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@@ -8,22 +8,24 @@ These skills turn your AI coding agent into a full-fledged electronics design as
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## 🔬 What it looks like in practice
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Point your agent at a KiCad project and it does the rest — parses every schematic and PCB file, traces every net, computes every voltage, and tells you what's wrong before you spend money on boards.
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> "Analyze my KiCad project at `hardware/rev2/`"
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The agent runs the analysis scripts, reads datasheets, and produces a full design review. Here's a condensed example from a real project — a 6-layer BLDC motor controller (187 components):
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Here's a condensed example from a real 6-layer BLDC motor controller (187 components). The agent found all of this automatically:
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**Power tree** — every regulator traced from input to output, feedback dividers identified, output voltage computed:
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**It builds your power tree** — tracing every regulator from input to load, computing output voltages from feedback dividers, and flagging when the math doesn't match:
**It tells you what needs attention** — and what doesn't:
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| Severity | Issue |
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|------------|-------|
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**What looks good:** 170µF bus capacitance across 38 caps, proper GND/GNDPWR domain separation, CAN bus termination verified, 100% MPN coverage across all components, zero DFM violations, JLCPCB standard tier compatible.
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**It maps your protection coverage** — finds every TVS, ESD suppressor, and fuse, then tells you which interfaces are unprotected:
D3 (SMBJ51A): V+ motor bus → GND [TVS, 51V standoff] ✓
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F1 (1A): V+ input [fuse] ✓
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⚠️ CAN_H / CAN_L — no TVS protection (exposed on connector J3)
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⚠️ I2C_SDA / I2C_SCL — no ESD protection (exposed on header J5)
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```
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**It estimates your sleep current** — traces every always-on path and totals the quiescent draw per rail:
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```
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+3.3V sleep current breakdown:
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U3 (TPS629203) quiescent: ~15 µA
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R5/R6 feedback divider (226k/16.2k): 13.6 µA
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R12 pull-up (100k to +3.3V): 33 µA
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Total estimated: ~62 µA
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```
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For a complete example, see the [full design review](example-report.md) of an ESP32-S3 board — 52 components, 2-layer, dual boost converters, USB host, touch sensing. For the end-to-end walkthrough from S-expression parsing through signal detection and datasheet cross-referencing, see [How It Works](how-it-works.md).
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## 🚀 Install
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Ask your agent:
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We're excited to release kicad-happy as a **Claude Code plugin** — you can now install it with two commands from the `/plugin` menu. For OpenAI Codex, the manual install and agent prompt methods still work as before.
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> Clone https://github.com/aklofas/kicad-happy and install all the skills
Every push and PR that touches KiCad files gets a **commit status check** (green/red with findings summary). On PRs, a structured review comment is also posted — power tree, protocol compliance, voltage derating, SPICE results, EMC risk analysis, thermal analysis, component health, and PCB stats. The comment updates on re-pushes. A [full report](skills/kicad/references/report-generation.md) is available on the Actions run page.
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Enable `diff-base: true` to show only what changed between the PR and the base branch — component additions/removals, signal parameter shifts, new/resolved EMC findings, and SPICE status transitions.
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<details>
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<summary><strong>Add AI-powered review (optional — needs Anthropic API key)</strong></summary>
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Chain with [`anthropics/claude-code-action`](https://github.com/anthropics/claude-code-action) for Claude to read the analysis + datasheets and write a natural-language design review. The cost estimates below apply only when using the Anthropic API (`ANTHROPIC_API_KEY`) for CI — there's no additional cost when reviewing locally with a Claude Code or OpenAI Codex subscription. Two options:
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**Quick review** (~$1-3 per PR via API, 5-10 min):
**Setup:** Get an API key from [console.anthropic.com/settings/keys](https://console.anthropic.com/settings/keys), then add it as a repository secret named `ANTHROPIC_API_KEY` in Settings → Secrets → Actions. Cost depends on design complexity — see [Anthropic pricing](https://www.anthropic.com/pricing).
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</details>
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Also available as a **GitHub Action** for automated PR reviews. Every push and PR that touches KiCad files gets a commit status check and a structured review comment — power tree, SPICE results, EMC risk, thermal analysis, and more. Optionally chain with Claude for AI-powered natural-language reviews.
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See [`action/examples/`](action/examples/) for fork-safe workflows, distributor API keys for datasheet download, and advanced configuration.
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See the **[GitHub Action setup guide](github-action.md)** for workflow examples, diff-based PR reviews, and AI-powered review configuration.
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## 📦 Skills
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| KiCad 6 | Full | Full | Full |
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| KiCad 5 | Full (legacy `.sch` + `.lib`) | Full | Full |
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## 🎯 v1.1 — EMC Pre-Compliance + Analysis Toolkit
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New skill: **EMC pre-compliance risk analysis** — predicts the most common causes of EMC test failures from your KiCad schematic and PCB layout. Plus four new analysis tools for tolerance, diffing, thermal, and what-if exploration.
|**Plugin install**| Available as a Claude Code plugin marketplace — `/plugin marketplace add aklofas/kicad-happy`. |
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|**Monte Carlo tolerance**|`--monte-carlo N` runs N simulations with randomized component values within tolerance bands. Reports 3σ bounds and per-component sensitivity analysis. |
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|**Design diff**| Compares two analysis JSONs — component changes, signal parameter shifts, EMC finding deltas. GitHub Action `diff-base: true` for automatic PR comparison. |
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|**Thermal hotspots**| Junction temperature estimation for LDOs, switching regulators, shunt resistors. Package Rθ_JA lookup, thermal via correction, proximity warnings. |
|**Code audit**| 22 bug fixes (trace inductance 25x overestimate, PDN target impedance, regulator voltage suffix parser, inner-layer reference planes, and more). Full AnalysisContext migration for cleaner internals. |
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|**Validation**| 6,853 EMC analyses across 1,035 repos (zero crashes), 96 equations verified against primary sources, 404K+ regression assertions at 100% pass rate. |
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## 🎯 v1.0 — First Stable Release
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This is the first stable release of kicad-happy. It marks the point where every piece of the analysis pipeline — schematic parsing, PCB layout review, Gerber verification, SPICE simulation, datasheet cross-referencing, BOM sourcing, and manufacturing prep — has been built, tested against 1,035 real-world KiCad projects, and validated with 294K+ regression assertions. Zero analyzer crashes across the full corpus.
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| SPICE subcircuit simulations | 30,646 across 17 types |
Add automated design review to any KiCad project. Every push and PR that touches KiCad files gets a **commit status check** (green/red with findings summary). On PRs, a structured review comment is posted covering power tree, protocol compliance, voltage derating, SPICE results, EMC risk analysis, thermal analysis, component health, and PCB stats.
The PR comment updates on re-pushes. A [full report](skills/kicad/references/report-generation.md) is available on the Actions run page. SPICE-enhanced mode activates automatically when ngspice is installed. EMC and thermal analysis run automatically after schematic/PCB analysis.
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## Diff-based PR reviews
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Enable `diff-base: true` to show only what changed between the PR and the base branch — component additions/removals, signal parameter shifts, new/resolved EMC findings, and SPICE status transitions. The PR comment includes a "Changes from Base" section.
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```yaml
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- uses: aklofas/kicad-happy@v1
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id: analysis
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with:
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diff-base: true
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```
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## AI-powered review (optional)
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Chain with [`anthropics/claude-code-action`](https://github.com/anthropics/claude-code-action) for Claude to read the analysis + datasheets and write a natural-language design review. The deterministic analysis (schematic, PCB, EMC, thermal) is always free. The cost estimates below come from Anthropic API calls made by `claude-code-action` — there's no additional cost when reviewing locally with a Claude Code or OpenAI Codex subscription.
Get an API key from [console.anthropic.com/settings/keys](https://console.anthropic.com/settings/keys), then add it as a repository secret named `ANTHROPIC_API_KEY` in Settings → Secrets → Actions. Cost depends on design complexity — see [Anthropic pricing](https://www.anthropic.com/pricing).
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## More examples
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See [`action/examples/`](action/examples/) for fork-safe workflows, distributor API keys for datasheet download, and advanced configuration.
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