA learn loop, or schedule training. Routes to complete-base, sea-learn-loop, agent-plan-train, and the abi-superpower-ai/sea/constitution superpowers.

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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.

ai-plan

Entry point for abi's AI subsystem (crates/abi-ai/src/). Routes to the specialist skills instead of duplicating them:

You want to…Use
Smoke-test base local completion (abi complete)complete-base
Drive the SEA self-learning loop (abi complete --learn)sea-learn-loop
Plan + train an agent (abi agent plan / train)agent-plan-train
Deep-dive AI routing/constitution/SEAabi-superpower-ai, abi-superpower-sea, abi-superpower-constitution
Run SEA learning, or inspect the REPL's session-only preferencesea-learning-controller (abi complete --learn; /sea is metadata only)

Facts that constrain any AI plan (from source, not marketing)

  • Default model claude-fable-5; crates/abi-ai/src/models.rs is the single source of truth for ids/aliases/provider routing (mod/stub parity).
  • Router selectBestProfile ties resolve abbey > aviva > abi; neutral input routes to abi. analyzeSentiment is prefix-only keyword matching.
  • Constitution audit is observability-only, not a gate — sets audit_passed / audit_vetoed / escore; safety+privacy hard-veto only when either scores < 0.5. Matching is case-insensitive substring (infix), so "harm" fires on "harmless" — it cannot detect novel harm patterns.
  • EMA weights persist only on the --learn/SEA path; plain complete re-runs sentiment each turn with no EMA persistence.

Honest boundary

No energy-efficiency, accuracy, or QPS claims without a repo test/benchmark proving them (see docs/contracts/external-claims-audit.mdx).

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