Production patterns for optimizing Bazel builds in large-scale monorepos.
Works with
Covers WORKSPACE configuration, .bazelrc tuning, remote caching/execution setup, and platform-specific build constraints
Includes templates for TypeScript and Python libraries, custom Docker rules, and dependency analysis via Bazel query
Provides performance profiling techniques, memory optimization strategies, and best practices for fine-grained targets and visibility enforcement
Addresses monorepo patterns
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbazel-build-optimizationExecute the skills CLI command in your project's root directory to begin installation:
Fetches bazel-build-optimization from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate bazel-build-optimization. Access via /bazel-build-optimization in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Production patterns for Bazel in large-scale monorepos.
workspace/
├── WORKSPACE.bazel # External dependencies
├── .bazelrc # Build configurations
├── .bazelversion # Bazel version
├── BUILD.bazel # Root build file
├── apps/
│ └── web/
│ └── BUILD.bazel
├── libs/
│ └── utils/
│ └── BUILD.bazel
└── tools/
└── bazel/
└── rules/
| Concept | Description |
|---|---|
| Target | Buildable unit (library, binary, test) |
| Package | Directory with BUILD file |
| Label | Target identifier //path/to:target |
| Rule | Defines how to build a target |
| Aspect | Cross-cutting build behavior |
# WORKSPACE.bazel
workspace(name = "myproject")
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
# Rules for JavaScript/TypeScript
http_archive(
name = "aspect_rules_js",
sha256 = "...",
strip_prefix = "rules_js-1.34.0",
url = "https://github.com/aspect-build/rules_js/releases/download/v1.34.0/rules_js-v1.34.0.tar.gz",
)
load("@aspect_rules_js//js:repositories.bzl", "rules_js_dependencies")
rules_js_dependencies()
load("@rules_nodejs//nodejs:repositories.bzl", "nodejs_register_toolchains")
nodejs_register_toolchains(
name = "nodejs",
node_version = "20.9.0",
)
load("@aspect_rules_js//npm:repositories.bzl", "npm_translate_lock")
npm_translate_lock(
name = "npm",
pnpm_lock = "//:pnpm-lock.yaml",
verify_node_modules_ignored = "//:.bazelignore",
)
load("@npm//:repositories.bzl", "npm_repositories")
npm_repositories()
# Rules for Python
http_archive(
name = "rules_python",
sha256 = "...",
strip_prefix = "rules_python-0.27.0",
url = "https://github.com/bazelbuild/rules_python/releases/download/0.27.0/rules_python-0.27.0.tar.gz",
)
load("@rules_python//python:repositories.bzl", "py_repositories")
py_repositories()
# .bazelrc
# Build settings
build --enable_platform_specific_config
build --incompatible_enable_cc_toolchain_resolution
build --experimental_strict_conflict_checks
# Performance
build --jobs=auto
build --local_cpu_resources=HOST_CPUS*.75
build --local_ram_resources=HOST_RAM*.75
# Caching
build --disk_cache=~/.cache/bazel-disk
build --repository_cache=~/.cache/bazel-repo
# Remote caching (optional)
build:remote-cache --remote_cache=grpcs://cache.example.com
build:remote-cache --remote_upload_local_results=true
build:remote-cache --remote_timeout=3600
# Remote execution (optional)
build:remote-exec --remote_executor=grpcs://remote.example.com
build:remote-exec --remote_instance_name=projects/myproject/instances/default
build:remote-exec --jobs=500
# Platform configurations
build:linux --platforms=//platforms:linux_x86_64
build:macos --platforms=//platforms:macos_arm64
# CI configuration
build:ci --config=remote-cache
build:ci --build_metadata=ROLE=CI
build:ci --bes_results_url=https://results.example.com/invocation/
build:ci --bes_backend=grpcs://bes.example.com
# Test settings
test --test_output=errors
test --test_summary=detailed
# Coverage
coverage --combined_report=lcov
coverage --instrumentation_filter="//..."
# Convenience aliases
build:opt --compilation_mode=opt
build:dbg --compilation_mode=dbg
# Import user settings
try-import %workspace%/user.bazelrc
# libs/utils/BUILD.bazel
load("@aspect_rules_ts//ts:defs.bzl", "ts_project")
load("@aspect_rules_js//js:defs.bzl", "js_library")
load("@npm//:defs.bzl", "npm_link_all_packages")
npm_link_all_packages(name = "node_modules")
ts_project(
name = "utils_ts",
srcs = glob(["src/**/*.ts"]),
declaration = True,
source_map = True,
tsconfig = "//:tsconfig.json",
deps = [
":node_modules/@types/node",
],
)
js_library(
name = "utils",
srcs = [":utils_ts"],
visibility = ["//visibility:public"],
)
# Tests
load("@aspect_rules_jest//jest:defs.bzl", "jest_test")
jest_test(
name = "utils_test",
config = "//:jest.config.js",
data = [
":utils",
"//:node_modules/jest",
],
node_modules = "//:node_modules",
)
# libs/ml/BUILD.bazel
load("@rules_python//python:defs.bzl", "py_library", "py_test", "py_binary")
load("@pip//:requirements.bzl", "requirement")
py_library(
name = "ml",
srcs = glob(["src/**/*.py"]),
deps = [
requirement("numpy"),
requirement("pandas"),
requirement("scikit-learn"),
"//libs/utils:utils_py",
],
visibility = ["//visibility:public"],
)
py_test(
name = "ml_test",
srcs = glob(["tests/**/*.py"]),
deps = [
":ml",
requirement("pytest"),
],
size = "medium",
timeout = "moderate",
)
py_binary(
name = "train",
srcs = ["train.py"],
deps = [":ml"],
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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bazel-build-optimization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend bazel-build-optimization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: bazel-build-optimization is the kind of skill you can hand to a new teammate without a long onboarding doc.
bazel-build-optimization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: bazel-build-optimization is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in bazel-build-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in bazel-build-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
bazel-build-optimization has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: bazel-build-optimization is focused, and the summary matches what you get after install.
bazel-build-optimization has been reliable in day-to-day use. Documentation quality is above average for community skills.
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