Adc Analyzer

Q: Why use Adc Analyzer on TypingMind?

Because you install it once and use it with any model. Adc Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

Q: How do I install Adc Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Arcadia-1/analog-agents/tree/main/skills/adc-analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Q: Which AI models can use Adc Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

Q: How many AI models can I use with Adc Analyzer?

As many as you like. As long as a model supports skills, you can use Adc Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Q: Is the Adc Analyzer AI skill free?

It is published on GitHub by Arcadia-1. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

Q: What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

Q: How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Community

Arcadia-1

adc-analyzer

ADC characterization orchestrator in the analog-agents project. Takes simulated/measured ADC output, produces the standard specs bundle (SNDR/SFDR/THD/ENOB, INL/DNL, FOM, NTF where applicable) as a verifier-report, and hands off back to the design/sizing loop. TRIGGER when the user asks to characterize an ADC, extract ENOB/INL/DNL from dout/aout, compute Walden/Schreier FOM, analyze Σ-Δ NTF, or check thermal/jitter noise floors. For raw API usage (function names, arguments, imports) see the `adctoolbox-user-guide` skill shipped with the package.

Overview

Publisher	Arcadia-1
Repository	`analog-agents`
Skill name	`adc-analyzer`
Stars	84
Forks	19
Bundled files	Instructions only
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Arcadia-1 on GitHub. Read the source before you install it.

Installation

Install the Adc Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Arcadia-1/analog-agents/tree/main/skills/adc-analyzer
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Arcadia-1/analog-agents.git /tmp/analog-agents
mkdir -p .claude/skills
cp -r /tmp/analog-agents/skills/adc-analyzer .claude/skills/adc-analyzer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adc Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Adc Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Adc Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ADC Analyzer

You are the ADC characterization agent. Inputs: dout (digital codes) or aout (reconstructed analog), sample rate fs, input tone fin, resolution. Outputs: a structured spec report plus plots saved under verifier-reports/L2-performance/.

Backend is the adctoolbox package in analog-agents/.venv. All function-level questions ("which function takes what?", "flat vs submodule import") go to the adctoolbox-user-guide skill — do not re-document that here.

Scope boundaries

upstream (spectre skill): runs the simulation, produces the raw output stream
upstream (analog-verify skill): pre-sim review + DC/AC sanity — do not skip
this skill: post-conversion characterization only
downstream (optimizer skill): consumes SNDR/ENOB/FOM as an objective to minimize

Skip this skill for non-ADC analog blocks — those go to analog-verify.

Standard characterization flow

Always run in this order; stop and report the moment something fails.

Coherency check — confirm fin is at a coherent bin for the chosen N; if not, warn and pick a nearby coherent fin (see find_coherent_frequency in the user guide).
Spectrum + core specs — SNDR, SFDR, THD, ENOB, noise floor + FFT plot.
Linearity — INL/DNL from sine histogram (needs full-scale input covering all codes).
Error-domain analysis — only if the spectrum shows structure the specs don't explain (e.g., spurs, periodicity): error-by-phase, error PDF, autocorrelation.
FOMs & floors — Walden + Schreier; compare against thermal-noise and jitter limits; state whether the ADC is noise-, distortion-, or linearity-limited.

For SAR: add weight-calibration pass + radix analysis. For Σ-Δ: add ntf_analyzer.

Report layout

Write to verifier-reports/L2-performance/adc-<timestamp>.md, plots into <project>/output/plots/ or WORK/plots/. Keep numeric output in the markdown; push any waveform/density visualization into saved PNGs.

One table per concern: spec table (measured / target / margin / status), MOSFET op recap (if available from upstream), FOM table, noise-floor comparison. No prose beyond one-line callouts.

Handoff rules

Pass: report convergence to the orchestrator; do not re-dispatch designer.
Fail, iter < max_iter: dispatch analog-design in background with the failing specs, suggested causes from error-domain analysis, and iteration counter incremented.
Fail, iter ≥ max_iter: escalate to orchestrator with all reports attached.

Frequently asked questions

What does the Adc Analyzer AI skill do?

Why use Adc Analyzer on TypingMind?

Because you install it once and use it with any model. Adc Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Adc Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Arcadia-1/analog-agents/tree/main/skills/adc-analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Adc Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Adc Analyzer?

As many as you like. As long as a model supports skills, you can use Adc Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Adc Analyzer AI skill free?

It is published on GitHub by Arcadia-1. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Caveman Stats

JuliusBrussee

CommunityPopular

Show recorded output and cache-read token usage and mode attribution for the current Claude Code session, or locate the host's native usage report. Trigger: /caveman-stats.

Ci Metrics

Query PyTorch CI, GitHub Actions, HUD, Grafana, and infrastructure metrics. Use when users ask about CI duration, job failures, queue times, workflow trends, runner health, dashboard data, or PyTorch…

Notcrawl

Notion archive: search, sync freshness, pages/databases, Markdown exports, SQL counts, and Notcrawl repo work.

Openclaw Test Heap Leaks

openclaw

OrganizationPopular

Investigate OpenClaw pnpm test memory growth, Vitest OOMs, RSS spikes, and heap snapshot deltas.

Adc Analyzer

Overview