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 Arcadia-1/virtuoso-bridge-lite --skill netlistgit clone --depth 1 https://github.com/Arcadia-1/virtuoso-bridge-liteWrote 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/arcadia-1/virtuoso-bridge-lite/netlist)<a href="https://agentmods.dev/skills/arcadia-1/virtuoso-bridge-lite/netlist"><img src="https://agentmods.dev/badge/skills/arcadia-1/virtuoso-bridge-lite/netlist/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/arcadia-1/virtuoso-bridge-lite/netlist"><img src="https://agentmods.dev/badge/skills/arcadia-1/virtuoso-bridge-lite/netlist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.00715 |
| Opus 5 | $0.00045 | $0.00358 |
| Sonnet 5 | $0.00018 | $0.00143 |
| Haiku 4.5 | $0.00009 | $0.00072 |
Grade A, and why
netlist 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Netlist Semantic Cleanup
Use this skill when converting generated netlists into readable, reviewable Spectre/SPICE reference decks.
Principle
The primary cleanup engine is semantic understanding by the model and engineer. Do not treat netlist cleanup as a blind text rewrite. A checker can report leftover tool artifacts, but it cannot decide circuit boundaries, node meaning, or instance names.
Workflow
- Preserve the raw generated artifact. Never edit ADE/PEX output in place.
- Read enough context to understand the circuit: ports, hierarchy, stimulus, measurements, clocking, biasing, and intended DUT boundary.
- Read
references/cleaning.mdbefore curating a real design. - Draft the semantic cleanup plan:
- DUT subckt or wrapper interface.
- Testbench-owned supplies, clocks, stimulus, loads, probes, and analyses.
- Run-deck-owned parameters, model includes, corners, sweeps, and saves.
- Rename map for random nodes/instances, plus unresolved review notes.
- Create the clean netlist as a curated source artifact. Use model reasoning to split DUT/testbench/run decks and to choose semantic names.
- Run the checker only after the semantic pass:
python skills/netlist/scripts/check_spectre_netlist.py netlist/dut/block.scs --mode dut
python skills/netlist/scripts/check_spectre_netlist.py netlist/tb/tb_block.scs --mode tb
The checker reports suspicious MOS tail parameters, random-looking node names, generic instance names, and DUT/testbench mixing. It does not rewrite files and should not be used as the main cleanup mechanism.
Rules
- Preserve MOS instance parameters by default when numerical behavior matters. Removing layout side-effect tails is an explicit stripped-reference choice, not the default.
- If a stripped reference is requested, it may remove
ad/as,pd/ps,nrd/nrs,sa/sb/sca/scb,sp*, DFM, stress, proximity, and extraction parameters, but expect performance differences and validate against the full-parameter or raw deck. - Split reusable artifacts into DUT, testbench, and run decks. A clean DUT file should not contain supplies, clocks, sweeps, saves, probes, or analysis statements.
- At the top of every curated netlist file or section containing MOS devices,
add an explicit terminal-order comment, for example:
// MOS terminal order: D G S B (drain gate source bulk/body). - Replace random names (
net1,_net23,N_*, numeric mesh nodes,I42,M0) with semantic names where the circuit meaning is known. If meaning is unknown, leave a short review note instead of guessing. - Validate after cleanup with a parser or Spectre syntax/smoke run when Cadence is available.
What ships with it
2 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.
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 · 62 lines · 90 tokens per session scan A fa1a907f4ff1
netlist is a skill published in the GitHub repository Arcadia-1/virtuoso-bridge-lite (709 stars, last pushed 6d ago), licensed MIT. It adds 90 tokens to every session and 715 once invoked, about $0.0005 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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