kicad-happy is a collection of coding-agent skills and tools that inspect KiCad schematics, PCB layouts, and Gerber files for electronics design issues. It is for hardware designers who want automated reviews, simulations, datasheet checks, component sourcing, and fabrication preparation. The catalogue entries are its agent skills, rules, plugin, and instruction for integrating this workflow with coding agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aklofas/kicad-happy --skill datasheetsgit clone --depth 1 https://github.com/aklofas/kicad-happyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aklofas/kicad-happy/datasheets)<a href="https://agentmods.dev/skills/aklofas/kicad-happy/datasheets"><img src="https://agentmods.dev/badge/skills/aklofas/kicad-happy/datasheets/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aklofas/kicad-happy/datasheets"><img src="https://agentmods.dev/badge/skills/aklofas/kicad-happy/datasheets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00156 | $0.02464 |
| Opus 5 | $0.00078 | $0.01232 |
| Sonnet 5 | $0.00031 | $0.00493 |
| Haiku 4.5 | $0.00016 | $0.00246 |
Grade A, and why
datasheets scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Datasheets Skill
Related Skills
| Skill | Relationship |
|---|---|
digikey / mouser / lcsc / element14 |
Producers — download the PDFs under <project>/datasheets/ that this skill extracts from |
kicad |
Primary consumer — VM-001/PU-001/FS-001/PP-001/LR-001/XT-001 + Phase 4b lookup detectors (AM-001/OV-001/TJ-001/FT-001/EX-001) query extractions via lookup(mpn) for verified-IC knowledge |
emc |
Consumer — switching-frequency, package-Rθ_JA, and operating-voltage data sharpen EMC heuristics |
spice |
Consumer — SPICE model presence + IBIS data feed simulation-readiness checks |
thermal |
Consumer — package Rθ_JA + junction temperature limits drive Tj estimates (TS-001..TJ-001) |
bom |
Indirect — coverage of structured extractions affects BOM verification confidence |
Handoff guidance: This skill is consumer infrastructure. The typical flow is distributor skill downloads PDF → datasheets skill extracts → analyzer skill queries. Use this skill directly when (a) the user asks to extract or verify a specific MPN, (b) an analyzer reports trust_level: low and the gap is per-MPN extraction quality, or (c) a new MPN was added to the BOM and downstream detectors should pick up its verified specs. Don't run this skill in isolation if the user just wants a design review — call it from the kicad workflow at the "Sync datasheets" step instead.
Purpose
Extract structured, machine-readable specifications from component datasheet PDFs and make them available to analyzer skills. Works on whatever PDFs are downloaded under <project>/datasheets/ (downloads are owned by distributor skills like digikey, mouser, lcsc, element14).
Scope
This skill owns:
- Extraction schemas — canonical JSON structures for per-MPN specs. v1.4 ships 6 JSON Schema Draft 2020-12 schemas under
schemas/(base,pinout,spec_value,regulator,extraction,manifest) plus 5 v1.4 category extensions (diode, transistor, opamp, mcu, crystal). v1.3 cache format (EXTRACTION_VERSIONinscripts/datasheet_extract_cache.py) is still read for compat. - Typed access layer (v1.4) —
datasheet_types/package exposesDatasheetFacts,SpecValue,Pin,Pinout,lookup(),best(),trusted(),has_data(). Recommended for all new consumers. - PDF page selection — heuristics to pick pages most likely to contain pinouts, e-chars, applications, SPICE models.
- Quality scoring — v1.4 uses a three-dimension rubric (pinout completeness, base completeness, category-extension completeness, 0–100 scale). v1.3 5-dimension weighted rubric still applies to legacy caches.
- Consumer APIs —
scripts/datasheet_lookup.pyfor v1.4 typed access;scripts/datasheet_features.pyfor the v1.3 dict-shaped helpers (get_regulator_features,get_mcu_features,get_pin_function) — the v1.3 helpers dual-read v1.4 caches and translate to v1.3 dict shape for legacy detector code. Sunset planned for v1.6. - Verification —
datasheet_verify.py(v1.3, schema-vs-usage cross-check) plusdatasheet_verify_v14_extraction(v1.4, power_domain references resolve, recommended ≤ absolute, regulator pin references exist).
What ships with it
59 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- datasheet_types/__init__.py 2.6 KB runs code
- datasheet_types/base_block.py 6.3 KB runs code
- datasheet_types/codec.py 5.6 KB runs code
- datasheet_types/extraction.py 8.1 KB runs code
- datasheet_types/pinout.py 5.2 KB runs code
- datasheet_types/regulator.py 5.3 KB runs code
- datasheet_types/spec_value.py 2.4 KB runs code
- datasheet_types/trust_gating.py 4.2 KB runs code
- examples/abm8g-106-12.000mhz-t.json 9.4 KB
- examples/irlml6344.json 16 KB
- examples/lm2596-adj.json 14 KB
- examples/lm358.json 16 KB
- examples/mbrs540t3g.json 12 KB
- examples/stm32f103c8t6.json 51 KB
- prompts/base.md 3.7 KB
- prompts/crystal.md 8.8 KB
- prompts/diode.md 8.3 KB
- prompts/mcu.md 9.6 KB
- prompts/opamp.md 11 KB
- prompts/pinout.md 3.7 KB
- prompts/regulator.md 4.3 KB
- prompts/scout.md 3.5 KB
- prompts/transistor.md 13 KB
- references/cache-layout.md 8.3 KB
- references/consumer-api.md 8.6 KB
- references/dispatch-claude-code.md 8.7 KB
- references/dispatcher-contract.md 7.2 KB
- references/extraction-pipeline.md 1.3 KB
- references/extraction-schema.md 17 KB
- references/field-extraction-guide.md 14 KB
- references/quality-scoring.md 7.8 KB
- schemas/base.schema.json 9.3 KB
- schemas/CHANGELOG.md 15 KB
- schemas/crystal.schema.json 7.2 KB
- schemas/diode.schema.json 7.9 KB
- schemas/extraction.schema.json 3.7 KB
- schemas/fixtures/lm2596-adj.example.json 14 KB
- schemas/fixtures/manifest.example.json 1000 B
- schemas/fixtures/minimal.example.json 2.1 KB
- schemas/manifest.schema.json 3.0 KB
- schemas/mcu.schema.json 12 KB
- schemas/opamp.schema.json 9.2 KB
- schemas/pinout.schema.json 5.9 KB
- schemas/plan.schema.json 4.7 KB
- schemas/regulator.schema.json 8.3 KB
- schemas/scout.schema.json 2.5 KB
- schemas/spec_value.schema.json 3.0 KB
- schemas/transistor.schema.json 12 KB
- scripts/_smoke_v14_roundtrip.py 8.2 KB runs code
- scripts/datasheet_extract_cache.py 18 KB runs code
- scripts/datasheet_features.py 16 KB runs code
- scripts/datasheet_lookup.py 8.9 KB runs code
- scripts/datasheet_page_selector.py 17 KB runs code
- scripts/datasheet_score.py 16 KB runs code
- scripts/datasheet_verify.py 40 KB runs code
- scripts/merge_results.py 11 KB runs code
- scripts/plan_extraction.py 7.4 KB runs code
- scripts/validate_extraction_result.py 4.3 KB runs code
- scripts/validate_sanity_vector.py 5.9 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 120 lines · 156 tokens per session scan A 84fb369c6ff1
datasheets is a skill published in the GitHub repository aklofas/kicad-happy (1,166 stars, last pushed 8d ago), licensed MIT. It adds 156 tokens to every session and 2,464 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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