Workflow tool for compiling Zig and running orchestrated tests with reporting.
Install
mkdir -p .claude/skills/dev && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2333" && unzip -o skill.zip -d .claude/skills/dev && rm skill.zipInstalls to .claude/skills/dev
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
LLM-focused workflow for working in this repo: compile Zig, run the orchestrated test runner, consume test-report.json/html artifacts, and discover/debug ConfigFlags.Key capabilities
- →Orchestrated Zig compilation triggering
- →Parsing of automated test artifacts
- →Generation of test comparison baselines
- →Inventory of configuration flags
- →GitHub Actions artifact integration
How it works
It wraps core build and test CLI operations into an interface that specifically parses generated JSON reports for LLM analysis.
Inputs & outputs
When to use dev
- →Compile Zig bindings
- →Run orchestrated tests
- →View test report artifacts
- →Discover and set configuration flags
About this skill
Dev Module
This skill is written for LLMs working inside this repo. It focuses on the fastest, most reliable inner loop:
- rebuild Zig bindings when needed
- run the repo’s orchestrated test runner (
ato dev test --llm, not raw test output) - use the generated test reports (
artifacts/test-report.json,artifacts/test-report.html,artifacts/test-report.llm.json) - discover and use
ConfigFlags correctly (and inventory them repo-wide)
Quick Start
source .venv/bin/activate
ato dev compile
ato dev test --llm -k solver
ato dev test --llm --view HEAD --open
ato dev test --reuse --baseline HEAD~1
ato dev flags
Relevant Files
- CLI commands:
src/atopile/cli/dev.pyato dev compile(triggers Zig build viaimport faebryk.core.zig)ato dev test --llm(runstest/runner/main.pywith args; supports baseline/CI report helpers)
- Zig build-on-import glue:
src/faebryk/core/zig/__init__.py(ZIG_NORECOMPILE,ZIG_RELEASEMODE) - Config flags utility:
src/faebryk/libs/util.py(ConfigFlag,ConfigFlagInt, …) - Test runner + reports:
test/runner/main.py(artifacts/test-report.json,artifacts/test-report.html,artifacts/test-report.llm.json) - CI artifacts definition:
.github/workflows/pytest.yml(test-report.json,test-report.html)
Dependants (Call Sites)
- CI/CD: The
devcommands are the primary interface for GitHub Actions workflows. - Local Development: Developers use
ato dev compileafter modifying Zig code.
How to Work With / Develop / Test
Core Commands
ato dev compile: compile native extensions (graph/typegraph/sexp bindings).ato dev test --llm: runs the orchestrated test runner (defaults to-p test -p src); supports:-kfilter (-- -k ...also works via passthrough args)--baselinecomparisons (commit hash orHEAD~Nstyle)--view/--opento fetch and open thetest-report.htmlartifact from GitHub Actions (requiresghCLI)--cito apply the CI marker expression (not not_in_ci and not regression and not slow)--direct -k <testname>to run a single test viatest/runtest.py(tight single-test loops)
Test Reports (JSON as source of truth)
Local test runs write:
artifacts/test-report.json(single source of truth; outcomes/durations/memory/baseline compare status + stdout/stderr/logs/tracebacks; seetests[].output_full)artifacts/test-report.html(human dashboard; derived from JSON; controlled byFBRK_TEST_GENERATE_HTML=1)artifacts/test-report.llm.json(LLM-friendly; derived from JSON; ANSI stripped logs)
CI uploads both artifacts (see .github/workflows/pytest.yml):
test-report.jsontest-report.html
Notes for LLM debugging:
- Prefer
artifacts/test-report.jsonorartifacts/test-report.llm.jsonover raw output; they include structured failures, logs, baseline compare, and collection errors. - The HTML is best for quickly scanning long-running tests, worker crashes, and per-test output.
Remote/baseline behavior:
ato dev test --llm --baseline <commit>uses the CItest-report.jsonartifact as the baseline (requiresghCLI).ato dev test --llm --view <commit> --opencurrently fetches/opens only the HTML artifact; for JSON, download thetest-report.jsonartifact viagh run download.ato dev test --reuse --baseline <commit>rebuilds JSON/HTML/LLM against a baseline without rerunning tests.ato dev test --keep-openkeeps the live report server running after tests finish.
Useful test-runner environment variables (see test/runner/main.py):
FBRK_TEST_REPORT_INTERVAL(seconds; report refresh cadence)FBRK_TEST_LONG_THRESHOLD(seconds; “long test” threshold)FBRK_TEST_WORKERS(0= cpu count, negative scales workers)FBRK_TEST_GENERATE_HTML(1/0)FBRK_TEST_PERIODIC_HTML(1/0)FBRK_TEST_OUTPUT_MAX_BYTES(truncate preview output used by HTML;tests[].output_fullremains complete)FBRK_TEST_OUTPUT_TRUNCATE_MODE(headortail)FBRK_TEST_BIND_HOST(orchestrator bind host; default0.0.0.0)FBRK_TEST_REPORT_HOST(host used in printed report URL; default bind host)FBRK_TEST_PERF_THRESHOLD_PERCENT(default0.30)FBRK_TEST_PERF_MIN_TIME_DIFF_S(default1.0)FBRK_TEST_PERF_MIN_MEMORY_DIFF_MB(default50.0)
LLM quick usage:
artifacts/test-report.llm.jsonis always generated (ANSI stripped, full tests + logs).ato dev test --llmprints a concise summary + schema + jq hints (stdout only).- jq recipes are embedded in the report under
llm.jq_recipes. - Auto-LLM:
ato dev testenables the summary automatically when running under claude-code/codex-cli/cursor. - Force on/off via
FBRK_TEST_LLM=1orFBRK_TEST_LLM=0.
ConfigFlags (how to use + how to inventory)
ConfigFlag is the repo’s “toggle-by-env-var” mechanism. The environment variable name is the first argument to ConfigFlag(...).
Usage:
export SOME_FLAG=1
Inventory all ConfigFlags in-tree (preferred over trying to maintain a manual list):
ato dev flags
Prefer using ato dev flags when you want the full picture (types/defaults/descriptions + callsite counts) in one place.
High-leverage flags you’ll use often:
- Zig build:
ZIG_NORECOMPILE,ZIG_RELEASEMODE - Solver debug:
SLOG,SVERBOSE_TABLE,SPRINT_START,SMAX_ITERATIONS,SSHOW_SS_IS - Logs:
COLOR_LOGS,LOG_TIME,LOG_FILEINFO
Development Workflow
- Zig Changes: Edit files under
src/faebryk/core/zig/src/-> Runato dev compile. - Profiling: If something is slow, use
ato dev profile <command>to generate a flamegraph or stats.
Testing
- Main test entrypoint:
ato dev test --llm. - If you change CLI behavior, add/adjust tests under
test/that exercise the command surface.
Best Practices
- Use ConfigFlags: For experimental features or verbose debugging, use a
ConfigFlaginstead of commenting out code. - Compile often: Zig errors won’t be caught by Python tooling.
When not to use it
- →Non-Zig project environments
- →Systems without access to repo-specific CLI tools
Prerequisites
Limitations
- →Tight dependency on repo-specific CLI tools
- →Requires existing test-runner configuration
- →Relies on network access for CI artifact fetching
How it compares
It focuses on the repo's internal inner-loop feedback mechanism rather than generic command execution.
Compared to similar skills
dev side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| dev (this skill) | 2 | 6mo | Review | Advanced |
| testing | 0 | 2mo | Review | Advanced |
| tdd-migrate | 1 | 7mo | Review | Advanced |
| ci-pr-helper | 0 | 6mo | Review | Beginner |
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Example prompts that trigger this skill in your AI assistant.
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