bazel-build-optimization

wshobson/agents · updated Apr 8, 2026

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$npx skills add https://github.com/wshobson/agents --skill bazel-build-optimization
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summary

Production patterns for optimizing Bazel builds in large-scale monorepos.

  • 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
skill.md

Bazel Build Optimization

Production patterns for Bazel in large-scale monorepos.

When to Use This Skill

  • Setting up Bazel for monorepos
  • Configuring remote caching/execution
  • Optimizing build times
  • Writing custom Bazel rules
  • Debugging build issues
  • Migrating to Bazel

Core Concepts

1. Bazel Architecture

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/

2. Key Concepts

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

Templates

Template 1: WORKSPACE Configuration

# 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()

Template 2: .bazelrc Configuration

# .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

Template 3: TypeScript Library BUILD

# 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",
)

Template 4: Python Library BUILD

# 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"],
how to use bazel-build-optimization

How to use bazel-build-optimization on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add bazel-build-optimization
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/wshobson/agents --skill bazel-build-optimization

The skills CLI fetches bazel-build-optimization from GitHub repository wshobson/agents and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/bazel-build-optimization

Reload or restart Cursor to activate bazel-build-optimization. Access the skill through slash commands (e.g., /bazel-build-optimization) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ 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.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.825 reviews
  • Rahul Santra· Nov 23, 2024

    bazel-build-optimization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Piyush G· Nov 15, 2024

    I recommend bazel-build-optimization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Amelia Tandon· Nov 7, 2024

    Keeps context tight: bazel-build-optimization is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Daniel Brown· Oct 26, 2024

    bazel-build-optimization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Oct 14, 2024

    Keeps context tight: bazel-build-optimization is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Amina Abbas· Oct 14, 2024

    Useful defaults in bazel-build-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Shikha Mishra· Oct 6, 2024

    Useful defaults in bazel-build-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yash Thakker· Sep 25, 2024

    bazel-build-optimization has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aanya Chawla· Sep 9, 2024

    Solid pick for teams standardizing on skills: bazel-build-optimization is focused, and the summary matches what you get after install.

  • Amina Ramirez· Sep 5, 2024

    bazel-build-optimization has been reliable in day-to-day use. Documentation quality is above average for community skills.

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