gyst
Team knowledge layer for AI coding agents. Every session learns, every agent benefits.
Open source Open in the app JSON README (API)
About
Team knowledge layer for AI coding agents. Every session learns, every agent benefits.
Details
- Kind
- Plugins
- Topic
- No topic detected
- Publisher
- chaydavs
- Origin
- gemini
- Category
- ferramentas
- Version
- 0.1.40
- Stars
- 4
- Last push
- 2026-06-29T05:24:27Z
- Repository state
- ativo
- Language
- TypeScript
- License
- MIT
- Added
- 2026-08-30 14:13:39
- Updated
- 2026-08-30 14:13:39
- Origin id
chaydavs/gyst
README
# Gyst **Give your AI agent your team's memory. In 90 seconds.** ```bash npm install -g gyst-mcp && gyst init ``` --- ## The problem AI coding agents are fast — but stateless. Every session your agent starts fresh: no memory of why the auth service keeps timing out, no knowledge of the deploy-on-Fridays rule, no record of decisions your team made last month. Your agent figures things out and then forgets them. The team never gets smarter. --- ## The solution - **Self-populating context layer** — mined automatically from your git history, code comments, markdown docs, and session transcripts - **Every session starts ready** — your team's rules, conventions, and past decisions are injected before the first prompt - **Works with every major agent** — Claude Code, Cursor, Codex CLI, Windsurf, Gemini CLI --- ## 90-second quickstart ```bash npm install -g gyst-mcp && gyst init ``` **Example output:** ``` ┌─────────────────────────────────────────────────────┐ │ gyst init │ ├─────────────────────────────────────────────────────┤ │ ✓ Database initialized .gyst/wiki.db │ │ ✓ MCP server registered Claude Code │ │ ✓ MCP server registered Cursor │ │ ✓ Hooks installed post-commit │ │ ✓ Scanning codebase ... 42 files │ │ ✓ Loaded conventions 8 entries │ │ ✓ Loaded decisions 3 entries │ │ ✓ Ghost knowledge generated 5 entries │ ├─────────────────────────────────────────────────────┤ │ Restart your AI tool. Context will inject on the │ │ next session start. │ └─────────────────────────────────────────────────────┘ ``` Restart your AI tool. That's it. --- ## What your agent gets | Context type | What it is | Example | |---|---|---| | **Ghost Knowledge** | High-confidence facts about your codebase the agent must know | "Never deploy on Fridays — batch job runs at 22:00 UTC and will conflict" | | **Conventions** | Coding standards scoped to files and directories | "All API responses use the `ApiResponse<T>` envelope shape" | | **Decisions** | Architecture choices and the reasons behind them | "Switched from Prisma to raw SQL — N+1 queries were killing dashboard load time" | | **Error Patterns** | Known failure signatures with their fixes | "`SQLITE_BUSY` on parallel writes — use WAL mode + retry with backoff" | --- ## Supported agents | Agent | Auto-detected | Context injection | Hook coverage | |---|:---:|:---:|:---:| | Claude Code | ✓ | ✓ | 12 hooks | | Cursor | ✓ | ✓ | 4 hooks | | Codex CLI | ✓ | ✓ | 4 hooks | | Windsurf | ✓ | ✓ | 4 hooks | | Gemini CLI | ✓ | ✓ | 4 hooks | --- ## How it works **Mining:** `gyst init` scans your codebase and git history to build a context layer — zero config, zero manual writing. It extracts conventions from your source files, decisions from commit messages and ADRs, error patterns from `TODO`/`FIXME` comments, and structural knowledge from the files your team touches most. The post-commit hook keeps it current automatically after every commit. **Injection:** At every session start, Gyst injects your team's ghost knowledge and top conventions into the agent's context window. Subagents get the same injection. When a session ends, anything the agent learned gets distilled back into the context layer, so the next session starts even stronger. --- ## Learn more - [Technical reference](docs/ADVANCED.md) — MCP tool API, CLI flags, hook system, search pipeline, configuration - [3-minute demo script](docs/DEMO_SCRIPT.md) — step-by-step pitch walkthrough --- ## Dashboard ```bash gyst dashboard # opens at localhost:3579 ``` Browse all context entries, inspect the knowledge graph, review low-confidence entries, and track context economics (leverage ratio, zero-result rate, intent mix). --- ## Team mode ### Git-sync (zero infrastructure) The context layer lives in your repo. `git pull` syncs it automatically via the `post-merge` hook. ### Shared HTTP server ```bash # Admin — set up once gyst create team "Acme Engineering" GYST_API_KEY=gyst_admin_... gyst team invite gyst serve --http --port 3456 # Each developer — one command gyst join gyst_invite_abc123... "Alice" --server http://your-host:3456 ``` Every developer's AI tools automatically point at the shared context layer. Knowledge grows as the team grows. --- ## License MIT — see [LICENSE](LICENSE).