77 lines
4.9 KiB
Markdown
77 lines
4.9 KiB
Markdown
# Decisions log
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Record *why* things are the way they are. Future-you will thank present-you.
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---
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## 2026-04-08 — AGENTS.md as cross-tool standard, not CLAUDE.md
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**Context**: Multiple tools (Crush, Pi, Antigravity) read `AGENTS.md` natively. Claude Code reads `CLAUDE.md`. Building on `CLAUDE.md` as the primary format locks into one vendor.
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**Decision**: Canonical source is `.context/AGENT.md` (root) and `.context/PROJECT.md` (per-project). The adapter script generates both `AGENTS.md` and `CLAUDE.md` — identical content, two filenames. Crush, Pi, and Antigravity read `AGENTS.md`; Claude Code reads `CLAUDE.md`.
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**Consequences**: One canonical file serves five+ tools. Adding a new tool that reads `AGENTS.md` requires zero adapter work.
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## 2026-04-08 — Agent Skills standard (SKILL.md in folders) over flat markdown
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**Context**: Claude Code, Pi, Crush, and Antigravity all support the Agent Skills open standard: a folder containing `SKILL.md` with frontmatter (`name`, `description`). Skills are discovered on-demand — only the description enters context, full instructions load when triggered.
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**Decision**: Skills live in `.skills/{name}/SKILL.md` at project level. This replaces the earlier `.context/skills/{name}.md` flat-file approach.
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**Consequences**: Skills are cross-compatible without adaptation. Pi auto-discovers them from `.pi/skills/` (symlink). Crush reads them natively. Progressive disclosure keeps context window lean.
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## 2026-04-08 — Go + HTMX as default stack
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**Context**: Need a default that's fast to prototype, easy to deploy as a single binary, and doesn't require a Node/npm toolchain for the UI layer.
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**Decision**: Go with HTMX + Templ for server-rendered UI. Python as fallback for ML/data tasks. TypeScript only when a project genuinely needs a rich client-side SPA.
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**Consequences**: Simpler deployment and dependency management. Agents need Go-specific skills.
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## 2026-04-08 — Task over Make
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**Context**: Makefiles have arcane syntax and poor cross-platform support.
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**Decision**: Use Taskfile (taskfile.dev) — YAML-based, cross-platform, supports task dependencies.
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**Consequences**: One extra binary to install. All project automation in `Taskfile.yml`.
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## 2026-04-08 — Qdrant over ChromaDB for vector store
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**Context**: Need collection-level isolation for client separation, payload filtering, runs well in k3s.
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**Decision**: Qdrant. Native collection isolation, rich filtering, mature gRPC API.
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**Consequences**: More operational complexity than Chroma, but isolation is non-negotiable for client work.
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## 2026-04-22 — Hyperguild scope reset: drop parametric learning, simplify brain
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**Context**: After shipping Phases 1–4 (MCP server, 6 skills, model orchestration, session logging, CD pipeline), we critically reviewed what was theater vs genuinely useful.
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**Decisions**:
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1. **Drop the parametric learning pipeline.** SFT/DPO/RL extraction, `brain/training-data/` directory structure, Axolotl/LLaMA-Factory fine-tuning loop — all cut. The loop requires thousands of high-quality examples to move the needle, which a solo consultant won't generate. Better base models ship faster than any fine-tuning effort could keep up with. This is a research project, not a productivity tool.
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2. **Simplify the brain to plain markdown.** `brain/knowledge/` replaces `brain/wiki/ + brain/raw/ + brain/training-data/`. The trainer and retrospective workers write markdown entries. `brain_query` searches markdown. No ingestion pipeline, no tagging for significance review, no structured JSONL formats.
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3. **Measure the escalation chain before assuming it's useful.** Local model (phi4) only belongs in a skill's chain if it passes Claude verification at a meaningful rate. Where it fails >70% of the time, it adds cost not value. Per-skill hit rate logging is the prerequisite to honest chain configuration.
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4. **Keep what's real**: MCP tool surface, session logging with attempt records, tier detection, CD pipeline, bridge to Claude Code.
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**What to build next** (in priority order):
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- `brain_query` injection into skill handlers before spawning workers — this makes the declarative brain actually function
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- `protocols.md` — behavioral contract injected into every worker prompt
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- Per-skill pass rate logging and chain tuning
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**Consequences**: Simpler system with a shorter feedback loop. The brain becomes real only when skill handlers query it. Training data ambitions deferred indefinitely — revisit if local model capabilities improve enough that fine-tuning becomes worthwhile.
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---
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## 2026-04-08 — Mistral Vibe gets its own adapter
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**Context**: Vibe doesn't read `AGENTS.md` — it uses `~/.vibe/prompts/` and `~/.vibe/agents/` with TOML config.
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**Decision**: The root context-sync generates a `mathias.md` prompt and `mathias.toml` agent config in `~/.vibe/`. This is the one tool that needs a custom adapter path.
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**Consequences**: Run `vibe --agent mathias` to use your conventions. Other Vibe users on the machine aren't affected.
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