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prompt-engineering

Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.

Quality

65%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./plugins/customaize-agent/skills/prompt-engineering/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%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.

The skill is rich with actionable, concrete examples but is held back by verbosity — it over-explains fundamentals Claude already knows — and by a monolithic structure that inlines ~560 lines with no progressive file split. Trimming conceptual padding and moving the deeper reference material into separate files would substantially improve it.

Suggestions

Cut or condense explanations of basics Claude already knows (the context-window definition, intros to few-shot/chain-of-thought, the persuasion research preamble) to lift conciseness.

Split the large 'Persuasion Principles' and 'Agent Prompting Best Practices' sections into separate reference files (e.g. references/persuasion.md, references/agent-prompting.md) with one-level-deep links from SKILL.md.

Add an explicit validation/iteration checkpoint to the Prompt Optimization workflow (measure baseline → iterate → re-measure → ship only if improved) to raise workflow clarity.

DimensionReasoningScore

Conciseness

The ~560-line body is noticeably verbose, explaining concepts Claude already knows (a full definition of 'context window', what few-shot and chain-of-thought are, persuasion-psychology research background) — several padded sections that do not earn their token cost.

2 / 5

Actionability

Concrete, mostly copy-pasteable examples throughout — few-shot/CoT markdown prompts, a Python template system, RAG and validation snippets, and ✅/❌ persuasion examples — with only minor gaps where illustrative templates need variables filled.

4 / 5

Workflow Clarity

This is a patterns catalog rather than a sequenced workflow; the Prompt Optimization section gives a rough sequence (start simple, measure, iterate, A/B test) but there are no explicit validation checkpoints or feedback loops.

3 / 5

Progressive Disclosure

Section headers are well organized, but at 560 lines all content is inlined in SKILL.md with no references to separate files, and distinct topics (persuasion principles, agent prompting best practices) that could be split out are not.

3 / 5

Total

12

/

20

Passed

Description

66%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.

The description covers a clear prompt-engineering domain with concrete actions and explicit trigger guidance, but its breadth and second-person phrasing slightly weaken specificity and distinctiveness. A grammar fix and tighter scope would lift it.

Suggestions

Rewrite in third person and fix the grammar slip: e.g. 'Optimizes and designs prompts, commands, hooks, and skills for agents and LLM interactions. Use when the user needs to craft, refine, or template prompts for any LLM.'

Narrow the overly broad 'any other LLM interaction' clause to reduce overlap risk with general coding or writing skills.

Add a few synonym trigger terms (e.g. 'prompt templates', 'system prompts', 'few-shot examples') to push trigger-term coverage toward comprehensive.

DimensionReasoningScore

Specificity

Lists several concrete actions ('writing commands, hooks, skills... optimizing prompts, improving LLM outputs, or designing production prompt templates'), which would anchor at 4, but the second-person voice ('Use this skill when you...') triggers the required specificity penalty of -1.

3 / 5

Completeness

Both 'what' (writing/optimizing/designing prompts and templates) and 'when' ('Use this skill when you writing commands, hooks, skills... or any other LLM interaction') are present with concrete trigger phrases; the 'when' could be slightly more explicit and has a grammar slip ('when you writing').

4 / 5

Trigger Term Quality

Good coverage of natural terms a user would say — 'commands', 'hooks', 'skills', 'prompts', 'optimizing prompts', 'prompt templates' — though a few common synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

It carves out a prompt-engineering niche but the phrase 'any other LLM interaction' makes it broad enough to overlap with many skills that involve prompts.

3 / 5

Total

14

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (560 lines); consider splitting into references/ and linking

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository

NeoLabHQ/context-engineering-kit

Path

plugins/customaize-agent/skills/prompt-engineering/SKILL.md

Reviewed

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