CtrlK
BlogDocsLog inGet started
Tessl Logo

prompt-engineering-patterns

This skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot prompting", or wants to apply advanced prompt engineering patterns for production LLM applications.

60

Quality

71%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/llm-application-dev/skills/prompt-engineering-patterns/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized, token-efficient overview with a solid executable Quick Start and clean one-level progressive disclosure. It is held back by descriptive capability lists that lack concrete code and by missing validation checkpoints in the optimization workflow.

Suggestions

Add a short executable snippet or a concrete command/link for at least 2-3 Core Capabilities (e.g. a few-shot example selection call, a CoT self-consistency snippet) instead of bullet descriptions.

Add an explicit numbered optimization workflow with a validate→fix→retry checkpoint, or link to scripts/optimize-prompt.py as the executable path.

Link the remaining bundle files from the body (chain-of-thought.md, few-shot-learning.md, assets/few-shot-examples.json, scripts/optimize-prompt.py) so all references are signaled one level deep.

DimensionReasoningScore

Conciseness

The body is mostly terse bullet lists and one code block with no padded explanations of concepts Claude already knows; minor trimming possible in Best Practices / Common Pitfalls / Success Metrics, which keeps it just below lean-and-efficient.

4 / 5

Actionability

The Quick Start is a complete, executable code block, but the six Core Capabilities sections and supporting lists are descriptive ('Example selection strategies', 'A/B testing prompt variations') with no executable guidance, leaving key details missing.

3 / 5

Workflow Clarity

The Quick Start gives a coherent sequence and Prompt Optimization hints at an iterative workflow, but there are no explicit validation checkpoints or a validate→fix→retry loop for the optimization process.

3 / 5

Progressive Disclosure

SKILL.md is a clear overview with a verified one-level-deep pointer to references/details.md that does not re-nest; however only details.md is signaled from the body while other reference files, the script, and assets go unmentioned.

4 / 5

Total

14

/

20

Passed

Description

81%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, trigger-rich description with excellent natural phrasing and clear distinctiveness. Its main weakness is that the 'what' stays abstract — it enumerates when-to-use scenarios more concretely than the actual capabilities.

Suggestions

Lead with one concrete capability sentence naming specific actions (e.g. 'Designs, optimizes, and debugs prompt templates with chain-of-thought, few-shot, and structured-output patterns') before the trigger list.

Keep the strong trigger phrase list; it is the description's best feature.

DimensionReasoningScore

Specificity

Trigger phrases are concrete, but the only stated capability is the abstract 'apply advanced prompt engineering patterns for production LLM applications' — names the domain with limited explicit actions rather than comprehensive concrete ones.

3 / 5

Completeness

Both 'what' (apply advanced prompt engineering patterns) and 'when' (explicit 'when the user asks to...' trigger list) are present; 'when' is concrete but 'what' stays somewhat abstract, so it falls short of the anchor-5 bar.

4 / 5

Trigger Term Quality

Comprehensive natural phrasings with synonyms are present — 'optimize a prompt', 'improve prompt performance', 'design a prompt template', 'write better prompts', 'debug prompt issues', 'use chain-of-thought', 'few-shot prompting'.

5 / 5

Distinctiveness Conflict Risk

'Prompt engineering' with distinct triggers (chain-of-thought, few-shot, structured prompting) carves a clear niche with minimal overlap risk against unrelated skills.

5 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
wshobson/agents
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.