Agent skill · Backend & API

step-parts

Find, evaluate, and download low-level common standard CAD parts from step.parts, such as screws, bolts, nuts, washers, bearings, standoffs, electronics parts, motors, connectors, and other off-the-shelf components. Use when Codex needs to search the hosted step.parts catalog, resolve fuzzy part names, standards, aliases, or dimensions, choose a matching part, fetch a canonical .step file, verify checksums, or use the step.parts API/OpenAPI/catalog endpoints for standard part discovery.

earthtojake11,498★ · +2,404/wk · 2 repos on radarProfile →
claude-codeships scriptsMIT
Install
npx skills add earthtojake/step.parts --skill step-parts --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 4 KB
Bundled scripts: yes
Path: skills/step-parts/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 320
Language: TypeScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# CAD Parts ## Overview Use the hosted step.parts machine endpoints instead of scraping HTML or relying on local repository files. Treat `https://api.step.parts` as the canonical API origin and `https://www.step.parts` as the site/static-asset origin unless the user provides a different hosted mirror. If the domain does not resolve or the API is unavailable, report that the hosted service is not reachable yet instead of falling back to repo-specific assumptions. ## Quick Workflow 1. Interpret the requested part into search terms and optional facets: - `q` for fuzzy tokens, standards, aliases, dimensions, source/product URLs, and attribute names/values. - `category`, `family`, `standard`, or `tag` when the user gives an exact facet. 2. Search `/v1/parts` and inspect `items`, `total`, and `facets`. 3. If results are ambiguous, present the best few options with `id`, `name`, `standard`, and key attributes before choosing. If one result clearly matches, return the selected record details without downloading unless the user asked for a local STEP file. 4. When the user asks to download or save a STEP file, download its `stepUrl`, then verify the file with the record's `sha256` when pres

What's inside
Steps it walks through
  1. Overview
  2. Quick Workflow
  3. Bundled Downloader
  4. API Reference
  5. Search Guidance
Ships with 3 files
  • agents/openai.yaml
  • references/step-parts-api.md
  • scripts/download_step_part.py
Commands it runs
python skills/step-parts/scripts/download_step_part.py "M3 socket head 12" --download --out-dir /tmp/step-parts
python skills/step-parts/scripts/download_step_part.py --id iso4762_socket_head_cap_screw_m3x12 --download --out-dir /tmp/step-parts
python skills/step-parts/scripts/download_step_part.py "bearing 608zz" --limit 5
About this skill
What does the step-parts skill do?

Find, evaluate, and download low-level common standard CAD parts from step.parts, such as screws, bolts, nuts, washers, bearings, standoffs, electronics parts, motors, connectors, and other off-the-shelf components. Use when Codex needs to search the hosted step.parts catalog, resolve fuzzy part names, standards, aliases, or dimensions, choose a matching part, fetch a canonical .step file, verify checksums, or use the step.parts API/OpenAPI/catalog endpoints for standard part discovery.

How do I install it?

Run `npx skills add earthtojake/step.parts --skill step-parts --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From earthtojake/step.parts, a repository with 320 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going