SKILLEMALL.ai

CD makepad-2.0-splash

CRITICAL: Use for Makepad 2.0 Splash scripting language. Triggers on: splash language, makepad script, script_mod!, makepad scripting, splash 脚本, makepad 2.0 script, mod.state, on_render, script_eval, streaming evaluation, splash syntax, splash vm, let binding, splash functions, hot reload, live reload, ScriptModKey, script_mod_overrides, checkpoint, incremental parsing, canvas splash, POST splash, fn tick, on_audio, set_text, tab switching, 音乐播放器, token monitor, driver script, audio API, 热重载, 脚本引擎, 增量解析

ZhangHanDong/makepad-skills Agent Skills author: ZhangHanDong 4 files body ≈ 5 942 tokens Open the sourcegithub.com↗ analyzed 6 h ago

CRITICAL: Use for Makepad 2.0 Splash scripting language. Triggers on: splash language, makepad script, scriptmod!, makepad scripting, splash 脚本, makepad 2.0…

As a process D 42/100 · Unfinished process — References files that are not bundled: examples/counter/src/app.rs, examples/todo/src/app.rs

GeneratorLearningSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
D
42/100
Unfinished process
References files that are not bundled: examples/counter/src/app.rs, examples/todo/src/app.rs
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

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. 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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 5942 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: examples/counter/src/app.rs
  • warning missing-ref reference to a missing file: examples/todo/src/app.rs

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: examples/counter/src/app.rs, examples/todo/src/app.rs
  • 0Tools and files. 2 referenced file(s) missing: examples/counter/src/app.rs, examples/todo/src/app.rs
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 10 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5942 tokens
  • 85Steps. 47 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 509: enough signal without eating the budget
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (30 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.