post-layout-signoff

post-layout-signoff is a skill for Claude Code from hdl-tools/analog-chip-design-agents. It costs 79 tokens per session (2,147 once invoked), scanned A, original, MIT.

A workflow for checking a chip circuit after layout by simulating its extracted electrical model across operating conditions and random variations. It compares the results with the original specifications and controls tape-out approval.

In plain words
What is it for?
Use it to run post-layout corner and Monte Carlo simulations, measure parasitic degradation, reopen circuit or layout fixes, and decide whether a block is ready for tape-out.
Why use it?
Physical layout adds parasitic effects that can change circuit behavior, so the original schematic results may no longer be sufficient.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

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

Good fit Use it to run post-layout corner and Monte Carlo simulations, measure parasitic degradation, reopen circuit or layout fixes, and decide whether a block is ready for tape-out.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hdl-tools/analog-chip-design-agents/post-layout-signoff
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 post-layout-signoff
Clone the repo
git clone --depth 1 https://github.com/hdl-tools/analog-chip-design-agents

Made for: Claude Code.

Or install analog-design-post-layout, 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 post-layout-signoff

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/hdl-tools/analog-chip-design-agents/post-layout-signoff"><img src="https://agentmods.dev/badge/skills/hdl-tools/analog-chip-design-agents/post-layout-signoff.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 2,147 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 $0.02147
Opus 5 $0.00039 $0.01073
Sonnet 5 $0.00016 $0.00429
Haiku 4.5 $0.00008 $0.00215

Measured 11d ago against content hash 9b30c092f7e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

post-layout-signoff 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 11d 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/post-layout/skills/post-layout-signoff/SKILL.md · 217 lines

How it starts

The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Post-Layout Sign-off

Invocation

  • If invoked by a user presenting a post-layout sign-off task: immediately spawn the analog-chip-design-agents:post-layout-signoff-orchestrator agent and pass the full user request and any available context. Do not execute stages directly.
  • If invoked by the post-layout-signoff-orchestrator mid-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:

  1. memory/post-layout/knowledge.md — known parasitic-degradation patterns, stability/CMRR loss recipes, corner re-sim pitfalls. Incorporate its guidance into every analysis.
  2. memory/post-layout/run_state.md — current run identity for resume-after-interruption.

Purpose

Close the design on the extracted (PEX) netlist: re-run corners/Monte-Carlo, re-verify specs versus the pre-layout design, quantify parasitic degradation, and gate tape-out. Five stages with explicit QoR gates. On a post-layout spec loss the sign-off cannot absorb, this domain opens a fix_request routed to custom-layout (parasitic reduction) or circuit-design (re-design). The final tapeout_signoff stage is a human-approval checkpoint.


Supported EDA Tools

Open-Source

  • ngspice (ngspice) / Xyce (Xyce) — corner/MC simulation on the extracted netlist
  • PySpice (python -m PySpice) — scripted corner / Monte-Carlo orchestration and post-processing

Proprietary (detect-only — never installed)

  • Cadence Spectre / Spectre X / APS (spectre)
  • Synopsys PrimeSim / FineSim (primesim)
  • Siemens AFS (Analog FastSPICE) (afs)

Stage: pex_netlist_assembly

Domain Rules

  1. Assemble the post-layout testbench around the PEX netlist from design_state.pex.netlist, reusing the pre-layout .measure testbench so specs compare like-for-like.
  2. Confirm device/net names map between the PEX netlist and the testbench; resolve any unmapped probes.
  3. Include the PDK model corners and the sign-off corner set from constraints.corners.

Read the full file on GitHub · 217 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. 11d ago First seen · 217 lines · 79 tokens per session scan A 9b30c092f7e7

Subscribe to this mod's changes

post-layout-signoff 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 2,147 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

neuroskill-bci

Use live BCI cognitive and mood state from NeuroSkill.

NousResearch/hermes-agent · 18 tokens

ruview-advanced-sensing

Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection…

ruvnet/RuView · 84 tokens

ruview-applications

Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually do something…

ruvnet/RuView · 79 tokens

lab-hardware-cad

Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research…

K-Dense-AI/scientific-agent-skills · 106 tokens

opentrons-integration

Author, review, migrate, simulate, and troubleshoot official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. Use for robot-specific liquid handling, deck and labware setup, pipettes, modules, runtime parameters, liquid classes, and Opentrons App analysis. Use pylabrobot instead when one workflow…

K-Dense-AI/scientific-agent-skills · 79 tokens

pylabrobot

Develop and review PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Use for PyLabRobot protocols or API questions; keep physical execution behind an explicit operator safety gate.

K-Dense-AI/scientific-agent-skills · 49 tokens