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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

60%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./antigravity/skills/prompt-engineering/SKILL.md

The canonical home for this skill is prompt-engineering in NeoLabHQ/context-engineering-kit

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 body is well-sectioned and rich with concrete, reusable prompt examples, but it is a ~560-line monolith that inlines three documents which should be one-level-deep reference files, and it repeatedly explains fundamentals (context windows, few-shot, chain-of-thought) that Claude already knows. It also contains mechanical defects: broken code-fence markers ('````markdown theme={null}'), a stray duplicated section header, and typos ('Usefull').

Suggestions

Split the three major sections into one-level-deep reference files (e.g. references/patterns.md, references/agent-prompting.md, references/persuasion.md) and keep SKILL.md as a lean overview that links to them.

Cut explanations of concepts Claude already knows — the context-window definition paragraph, the input/output phase walkthrough, and generic few-shot/chain-of-thought primers — keeping only the actionable patterns and examples.

Fix the broken code fences ('````markdown theme={null}'), the duplicated headings, and typos ('Usefull') so the document renders correctly.

DimensionReasoningScore

Conciseness

The ~560-line body spends significant tokens explaining concepts Claude already knows — a full paragraph defining 'context window' ('The “context window” refers to the entirety of the amount of text a language model can look back on...'), generic explanations of few-shot learning and chain-of-thought, and a persuasion-psychology rationale section ('LLMs are parahuman: Trained on human text containing these patterns'). This matches the anchor 'Noticeably verbose; several unnecessary explanations or padded sections'; it is above a 1 because the pattern examples and ✅/❌ comparisons do carry non-obvious information.

2 / 5

Actionability

Most guidance is concrete: copy-paste prompt templates (the few-shot extraction example, the code review template with .format() usage, the RAG and validation f-string prompts) and paired ✅/❌ examples for each persuasion principle ('✅ Write code before test? Delete it. Start over. No exceptions.'). It falls short of 5 because several snippets are illustrative pseudocode ('# Process data / # Generate output in specified format') and the persuasion section is more descriptive than instructional; it is above 3 because the pseudocode is explicitly justified as a degrees-of-freedom illustration.

4 / 5

Workflow Clarity

There are sequenced frameworks — the Progressive Disclosure levels 1-4, the instruction hierarchy ('[System Context] → [Task Instruction] → [Examples] → [Input Data] → [Output Format]'), and the Quick Reference five-question checklist — but no end-to-end workflow for actually applying the skill to design or optimize a prompt. The content reads as a topical reference with implicit sequencing, matching the anchor 'Steps listed but... checkpoints missing or implicit'. No validation cap applies since no destructive or batch operations are involved.

3 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/ directories), so the entire body is inline in SKILL.md. Section headers are clear and consistent, but three essentially independent documents (prompt engineering patterns, Anthropic agent prompting practices, persuasion principles) are stitched together with a bare '---' divider and clearly belong in separate reference files. This matches the anchor 'Some structure but could be better organized; content that should be separate is inline'.

3 / 5

Total

12

/

20

Passed

Description

53%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 has strong, explicit trigger guidance and a reasonably distinct niche, but it never states what the skill delivers (prompt engineering patterns and best practices), omits the most natural trigger phrase 'prompt engineering', and is written with second-person voice and a grammar error ('when you writing'). It reads as a trigger list rather than a capability statement.

Suggestions

State the 'what' explicitly in third person, e.g. 'Provides prompt engineering patterns and best practices for designing, testing, and optimizing prompts.', followed by the 'Use when...' trigger clause.

Fix the grammar error ('when you writing' → 'when writing') and remove second-person phrasing to match the third-person convention.

Add missing natural trigger terms users would actually say: 'prompt engineering', 'write better prompts', 'improve a prompt', 'agent prompting'.

DimensionReasoningScore

Specificity

The description lists several concrete artifacts and actions — "writing commands, hooks, skills for Agent, or prompts for sub agents", "optimizing prompts, improving LLM outputs, or designing production prompt templates" — which matches the anchor for several specific actions with gaps (a 4). However it is written in second person ("when you writing commands") and contains a grammatical error, so per the judging guidelines the specificity score is reduced by 1, landing at 3.

3 / 5

Completeness

The 'when' is explicit and specific ("Use this skill when... commands, hooks, skills for Agent, or prompts for sub agents"), but the 'what' is vague: the description never states what the skill actually provides (a library of prompt engineering patterns and best practices). This sits between the 'only when present without what' anchor (2) and 'both what and when present' (4) — the strong when with a weak what puts it at 3, noticeably below the midpoint because the core capability is unstated.

3 / 5

Trigger Term Quality

Relevant keywords are present ("commands", "hooks", "skills", "prompts for sub agents", "prompt templates", "LLM interaction") but common natural variations are missing: the phrase "prompt engineering" itself never appears, nor do synonyms like "write better prompts", "improve a prompt", or "agent prompting". This matches the anchor 'Some relevant keywords but missing common variations or synonyms'.

3 / 5

Distinctiveness Conflict Risk

The prompt-authoring domain (commands, hooks, skills, sub agent prompts) is mostly distinct with only minor overlap risk against closely related skills (e.g., an API-usage or agent-writing skill), matching the anchor 'Mostly distinct; minor overlap risk with closely related skills'. It is not a 5 because 'any other LLM interaction' and 'improving LLM outputs' are broad enough to overlap with general output-quality skills.

4 / 5

Total

13

/

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

antigravity/skills/prompt-engineering/SKILL.md

Reviewed

Table of Contents

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