extract
免费Builds the gauntlet knowledge base from AST extraction and AI enrichment. Use when initializing or refreshing codebase knowledge for challenges.
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编码规范、框架、重构、代码审查(1.7万 个)
Builds the gauntlet knowledge base from AST extraction and AI enrichment. Use when initializing or refreshing codebase knowledge for challenges.
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Generates a Mermaid class diagram showing types, inheritance, and composition. Use when visualizing class hierarchies or documenting a module public API.
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Traces execution paths through the code graph with criticality scoring and Mermaid charts. Use when understanding how a function propagates through the system.
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Guide minimal code via a decision ladder with full safety, edge, and negative-case coverage. Use when adding code, choosing a dependency, or auditing a diff.
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Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
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Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.
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Delegates tasks to OpenCode (opencode run) via delegation-core. Use when delegation-core selects OpenCode or a provider-agnostic harness is wanted.
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Generates a Mermaid dependency graph showing import relationships between modules. Use when analyzing coupling, finding circular deps, or planning refactors.
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Detects architectural clusters and coupling boundaries via community detection on the code graph. Use when identifying module groupings or refactoring targets.
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Adds developer-authored annotations to the gauntlet knowledge base. Use when capturing tribal knowledge or rationale not visible in code.
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Applies KISS, YAGNI, and SOLID principles for clean code with reduced complexity. Use when refactoring or reviewing code for over-engineering.
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Guide creating Claude Code skills with TDD and persuasion principles. Use for new skill development.
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Chronicles settled battles, reverts, and dead ends. Use when a fix echoes a past failure. Do not use for live triage; use night-market-debugging-playbook.
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Sweep plugins, skills, agents, commands, and hooks after a model release or Claude Code version bump. Use when upstream ships. Do not use for routine edits; use night-market-change-control.
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Classify, gate, and review changes. Use when landing a PR, releasing, or amending rules. Do not use for failure triage; use night-market-debugging-playbook.
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Rebuild the dev environment: uv, Python tiers, pins, traps. Use when onboarding or toolchain breaks. Do not use for daily commands; use night-market-operations.
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Triage night-market failures by symptom (hooks, CI, tests). Use when a check fails unexpectedly. Do not use for routine gates; use night-market-operations.
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Explain plugin, skill, command, agent, and hook mechanics used here. Use when authoring or debugging plugins. Do not use for ops; use night-market-operations.
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Foolbox operating guidance for wrapping vision models, running adversarial attacks, measuring clean and robust accuracy, handling NumPy/PyTorch/TensorFlow/JAX backends, and loading Foolbox-compatible model-zoo repositories.
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Use face_recognition to detect faces, extract landmarks and encodings, compare identities, run the face_recognition and face_detection CLIs, and troubleshoot dlib/model installation.
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Operate the legacy Frustum PointNets code release for KITTI or SUN RGB-D data preparation, TensorFlow runtime setup, training, inference, and 3D detection evaluation.
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Guide Django REST Framework and GeoDjango projects through django-rest-framework-gis installation, GeoJSON serialization, spatial filtering, pagination, OpenAPI schema generation, and backend troubleshooting.
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Use Dexbotic to prepare DexData, train and serve vision-language-action policies, evaluate checkpoints, and integrate explicitly external RL or robot backends.
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Guide the official Elasticsearch Python client for cluster connections, generated APIs, async code, bulk ingestion, query DSL, ES|QL, optional integrations, and runtime troubleshooting.
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