GitHub organization
Agent skills by atopile
- skills
- 19
- repository
- 1
Repositories by atopile
Skills by atopile, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Reference for the .ato declarative DSL: type system, connection semantics, constraint model, and standard library. | atopile/ | 4k | — | ~3.5k | Automated safety check: Pass | MIT | 3 mo ago |
| 2 | 2.Compiler How the atopile compiler builds and links TypeGraphs from .ato (ANTLR front-end → AST → TypeGraph → Linker → DeferredExecutor), plus the key invariants and test entrypoints. | atopile/ | 4k | — | ~1k | Automated safety check: Pass | MIT | 3 mo ago |
| 3 | Instructions for electronics-specific logic and build processes: netlists, PCBs, build steps, and exporters. | atopile/ | 4k | — | ~791 | Automated safety check: Pass | MIT | 3 mo ago |
| 4 | 4.Fabll How FabLL (faebryk.core.node) maps Python node/trait declarations into the TypeGraph + instance graph, including field/trait invariants and instantiation patterns. | atopile/ | 4k | — | ~1.1k | Automated safety check: Pass | MIT | 3 mo ago |
| 5 | 5.Faebryk How Faebryk's TypeGraph works (GraphView + Zig edges), how to traverse/resolve references, and how FabLL types/traits map onto edge types. | atopile/ | 4k | — | ~861 | Automated safety check: Pass | MIT | 3 mo ago |
| 6 | 6.Graph How the Zig-backed instance graph works (GraphView/NodeReference/EdgeReference), the real Python API surface, and the invariants around allocation, attributes, and cleanup. | atopile/ | 4k | — | ~952 | Automated safety check: Pass | MIT | 3 mo ago |
| 7 | 7.Library How the Faebryk component library is structured, how F.py is generated, and the conventions/invariants for adding new library modules. | atopile/ | 4k | — | ~714 | Automated safety check: Pass | MIT | 3 mo ago |
| 8 | 8.Pyzig How the Zig↔Python binding layer works (pyzig), including build-on-import, wrapper generation patterns, ownership rules, and where to add new exported APIs. | atopile/ | 4k | — | ~1k | Automated safety check: Pass | MIT | 3 mo ago |
| 9 | 9.Sexp How the Zig S-expression engine and typed KiCad models work, how they are exposed to Python (pyzigsexp), and the invariants around parsing, formatting, and freeing. | atopile/ | 4k | — | ~1k | Automated safety check: Pass | MIT | 3 mo ago |
| 10 | 10.Solver How the Faebryk parameter solver works (Sets/Literals, Parameters, Expressions), the core invariants enforced during mutation, and practical workflows for debugging and extending the solver. | atopile/ | 4k | — | ~2.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 11 | 11.Agent Core runtime behavior for the atopile sidebar agent: identity, persistence model, execution rules, and tool recipes. | atopile/ | 4k | — | ~4.2k | Automated safety check: Pass | MIT | 3 mo ago |
| 12 | Generate short live progress summaries for the atopile agent from recent tool events, preambles, checklist changes, and build state. | atopile/ | 4k | — | ~821 | Automated safety check: Pass | MIT | 3 mo ago |
| 13 | 13.Code Review LLM-focused code review process for this repo: what to check, how to ground feedback in invariants/tests, and how to verify changes efficiently (including test-report.json). | atopile/ | 4k | — | ~1.9k | Automated safety check: Pass | MIT | 3 mo ago |
| 14 | 14.Dev LLM-focused workflow for working in this repo: compile Zig, run the orchestrated test runner, consume test-report.json/html artifacts, and discover/debug ConfigFlags. | atopile/ | 4k | — | ~1.6k | Automated safety check: Pass | MIT | 3 mo ago |
| 15 | 15.Frontend Frontend standards for atopile extension webviews: architecture, contracts, design system, and testing workflow. | atopile/ | 4k | — | ~3.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 16 | 16.Lsp How the atopile Language Server works (pygls), how it builds per-document graphs for completion/hover/defs, and the invariants for keeping it fast and crash-proof. | atopile/ | 4k | — | ~594 | Automated safety check: Pass | MIT | 3 mo ago |
| 17 | 17.Planning Spec-driven planning for complex design tasks: when to plan, how to write specs as .ato files, and how to verify against requirements. | atopile/ | 4k | — | ~4k | Automated safety check: Pass | MIT | 3 mo ago |
| 18 | 18.Ato Authoritative ato authoring and review skill: language reference, stdlib, design patterns, and end-to-end board design workflow. | atopile/ | 4k | — | ~12k | Automated safety check: Pass | MIT | 3 mo ago |
| 19 | How to write and maintain .claude/skills//SKILL.md files: source-of-truth-first process, verification steps, and conventions. | atopile/ | 4k | — | ~893 | Automated safety check: Pass | MIT | 3 mo ago |
Questions, answered from the data.
What is the best skill by atopile?
Ato Language from atopile/atopile ranks first of the 19 skills by atopile listed here, with the highest score: its repository has 4k GitHub stars, its SKILL.md loads about 3.5k tokens and it passes the automated safety check with no findings. Next come Compiler and Domain Layer.
Are atopile's skills official?
None yet. All 19 skills by atopile listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.