agentmods.dev

qspice-waveform-analysis

qspice-waveform-analysis is a skill for Claude Code, Codex from kh6570/HAbedini-qspice-mcp. It costs 62 tokens per session (842 once invoked), scanned A, original, MIT.

A workflow for examining QSpice waveform files produced by simulations and calculating values such as peaks, RMS, gain, or distortion.

In plain words
What is it for?
Use it to list signals, read selected time ranges, compare or calculate signals, measure results, and export traces.
Why use it?
It turns simulation traces into specific measurements without requiring you to inspect every raw sample.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 5repo 1mo ago A scan 62 tokens original MIT

Good fit Use it to list signals, read selected time ranges, compare or calculate signals, measure results, and export traces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis
View source ↗ kh6570/HAbedini-qspice-mcp
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 kh6570/HAbedini-qspice-mcp --skill qspice-waveform-analysis
Clone the repo
git clone --depth 1 https://github.com/kh6570/HAbedini-qspice-mcp

Made for: Claude Code, Codex.

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 qspice-waveform-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis/github.svg)](https://agentmods.dev/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis)
Your own site
<a href="https://agentmods.dev/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis"><img src="https://agentmods.dev/badge/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis/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 qspice-waveform-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis"><img src="https://agentmods.dev/badge/skills/kh6570/habedini-qspice-mcp/qspice-waveform-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 842 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 $0.00062 $0.00842
Opus 5 $0.00031 $0.00421
Sonnet 5 $0.00012 $0.00168
Haiku 4.5 $0.00006 $0.00084

Measured 12d ago against content hash abf43d4a3ac8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qspice-waveform-analysis 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 12d 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.

src/qspice_mcp/data/skills/qspice-core/qspice-waveform-analysis/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QSpice: Waveform Analysis

A workflow for turning a completed .qraw result into answers: which signals exist, what a derived quantity looks like, and what the scalar metrics are.

When to use

  • A simulation finished and you need to read or quantify the result.
  • You need a derived signal (difference, product, ratio) the raw file does not store directly, e.g. V(out)-V(in) or instantaneous power V(n1)*I(L1).
  • You need scalar metrics (RMS, mean, peak-to-peak, gain) or a Fourier/noise summary.

When NOT to use

  • The run failed / produced no waveform → use qspice-convergence-debugging.
  • You still need to author or simulate the circuit → qspice-getting-started.

Workflow

  1. Enumerate. list_signals (and list_steps for stepped/.step runs) to learn the exact, case-correct signal names. QSpice lowercases net names, so a node drawn as VOUT is read as V(vout).
  2. Read a single trace. read_waveform with a signal and optional t_start/t_end. Responses are budget-capped (2000 points); narrow the window instead of asking for everything.
  3. Derive across signals. evaluate_waveform_expression with an arithmetic expression over signal tokens — V(out)-V(in), V(out)*I(L1), 2*V(fb). Only + - * / **, parentheses, and numeric constants are allowed; all referenced signals must share one axis (same raw, step, window).
  4. Quantify. measure_waveform for RMS/mean/max/min/peak-to-peak on one signal; read_noise for .noise integrated/spot output.
  5. Harmonics and distortion. Stage .four with prepare_four, re-run, then read_fourier for the harmonic table — or skip the directive entirely and use compute_thd (post-processing FFT THD on any periodic trace) and export_fft_spectrum for a full spectrum CSV.
  6. Frequency response. measure_bode_response extracts gain/phase versus frequency from an AC or .bode result in one call.
  7. Log-side measures. prepare_meas stages .meas directives (find_at/avg/trig_targ/fra/four); after the run, list_measures enumerates the QPOST-derived blocks and read_measures returns their values with optional step filtering.
  8. Visualize / export. plot_waveforms for a PNG preview; export_waveform_csv when downstream tooling needs the full series outside the MCP budget.

Read the full file on GitHub · 64 lines

Files

What ships with it

1 file 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.

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. 12d ago First seen · 64 lines · 62 tokens per session scan A abf43d4a3ac8

Subscribe to this mod's changes

qspice-waveform-analysis is a skill published in the GitHub repository kh6570/HAbedini-qspice-mcp (5 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 842 once invoked, about $0.0003 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 2026-08-31.

Analytics and metricsScientific
Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens