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prompt-engineering

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.

53

Quality

60%

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SecuritybySnyk

Passed

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/prompt-engineering/SKILL.md

The canonical home for this skill is prompt-engineering in administrakt0r/AI-Agents-Safe-Coding-Skills

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 content is well-organized with concrete, usable prompt templates, but it is held back by tutorial-style explanations of concepts Claude already knows and a lack of any file-based progressive disclosure. The vague 'When to Use' closing line adds little workflow guidance.

Suggestions

Cut explanations of concepts Claude already knows (definitions of few-shot learning, chain-of-thought, system prompts) and keep only the actionable templates and 'use when' triggers.

Tighten each capability section to the prompt template/example plus a one-line trigger, removing the surrounding prose.

Replace the generic 'When to Use' line ('applicable to execute the workflow or actions described in the overview') with concrete trigger scenarios that map user requests to specific patterns.

DimensionReasoningScore

Conciseness

The body spends notable space explaining concepts Claude already knows (e.g., 'Teach the model by showing examples instead of explaining rules', what chain-of-thought and system prompts are) in tutorial prose. It is above 1 because the padding is moderate rather than severe, but below 3 because there are several unnecessary explanation passages that should be trimmed.

2 / 5

Actionability

Provides concrete, copy-paste-ready prompt templates for common cases (ticket extraction, bug root-cause, summarization, code review) plus an executable Python template. It is below 5 because these are templates rather than fully realized programs with all variations covered, and above 3 because the guidance is concrete and executable rather than pseudocode.

4 / 5

Workflow Clarity

Loose sequences exist (Progressive Disclosure levels 1-4, the Instruction Hierarchy arrow) but there are no validation checkpoints, and the 'When to Use' section is vague ('applicable to execute the workflow or actions described in the overview'). It is above 2 because sequences are present and coherent, but below 4 because checkpoints are missing and the closing guidance is unhelpful.

3 / 5

Progressive Disclosure

The content is well-sectioned with clear headers, but all ~170 lines are inlined in SKILL.md with no bundle files and no one-level-deep references; the detailed per-pattern examples are content that could plausibly live in separate reference files. It is above 2 because the structure is organized rather than minimal, but below 4 because references are entirely absent and bulk detail is inline.

3 / 5

Total

12

/

20

Passed

Description

70%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 clearly answers both what the skill does and when to use it, with natural trigger phrases and a mostly distinct niche. Its main weakness is generic 'what' phrasing ('Expert guide on... patterns, best practices') that under-specifies the concrete actions the skill performs.

Suggestions

Replace the generic 'Expert guide on... patterns, best practices, and optimization techniques' with concrete actions the skill performs (e.g., 'Generates few-shot examples, composes chain-of-thought prompts, and iteratively optimizes prompts via A/B testing').

Add natural synonyms users might say to broaden trigger coverage (e.g., 'prompt design', 'write better prompts', 'LLM prompting tips').

Tighten 'debug agent behavior' to a more prompt-specific trigger to reduce overlap risk with general agent-debugging skills.

DimensionReasoningScore

Specificity

Names the prompt-engineering domain and a few action categories ('patterns, best practices, and optimization techniques', 'improve prompts, learn prompting strategies, or debug agent behavior'), but the 'what' is described generically rather than as comprehensive concrete actions. It is above a score of 2 because real actions are named, but below 4 because the action list is not specific or comprehensive.

3 / 5

Completeness

Explicitly answers both 'what' (guide on prompt engineering patterns, best practices, optimization techniques) and 'when' ('Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior') with concrete triggers. It is below 5 because the 'what' leans slightly generic/fluffy ('Expert guide on...'), and above 3 because the 'when' is fully explicit rather than weakly implied.

4 / 5

Trigger Term Quality

Contains good natural trigger phrases users would say ('improve prompts', 'learn prompting strategies', 'debug agent behavior', 'prompt engineering'). It is below 5 because synonyms like 'prompt design' or 'better prompts' are missing, and above 3 because coverage is solid rather than minimal.

4 / 5

Distinctiveness Conflict Risk

The prompt-engineering niche is mostly distinct with specific triggers, but 'debug agent behavior' introduces minor overlap risk with general agent/coding skills. It is below 5 due to that overlap risk, and above 3 because the core scope is clearly bounded.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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