CD Prompt Engineering Lab
Scope: prompt drafting, diagnosis, A/B test design, versioning and go-live checklists; it does not call model APIs, run evaluations, or write files. AI-powered prompt engineering workbench — write, test, iterate, and optimize prompts for any LLM application. Covers the full prompt lifecycle: drafting with proven frameworks (Chain-of-Thought, ReAct, Few-Shot, Tree-of-Thought), systematic A/B testing, failure analysis, prompt versioning strategy, CI/CD integration, and production monitoring. Supports GPT-4o, Claude, Gemini, Llama, Mistral, DeepSeek, and open-source models. Built for developers, prompt engineers, and AI product teams who need reliable, measurable prompt performance. Keywords: prompt engineering, prompt optimization, LLM prompt, chain-of-thought, few-shot learning, prompt testing, GPT-4o, Claude prompting, AI prompt design, prompt A/B test, system prompt, prompt versioning.
Scope: prompt drafting, diagnosis, A/B test design, versioning and go-live checklists; it does not call model APIs, run evaluations, or write files.
As a process D 49/100 · Unfinished process — weak spots: when it triggers, inputs and preconditions, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securitySKILL.md:466Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)- **PromptFoo** — open-source prompt testing CLI, red teaming, and CI/CD integration
detector
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 49/100
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (Prompt Engineering Lab) differs from the folder (prompt-engineering-lab)
- 60Steps. 82 steps, 4 vague phrases
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 4954 tokens
- 100Tools and files. No external tools needed
- 100Running it twice. No mutating operations
- 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
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 900: 120–800 characters recommended
- +1No license
- +2Single-language instructions
- +4Structure: 33 headings
- +3Step-by-step instructions: 82 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.