Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/vibeic/vibe-icnpx agentmods add skills/vibeic/vibe-ic/analog-sizing-loopWrote 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/vibeic/vibe-ic/analog-sizing-loop)<a href="https://agentmods.dev/skills/vibeic/vibe-ic/analog-sizing-loop"><img src="https://agentmods.dev/badge/skills/vibeic/vibe-ic/analog-sizing-loop.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00064 | $0.02795 |
| Opus 5 | $0.00032 | $0.01398 |
| Sonnet 5 | $0.00013 | $0.00559 |
| Haiku 4.5 | $0.00006 | $0.00280 |
Grade A, and why
analog-sizing-loop 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analog Sizing Loop
Automates the iterative analog design loop that previously required 5-14 manual iterations (per PRACTICAL_NOTES.md). Orchestrates analog-sizing → analog-netlist-gen → eda_spice_corner in a closed loop with spec-driven convergence.
When to use
- Step A4 of the analog track (after topology + initial sizing)
- When a single SPICE run shows failing corners and the user wants automated optimization
- After
/analog-sizingprovides an initial design point
Inputs
analog/<block>/spec.json— performance targets with min/max limitsanalog/<block>/topology.md— selected topologyanalog/<block>/sizing.md— initial sizing fromanalog-sizing- PDK (gf180 or sky130)
Loop workflow
Iteration 0:
analog-sizing → initial W/L + bias
analog-netlist-gen → SPICE deck
eda_spice_corner (TT only) → quick sanity check
If TT fails → re-size immediately (don't waste time on corners)
Iteration 1-N (max 5):
eda_spice_corner (all corners: TT/SS/FF × -40/25/125°C)
yield-vs-spec + worst-corner → enforced by programs/corner_yield_vs_spec_check.py
If all PASS → done
If FAIL:
1. (deterministic) worst corner is reported by corner_yield_vs_spec_check.py
2. (JUDGMENT) identify the DOMINANT failure at that corner — gain shortfall
vs the spec it violates may live in M1's gm, the load impedance, or the
bias point; the canned table only approximates this.
3. (JUDGMENT) identify the SENSITIVE device — which transistor's
gm/parameter actually drives the failing spec for THIS topology.
4. once the failure mode is named, the canonical parameter delta is a
table lookup → enforced by programs/sizing_adjust_policy.py
5. Re-generate netlist with new sizes; re-simulate
- TT-only on iteration 0, full PVT sweep on iter ≥1 — enforced by
programs/corner_schedule_policy.py(policy emit + sizing_history audit). - Yield-table vs spec.json limits + worst-corner argmin — enforced by
programs/corner_yield_vs_spec_check.py(re-derives PASS/FAIL from spec.json min/max, independent of any pre-computedstatusfield). - Convergence-strategy table (named failure mode → canonical sizing delta)
— enforced by
programs/sizing_adjust_policy.py:
What ships with it
2 files 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.
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 · 223 lines · 64 tokens per session scan A 03d2331427f7
analog-sizing-loop is a skill published in the GitHub repository vibeic/vibe-ic (23 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 2,795 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 2026-08-30.
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