Set up and operate abi through opencode — how opencode discovers abi skills, slash-commands, and MCP servers. Use when the user asks about opencode config, why an abi skill is not loading in opencode, or how to add a skill to the opencode allowlist.
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Build, launch, and drive the abi stable-Rust project — the `abi` CLI and the `abi-mcp` JSON-RPC server. Use when asked to run, start, build, smoke-test, or screenshot abi, drive its CLI subcommands, exercise the MCP server over stdio, or confirm a change works in the real binaries (not just the test suite).
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Show or reset abi agent context: report history, file mentions and session data (`/context` in abi agent tui), or clear history, file mentions and transient state (`/reset`).
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Local multi-agent orchestration superpower. Fixed trio, custom workers, browser planning — all scheduler-backed, no distributed agents, no embedded browser.
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AI completion and SEA learning guide. Maps completion, streaming, training, and learning requests to real ABI CLI paths.
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GPU and Metal backend superpower. Reports backend status, vector ops, hardware capabilities.
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ABI MCP JSON-RPC server skill for the frozen 12-tool stdio surface and custom loopback HTTP compatibility listener.
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SEA (Sparse Evidence Attention) learning superpower. Evidence-augmented completion with task-aware scoring and adaptive modulation.
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WDBX compute superpower. Cycle-free accelerator contracts, deterministic CPU SIMD fallback, scoped Metal execution, output-checked CoreML inference, and honest CUDA/Vulkan boundaries.
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WDBX secure/compression demos. Deterministic persisted PQ/autoencoder artifacts, additive/DGHV references, educational refresh, and optional pinned TFHE-rs execution with strict claim boundaries.
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Plan and execute ABI repo work from current TODOs, roadmap/spec docs, stable Rust 1.99.1 constraints, and validation gates. Use when user asks to find all ABI todos/roadmaps, compile ABI goals/specs, organize a large ABI implementation goal, or decide the next safe work slice in the abi repository.
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Execute ABI repo work from current TODOs, roadmap/spec docs, stable Rust 1.99.1 constraints, and validation gates. Use when user asks to find all ABI todos/roadmaps, compile ABI goals/specs, organize a large ABI implementation goal, or decide the next safe work slice in the abi repository.
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Use when a macOS user asks to free substantial storage, delete caches or duplicates, empty Trash, manage Time Machine snapshots, consolidate repositories, or reorganize files across the home directory.
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Run the propose-then-apply self-improvement loops in abi (`abi improve`) and abbey (`abbey learn improve`). Use when asked to "self-improve", "auto-improve", or preview/apply what abi or abbey would learn from recent activity. Both default to a dry run; applying is an explicit, gated step. Not a trainer, not LoRA, and not skill-loop.
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Build the abi CLI and report GPU / accelerator / shader / MLIR backend status and the compute-backend matrix (CPU/GPU/NPU/TPU detection + dynamic selection). Use when asked about backend capabilities, why a backend shows accelerated=false, or to capture a hardware/dispatch report.
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Build the abi CLI and drive the base completion path — `abi complete "<input>"` with no flags — routing to the local model, running the constitution audit, and optionally recording the completion in WDBX. Use to smoke-test the core local-completion path after touching crates/abi-ai or the model catalog. Fully local: no --live (remote) and no --learn (SEA).
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Show all build-time feature flags and their current state. Maps to `/features` slash command in abi agent tui.
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WDBX vector store operations superpower. Includes insert, query, stats, compaction, secure demos, and REST API.
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Drive ABI's loopback multimodal browser studio — camera/image/video frames, microphone PCM, client-side Web Speech STT/TTS, and deterministic local analysis via `abi agent browser --studio`. Use for vision, voice, image, video, getUserMedia, or browser-studio work. Not a neural vision/STT/TTS model.
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Donald Filimon's agent style for ABI and multi-CLI work: terse path-anchored status, claim-honest verification, cursor/ branches with draft PRs, skill-loop path hygiene, sync-clis discipline, mid-task skill routing, Cell/Browserbase orientation, and CoreAI skill lanes. Use for Donald, /donald-mode, or requests to work in this style.
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Build the abi CLI and run the miniature character-level neural-net demo — `nn train` (real manual-backprop char-LM) and `nn sample` (train-then-generate). Use to train, sample, or smoke-test the nn demo trainer, or verify nn after touching crates/abi-nn/. This is a demo trainer, NOT a production/LLM/distributed trainer.
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Build the abi CLI and exercise the OS-control policy in dry-run (planning) mode only, and verify the execute path refuses without --confirm. Use when working on OS-control handlers or the `abi agent os` handler, or to safely demo OS-command planning. Never executes a command.
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Create reviewed conventional Git commits through the agent workflow. This is not an `abi agent tui` slash command.
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Review Git diffs through the agent workflow. This is not an `abi agent tui` slash command.
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