manufacturability-loop

manufacturability-loop is a skill for Claude Code from JMMonte/agentic-digital-twin. It costs 89 tokens per session (850 once invoked), scanned A, original, MIT.

A repeated design-and-check process for packaging a hardware-as-code project. It separates fabricated parts from ready-made components and checks whether their placement, weight, wiring, clearances, and access fit together.

In plain words
What is it for?
Use it to document parts, suppliers, joints, harnesses, access openings, positions, and sizes, then run an automated manufacturability and packaging check.
Why use it?
It catches physical problems such as collisions, incorrect mass or balance, poor containment, and blocked retrieval paths that may not be visible in a digital design.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agentic-digital-twin plugin — 8 skills, 1 agent shipped together

Good fit Use it to document parts, suppliers, joints, harnesses, access openings, positions, and sizes, then run an automated manufacturability and packaging check.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jmmonte/agentic-digital-twin/manufacturability-loop
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 JMMonte/agentic-digital-twin --skill manufacturability-loop
Clone the repo
git clone --depth 1 https://github.com/JMMonte/agentic-digital-twin

Made for: Claude Code.

Or install agentic-digital-twin, the plugin that ships this one along with the rest of its 8 skills, 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 manufacturability-loop

README.md
[![agentmods](https://agentmods.dev/badge/skills/jmmonte/agentic-digital-twin/manufacturability-loop/github.svg)](https://agentmods.dev/skills/jmmonte/agentic-digital-twin/manufacturability-loop)
Your own site
<a href="https://agentmods.dev/skills/jmmonte/agentic-digital-twin/manufacturability-loop"><img src="https://agentmods.dev/badge/skills/jmmonte/agentic-digital-twin/manufacturability-loop/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 manufacturability-loop

Your own site · 80×15
<a href="https://agentmods.dev/skills/jmmonte/agentic-digital-twin/manufacturability-loop"><img src="https://agentmods.dev/badge/skills/jmmonte/agentic-digital-twin/manufacturability-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 850 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 $0.00089 $0.00850
Opus 5 $0.00044 $0.00425
Sonnet 5 $0.00018 $0.00170
Haiku 4.5 $0.00009 $0.00085

Measured 8d ago against content hash 9f229fe6ac1d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

manufacturability-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.

skills/manufacturability-loop/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

The manufacturability / packaging loop

Manufacturability is a deliberate BLEND: judgment that only a human-or-agent can author, scored by automation that a human-or-agent cannot fake. Never let one silently replace the other — a wrong placement still parses as valid JSON, and a wrong boolean still passes watertight+volume>0. The solver is what proves the judgment actually fits.

The two layers

  • AGENT layer — mfg/judgment.json (you author this): how the design decomposes into FABRICATED parts vs COTS, the cable/fluid harness, the joints, and each item's PLACEMENT (position + envelope) and SOURCING.
  • AUTOMATION layer — mfg/packaging_solve.py (this scores it): skin containment against the REAL inner ring, envelope COLLISIONS, MASS closure, CG, clearance to moving parts, and RETRIEVAL corridors. Exit 1 on FAIL.

The loop

  1. Author judgment. Edit mfg/judgment.json: list fabricated parts (process + material + est. mass), COTS (vendor PN + mass + pos + envelope + sourcing note), the harness, joints, and access openings. Use real datasheet envelopes — a too-small box that "looks placed" fails the density check.

  2. Score it. uv run mfg/packaging_solve.py. Read mfg/packaging.md.

  3. Fix what's flagged. Each FAIL names the item and the violation:

    • containment → the item pokes out the skin; move it inboard / down. Remember tumblehome: a side box can poke out the TOP corner too.
    • collision → two envelopes intersect; re-place one.
    • mass closure → the fabricated + COTS total is off MTOW; revisit the decomposition or masses.
    • retrieval → a serviceable item isn't reachable through any opening, or a fixed box blocks the pull corridor; clear the channel.
  4. Re-run. Repeat until 0 FAIL. WARN is allowed for honest, documented compromises; FAIL is not.

  5. Verify the boolean, don't trust it. When the layout drives real geometry (cuts, mounts, decks), the build must export the as-built result and an audit must assert its expected bbox/volume/CG — because the kernel can silently no-op a boolean (see GUARDRAILS.md §1).

Read the full file on GitHub · 73 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. 8d ago First seen · 73 lines · 89 tokens per session scan A 9f229fe6ac1d

Subscribe to this mod's changes

manufacturability-loop is a skill published in the GitHub repository JMMonte/agentic-digital-twin (2 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 850 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 2026-08-31.

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