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optimizing-staking-rewards

Compare and optimize staking rewards across validators, protocols, and blockchains with risk assessment. Use when analyzing staking opportunities, comparing validators, calculating staking rewards, or optimizing PoS yields. Trigger with phrases like "optimize staking", "compare staking", "best staking APY", "liquid staking", "validator comparison", "staking rewards", or "ETH staking options".

67

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

65%Weight 40%Scale 1-3

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

The body is actionable with strong executable commands and reasonable structure, but it leans slightly redundant (inline Examples duplicating the Instructions) and lacks explicit validation checkpoints for the batch/financial optimization workflow it drives.

Suggestions

Add an explicit validation step to the optimization workflow (e.g., verify the parsed positions and risk scores before recommending reallocations) to satisfy the feedback-loop requirement for batch/financial operations.

Replace the inline Examples section with a pointer to references/examples.md (or merge them) to remove duplication and ensure every bundle file is reachable from the body.

Remove the hardcoded sample timestamp ("2025-01-15 15:30 UTC") from the Output block or label it as illustrative, since time-sensitive markers penalize conciseness when not in a deprecated/old-patterns section.

DimensionReasoningScore

Conciseness

The body is mostly efficient with executable commands and no concept explanations, but the inline "Examples" section partly duplicates the "Instructions" section and a hardcoded sample timestamp ("2025-01-15 15:30 UTC") adds time-sensitive noise that could be trimmed.

2 / 3

Actionability

Provides fully executable, copy-paste-ready `python ${CLAUDE_SKILL_DIR}/scripts/staking_optimizer.py` commands with concrete flags (--asset, --amount, --optimize, --compare, --format) and clear expected outputs.

3 / 3

Workflow Clarity

Steps are numbered and sequenced, but the workflow lacks validation/verification checkpoints for batch and financial optimization operations, which caps clarity at 2; the Error Handling table mitigates but does not insert an explicit validate-then-proceed loop.

2 / 3

Progressive Disclosure

Sections are organized and reference real one-level-deep files (errors.md, implementation.md) plus external links, but the bundled examples.md is never referenced from the body while a redundant inline Examples section exists, leaving organization slightly suboptimal.

2 / 3

Total

9

/

12

Passed

Description

100%Weight 40%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 is concise, third-person, and clearly states both capabilities and explicit trigger guidance with natural keywords. It distinguishes itself well within a specific crypto-staking niche.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Compare and optimize staking rewards across validators, protocols, and blockchains with risk assessment" — naming the domain scope rather than vague language.

3 / 3

Completeness

Explicitly answers both what (compare/optimize staking rewards with risk assessment) and when ("Use when analyzing staking opportunities, comparing validators, calculating staking rewards, or optimizing PoS yields").

3 / 3

Trigger Term Quality

Provides natural trigger phrases users would actually say ("optimize staking", "best staking APY", "liquid staking", "validator comparison", "staking rewards", "ETH staking options") with good coverage of variations.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (staking reward optimization) with distinct triggers that are unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

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

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
jeremylongshore/claude-code-plugins-plus-skills
Reviewed

Table of Contents

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