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modal-docs
Use when a task depends on current Modal Python APIs, migration guidance, deployed object lookup, or docs-backed runtime behavior.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Use when a task depends on current Modal Python APIs, migration guidance, deployed object lookup, or docs-backed runtime behavior.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when acting as the auto-AlphaFold3 autoresearch agent: read baseline metrics and Fold Cartographer diagnostics, choose one diagnostic target and one move family, propose or patch only the allowed AlphaFold3-lite model/training/sampler surface, and hand one trial to the orchestrator without touching Modal infrastructure or locked benchmark files.
Use when operating as a bounded auto-AlphaFold3 subagent worker that produces one proposal artifact for an assigned diagnostic target or move family, supports fast parallel hypothesis fanout, and never submits trials, calls Modal, edits locked files, appends ledgers, or integrates its own result.
Use when validating and submitting exactly one auto-AlphaFold3 AutoFoldTrial JSON through the approved local orchestrator command, rejecting direct Modal calls, locked benchmark paths, hidden-validation search, missing hypotheses, and multi-trial submissions.
Use when interpreting auto-AlphaFold3 scorer diagnostics into exactly one Fold Cartographer failure target, preserving best_val_calpha_lddt as the primary objective and mapping local geometry, long-range topology, distogram-vs-3D, or stability/compute evidence to safe move-family suggestions.
| name | modal-docs |
| description | Use when a task depends on current Modal Python APIs, migration guidance, deployed object lookup, or docs-backed runtime behavior. |
Use this skill when a task depends on current Modal APIs or when existing code may rely on stale pre-1.0 patterns. Open the smallest relevant doc set first instead of crawling the full corpus.
Use for image construction, dependency installation, and stale build-time patterns that now need image-based replacements.
Use for add_local_*, add_local_python_source, file staging, and Mount-to-image migrations.
Use for app wiring, deployed object discovery, and looking up functions or classes across apps.
Use for persisted files, cache state, Volume attachment semantics, and commit/reload behavior.
Use for endpoint decorators, request handling, and wiring deployed apps to HTTP entrypoints.
Use when snippets mention deprecated Modal APIs such as Mount, copy_local_*, older lifecycle hooks, or outdated lookup patterns.