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BD course-style

The shared visual and writing reference for AI Engineering from Scratch pages, figures, and manuals. Use it for light and dark colour tokens, font stacks, FIG_ label formats, and card layout. Use it for the plain technical English rules and the accessibility and reduced motion defaults. Trigger phrases: "course style", "blueprint palette", "course tokens", "FIG label", "plain technical English", "check my prose", "course fonts", "dark mode tokens"

rohitg00/ai-engineering-from-scratch Agent Skills author: rohitg00 MIT 6 files body ≈ 1 406 tokens Open the sourcegithub.com↗ analyzed 5 d ago

The shared visual and writing reference for AI Engineering from Scratch pages, figures, and manuals.

As a process D 36/100 · Unfinished process — References files that are not bundled: scripts/audit_manuals.js

GeneratorDesignWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
D
36/100
Unfinished process
References files that are not bundled: scripts/audit_manuals.js
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: course-style (rohitg00/ai-engineering-from-scratch)

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/audit_manuals.js

Process rating: all ten parameters 36/100

Will not run. References files that are not bundled: scripts/audit_manuals.js
  • 0Tools and files. 1 referenced file(s) missing: scripts/audit_manuals.js
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 100Steps. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1406 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 451: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 60 items
  • +4Reference files are cited in the instructions (5 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.