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prompt-engineering

This skill should be used when creating, optimizing, or implementing advanced prompt patterns including few-shot learning, chain-of-thought reasoning, prompt optimization workflows, template systems, and system prompt design. It provides comprehensive frameworks for building production-ready prompts with measurable performance improvements.

48

Quality

60%

Does it follow best practices?

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tessl review fix ./plugins/developer-kit-ai/skills/prompt-engineering/SKILL.md

The canonical home for this skill is giuseppe-trisciuoglio/developer-kit

SKILL.md
Quality
Evals
Security

Quality

Content

35%Scale 1-3

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

This skill suffers from significant verbosity, explaining fundamental prompt engineering concepts that Claude already understands. While it provides structural frameworks and references external files appropriately, the lack of concrete, executable examples and the redundant content (Common Pitfalls appears twice with overlapping content) significantly reduce its utility. The document would benefit from being reduced to 1/3 its current length with actual working prompt examples.

Suggestions

Remove explanations of basic concepts (what few-shot learning is, what CoT means) and assume Claude's competence - focus only on project-specific patterns and preferences

Replace template placeholders with at least 2-3 complete, copy-paste-ready prompt examples showing real inputs and expected outputs

Move detailed framework content to the referenced files and keep SKILL.md as a concise overview with quick-start examples

Add explicit validation steps with concrete criteria (e.g., 'Test prompt with these 3 specific edge cases: [list them]') rather than generic 'validate and test' instructions

DimensionReasoningScore

Conciseness

Extremely verbose with extensive explanations of concepts Claude already knows (what few-shot learning is, what chain-of-thought means, basic prompt engineering concepts). The document is padded with unnecessary context, redundant sections (Common Pitfalls appears twice), and explanatory text that doesn't add actionable value.

1 / 3

Actionability

Provides template structures and frameworks but lacks truly executable examples. The 'Usage Examples' section contains only vague descriptions rather than actual prompts. Templates use placeholders without concrete filled-in examples showing real inputs and outputs.

2 / 3

Workflow Clarity

Workflows are listed with numbered steps but lack validation checkpoints and feedback loops. For example, 'Validate and Test' is mentioned but no specific validation commands or criteria are provided. Missing explicit error recovery steps for when prompts fail.

2 / 3

Progressive Disclosure

References external files (references/few-shot-patterns.md, etc.) appropriately, but the main document is a monolithic wall of text with excessive inline content. Much of the detailed framework content should be in the referenced files rather than duplicated in the overview.

2 / 3

Total

7

/

12

Passed

Description

67%Scale 1-3

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

The description adequately explains when to use the skill and covers the prompt engineering domain, but relies on abstract language ('comprehensive frameworks', 'production-ready') rather than concrete actions. It would benefit from more specific capability statements and additional natural trigger terms users might actually say.

Suggestions

Replace abstract phrases like 'comprehensive frameworks' and 'production-ready prompts' with concrete actions (e.g., 'write few-shot examples', 'structure chain-of-thought prompts', 'design system prompts')

Add common user trigger variations like 'prompt engineering', 'write a prompt', 'improve my prompt', 'LLM prompts', or 'prompting techniques'

DimensionReasoningScore

Specificity

Names the domain (prompt engineering) and lists several techniques (few-shot learning, chain-of-thought reasoning, template systems), but uses abstract language like 'comprehensive frameworks' and 'measurable performance improvements' without concrete actions.

2 / 3

Completeness

Explicitly answers both what ('creating, optimizing, or implementing advanced prompt patterns') and when ('should be used when creating, optimizing, or implementing...') with clear trigger guidance at the start.

3 / 3

Trigger Term Quality

Includes some relevant keywords like 'prompt', 'few-shot learning', 'chain-of-thought', 'system prompt', but misses common user variations like 'write a prompt', 'prompting', 'LLM prompts', or 'prompt engineering'.

2 / 3

Distinctiveness Conflict Risk

Reasonably specific to prompt engineering domain, but phrases like 'template systems' and 'optimization workflows' could overlap with other skills. The focus on prompts provides some distinction but isn't highly unique.

2 / 3

Total

9

/

12

Passed

Validation

90%

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

Validation — 10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

10

/

11

Passed

Repository

fernandezbaptiste/developer-kit

Path

plugins/developer-kit-ai/skills/prompt-engineering/SKILL.md

Reviewed

Table of Contents

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