behavioral-modeling

behavioral-modeling is a skill for Claude Code from hdl-tools/analog-chip-design-agents. It costs 79 tokens per session (3,173 once invoked), scanned A, original, MIT.

A skill for creating and checking analog and mixed-signal models in hardware description languages such as Verilog-A and SystemVerilog. Mixed-signal models represent both continuous electrical behavior and digital signals.

In plain words
What is it for?
Use it to plan, write, compile, connect, and validate behavioral models for analog blocks and analog-digital interfaces.
Why use it?
It provides rules for building models that can be compiled and compared with circuit simulations, helping catch inaccurate or unusable models.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the analog-design-modeling plugin — 1 skill, 1 agent shipped together

Good fit Use it to plan, write, compile, connect, and validate behavioral models for analog blocks and analog-digital interfaces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hdl-tools/analog-chip-design-agents/behavioral-modeling
Install

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.

Any agent
npx skills add hdl-tools/analog-chip-design-agents --skill behavioral-modeling
Clone the repo
git clone --depth 1 https://github.com/hdl-tools/analog-chip-design-agents

Made for: Claude Code.

Or install analog-design-modeling, the plugin that ships this one along with the rest of its 1 skill, 1 agent.

Wrote 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.

agentmods badge for behavioral-modeling

README.md
[![agentmods](https://agentmods.dev/badge/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling/github.svg)](https://agentmods.dev/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling)
Your own site
<a href="https://agentmods.dev/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling"><img src="https://agentmods.dev/badge/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling/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.

agentmods 80×15 button for behavioral-modeling

Your own site · 80×15
<a href="https://agentmods.dev/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling"><img src="https://agentmods.dev/badge/skills/hdl-tools/analog-chip-design-agents/behavioral-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,173 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.03173
Opus 5 $0.00039 $0.01587
Sonnet 5 $0.00016 $0.00635
Haiku 4.5 $0.00008 $0.00317

Measured 10d ago against content hash 2461e292a0fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

behavioral-modeling 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.

plugins/modeling/skills/behavioral-modeling/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Behavioral / AMS Modeling

Invocation

  • If invoked by a user presenting a modeling task: immediately spawn the analog-chip-design-agents:behavioral-modeling-orchestrator agent and pass the full user request and any available context. Do not execute stages directly.
  • If invoked by the behavioral-modeling-orchestrator mid-flow (including fix-request servicing): do not spawn a new agent. Treat this file as read-only — return the requested stage rules, sign-off criteria, or loop-back guidance.

Spawning the orchestrator from within an active orchestrator run causes recursive delegation and must never happen.

Pre-run Context

Before executing or advising on any stage, read the following if they exist:

  1. memory/modeling/knowledge.md — known Verilog-A idioms, OpenVAF/ADMS quirks, convergence recipes, RNM pitfalls. Incorporate its guidance into every authoring decision.
  2. memory/modeling/run_state.md — current run identity (run_id, design_name, pdk, last_stage) for resume-after-interruption.

Purpose

Author, compile, and validate analog behavioral models and the connect modules that bridge analog and digital domains — the "analog HDL" capability. Six stages with explicit QoR gates and loop-back criteria enforced by the behavioral-modeling orchestrator. A model is only signed off when it is both accurate (vs a SPICE reference) and faster than SPICE.


Supported EDA Tools

Open-Source

  • OpenVAF (openvaf) — Verilog-A → OSDI compiler for ngspice / Xyce; the primary path
  • ADMS (admsXml) — legacy Verilog-A → C model generation
  • ngspice (ngspice) / Xyce (Xyce) — OSDI loading + model-vs-SPICE co-sim
  • SystemVerilog RNM (nettype/wreal) via Verilator (verilator) / Icarus (iverilog)
  • Hdl21 + VLSIR (python -m hdl21) — programmatic (Python) analog HDL
  • GHDL-AMS (ghdl) — limited VHDL-AMS support

Proprietary (detect-only — never installed)

  • Cadence AMS Designer / Xcelium AMS (xrun) — Verilog-AMS / Verilog-A reference
  • Spectre Verilog-A (spectre) — Verilog-A in Spectre
  • Synopsys VCS-AMS / CustomSim (vcs) — AMS co-sim
  • Siemens Symphony / Symphony Pro — AMS simulation

Read the full file on GitHub · 259 lines

Changes

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.

  1. 10d ago First seen · 259 lines · 79 tokens per session scan A 2461e292a0fc

Subscribe to this mod's changes

behavioral-modeling is a skill published in the GitHub repository hdl-tools/analog-chip-design-agents (22 stars, last pushed 3mo ago), licensed MIT. It adds 79 tokens to every session and 3,173 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

gke-compute-classes

Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…

google/skills · 83 tokens

jetson-diagnostic

Read-only Jetson health snapshot for identity, memory, GPU, thermal, power, storage, services, and top processes.

NVIDIA/skills · 30 tokens

doca-socket-relay

Use this skill when the operator is driving the DOCA Socket Relay to bridge a socket-oriented host application onto a BlueField DPU peer without rewriting it — picking the deployment shape (in-process, sidecar, or BlueField service container), configuring the host-side socket and the DPU-side forwarding endpoint…

NVIDIA/skills · 236 tokens

offensive-z-wave

Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting…

SnailSploit/Claude-Red · 113 tokens

hsb-flash

Flash the FPGA on an HSB board connected to an NVIDIA devkit. Supports HSB Lattice boards (FPGA versions 2407, 2412, 2507, 2510) and Leopard Imaging VB1940 "all-in-one" cameras (FPGA versions 2507, 2510). Uses release-specific YAML manifests and board-type-specific program commands. Lattice and VB1940 commands must…

NVIDIA/skills · 94 tokens

jetson-validate-image

Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.

NVIDIA/skills · 50 tokens