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 hdl-tools/analog-chip-design-agents --skill characterizationgit clone --depth 1 https://github.com/hdl-tools/analog-chip-design-agentsWrote 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/hdl-tools/analog-chip-design-agents/characterization)<a href="https://agentmods.dev/skills/hdl-tools/analog-chip-design-agents/characterization"><img src="https://agentmods.dev/badge/skills/hdl-tools/analog-chip-design-agents/characterization.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00079 | $0.02556 |
| Opus 5 | $0.00039 | $0.01278 |
| Sonnet 5 | $0.00016 | $0.00511 |
| Haiku 4.5 | $0.00008 | $0.00256 |
Grade A, and why
characterization 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 8d 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Characterization
Invocation
- If invoked by a user presenting a characterization task: immediately spawn the
analog-chip-design-agents:characterization-orchestratoragent and pass the full user request and any available context. Do not execute stages directly. - If invoked by the
characterization-orchestratormid-flow (including re-validation): 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:
memory/characterization/knowledge.md— known .lib generation patterns, sweep/corner recipes, monotonicity fixes, and PDK/tool quirks. Incorporate its guidance into every stage.memory/characterization/run_state.md— current run identity for resume-after-interruption.
Purpose
Produce the validated abstract views of a signed-off, extracted analog/mixed macro: timing, power,
and noise characterized across the required PVT corners, written as Liberty (.lib) plus
behavioral models, and validated against SPICE. Seven stages with explicit QoR gates.
Characterization is a terminal consumer — its loop-backs are stage-local retries
(model_validation → char_setup); it does not open cross-domain fix_requests. A characterization
that cannot converge on a valid model after the retry cap escalates to the user.
Supported EDA Tools
Open-Source
- ngspice / Xyce (
ngspice/xyce) — sweep harnesses driving the characterization grid - Python
.libwriters — emit NLDM/CCS-style Liberty tables from the sweep results - scipy / numpy — monotonicity checks, interpolation, model fitting
Proprietary (detect-only — never installed)
- Cadence Liberate (
liberate) — characterization + .lib generation - Synopsys SiliconSmart (
siliconsmart) - Siemens Solido ML Characterization (
solido) - Altos (legacy)
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.
- 8d ago First seen · 270 lines · 79 tokens per session scan A 19468048244f
characterization 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 2,556 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.
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