Bazel Build Optimization

Bazel Build Optimization

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/bazel-build-optimization from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Bazel Build Optimization Production patterns for Bazel in large-scale monorepos.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Templates, Performance Optimization, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• The task is unrelated to bazel build optimization
• You need a different domain or tool outside this scope
• Setting up Bazel for monorepos
• Configuring remote caching/execution
• Optimizing build times
• Writing custom Bazel rules

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
6. Read the overview and provenance files before loading any copied upstream support files.
7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Imported: 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

Examples

Example 1: Ask for the upstream workflow directly

Use @bazel-build-optimization to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @bazel-build-optimization against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @bazel-build-optimization for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @bazel-build-optimization using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Use fine-grained targets - Better caching
• Pin dependencies - Reproducible builds
• Enable remote caching - Share build artifacts
• Use visibility wisely - Enforce architecture
• Write BUILD files per directory - Standard convention
• Don't use glob for deps - Explicit is better
• Don't commit bazel- dirs* - Add to .gitignore

Imported Operating Notes

Imported: Best Practices

Do's

• Use fine-grained targets - Better caching
• Pin dependencies - Reproducible builds
• Enable remote caching - Share build artifacts
• Use visibility wisely - Enforce architecture
• Write BUILD files per directory - Standard convention

Don'ts

• Don't use glob for deps - Explicit is better
• Don't commit bazel- dirs* - Add to .gitignore
• Don't skip WORKSPACE setup - Foundation of build
• Don't ignore build warnings - Technical debt

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/bazel-build-optimization, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Resources

• Bazel Documentation
• Bazel Remote Execution
• rules_js

Imported: 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"],
    data = ["//data:training_data"],
)

Template 5: Custom Rule for Docker

# tools/bazel/rules/docker.bzl
def _docker_image_impl(ctx):
    dockerfile = ctx.file.dockerfile
    base_image = ctx.attr.base_image
    layers = ctx.files.layers

    # Build the image
    output = ctx.actions.declare_file(ctx.attr.name + ".tar")

    args = ctx.actions.args()
    args.add("--dockerfile", dockerfile)
    args.add("--output", output)
    args.add("--base", base_image)
    args.add_all("--layer", layers)

    ctx.actions.run(
        inputs = [dockerfile] + layers,
        outputs = [output],
        executable = ctx.executable._builder,
        arguments = [args],
        mnemonic = "DockerBuild",
        progress_message = "Building Docker image %s" % ctx.label,
    )

    return [DefaultInfo(files = depset([output]))]

docker_image = rule(
    implementation = _docker_image_impl,
    attrs = {
        "dockerfile": attr.label(
            allow_single_file = [".dockerfile", "Dockerfile"],
            mandatory = True,
        ),
        "base_image": attr.string(mandatory = True),
        "layers": attr.label_list(allow_files = True),
        "_builder": attr.label(
            default = "//tools/docker:builder",
            executable = True,
            cfg = "exec",
        ),
    },
)

Template 6: Query and Dependency Analysis

# Find all dependencies of a target
bazel query "deps(//apps/web:web)"

# Find reverse dependencies (what depends on this)
bazel query "rdeps(//..., //libs/utils:utils)"

# Find all targets in a package
bazel query "//libs/..."

# Find changed targets since commit
bazel query "rdeps(//..., set($(git diff --name-only HEAD~1 | sed 's/.*/"&"/' | tr '\n' ' ')))"

# Generate dependency graph
bazel query "deps(//apps/web:web)" --output=graph | dot -Tpng > deps.png

# Find all test targets
bazel query "kind('.*_test', //...)"

# Find targets with specific tag
bazel query "attr(tags, 'integration', //...)"

# Compute build graph size
bazel query "deps(//...)" --output=package | wc -l

Template 7: Remote Execution Setup

# platforms/BUILD.bazel
platform(
    name = "linux_x86_64",
    constraint_values = [
        "@platforms//os:linux",
        "@platforms//cpu:x86_64",
    ],
    exec_properties = {
        "container-image": "docker://gcr.io/myproject/bazel-worker:latest",
        "OSFamily": "Linux",
    },
)

platform(
    name = "remote_linux",
    parents = [":linux_x86_64"],
    exec_properties = {
        "Pool": "default",
        "dockerNetwork": "standard",
    },
)

# toolchains/BUILD.bazel
toolchain(
    name = "cc_toolchain_linux",
    exec_compatible_with = [
        "@platforms//os:linux",
        "@platforms//cpu:x86_64",
    ],
    target_compatible_with = [
        "@platforms//os:linux",
        "@platforms//cpu:x86_64",
    ],
    toolchain = "@remotejdk11_linux//:jdk",
    toolchain_type = "@bazel_tools//tools/jdk:runtime_toolchain_type",
)

Imported: Performance Optimization

# Profile build
bazel build //... --profile=profile.json
bazel analyze-profile profile.json

# Identify slow actions
bazel build //... --execution_log_json_file=exec_log.json

# Memory profiling
bazel build //... --memory_profile=memory.json

# Skip analysis cache
bazel build //... --notrack_incremental_state

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.