SKILLEMALL.ai

BB VSCode

Configures, debugs, and speeds up Visual Studio Code: settings scopes, launch.json, tasks.json, extensions, keybindings, formatters, and remote work. Use when a setting has no effect because something else overrides it, when format-on-save runs the wrong formatter or two formatters fight, when a breakpoint stays hollow, F5 does nothing, or a debug config will not attach, when a watch task hangs preLaunchTask forever, when the extension host crashes or two extensions collide, when IntelliSense dies and the TypeScript server or Python interpreter stops resolving, when a keyboard shortcut is swallowed by the terminal, when Remote-SSH, WSL, dev containers, or tunnels misbehave, when startup, search, or file watching is slow, or when deciding what belongs in .vscode/ and which extensions a fork like VSCodium or Cursor can install. Not for language semantics (`typescript`, `py`), Docker image authoring (`docker`), or general bug isolation (`debugging`).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 20 files body ≈ 7 396 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 74/100 · Nearly there — weak spots: inputs and preconditions

ProcedureVS CodeDockerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
B
74/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Result and completion w 14
60
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.
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: 20. 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 ≈ 7396 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 74/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 7396 tokens
  • 100Steps. 43 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 6 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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
  • +3Description length 961: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 43 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill is transparent and VS Code-focused, but it automatically reads, writes, and restructures persistent local memory and shared host/project inventories without asking each time.
LLM: suspicious (high) · 27 Jul 2026