AB skill-with-prompt-engineering
A Prompt Engineering assistant based on Gen AI Space's 16-technique framework. Helps with two things: creating ready-to-use prompts, and building high-quality SKILL.md files. Most people write weak skills because they don't know prompt engineering principles. This skill fixes that. Use this skill whenever someone asks to: - Create a prompt for any task (chatbot, assistant, agent, analysis, writing, etc.) - Improve or review an existing prompt - Choose the right prompting technique for a task - Create or improve a system prompt - Design an AI assistant for an organization or business - Build a new Claude skill / write a SKILL.md - "Make Claude always do X" - "Create a skill for..." Primary language: English
As a process B 74/100 · Nearly there — weak spots: inputs and preconditions, running it twice
How to improve
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 74/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 11 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Failures and branches. 7 branches
- 100Tools and files. No external tools needed
- 100Steps. 90 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3884 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 717: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 90 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.