SKILLEMALL.ai
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Create a reusable prompt file (.prompt.md) for a common task.

The skillemall take

This skill generates a reusable .prompt.md file template. Promises to standardize prompts across different tasks. The code runs 263 tokens with basic structure and no lint errors. Scores are middling: quality at 68, process at 64. No critical findings, nothing remarkable—a routine template generator.

Works across all major platforms from Claude to DeepSeek. Useful if you're writing similar AI assistant instructions repeatedly and tired of copying structure. Otherwise it's an extra layer. Install if you already use .prompt.md in your workflows and want faster template creation.

microsoft/vscode Claude Code author: microsoft MIT 1 file body ≈ 263 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Create a reusable prompt file (.prompt.md) for a common task.

As a process C 64/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorAI and agentstype 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
C
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 64/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 9 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 263 tokens
  • 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)
  • +3Description length 61: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 3 headings
  • +3Step-by-step instructions: 9 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.