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legal-support

Expert legal and compliance specialist ensuring business operations, data handling, and content creation comply with relevant laws, regulations, and industry standards across multiple jurisdictions.

27

Quality

11%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./legal-helper/skills/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Discovery

22%

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

This description reads like a job title or role summary rather than a functional skill description. It lacks concrete actions, specific trigger terms, and any 'Use when...' guidance, making it difficult for Claude to know when to select this skill over others. The broad, buzzword-heavy framing ('expert legal and compliance specialist') adds no actionable information.

Suggestions

Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user asks about legal compliance, regulatory requirements, GDPR, privacy policies, terms of service, or contract review.'

Replace the vague role description with specific concrete actions, e.g., 'Reviews contracts for compliance issues, drafts privacy policies, identifies regulatory requirements, assesses GDPR/CCPA obligations, and audits content for legal risks.'

Include natural user-facing keywords like 'GDPR,' 'privacy policy,' 'terms of service,' 'contract,' 'regulatory compliance,' 'data protection,' and 'legal review' to improve trigger term coverage.

DimensionReasoningScore

Specificity

The description uses vague, abstract language like 'ensuring business operations, data handling, and content creation comply.' It names broad domains but no concrete actions—there's no mention of specific tasks like 'review contracts,' 'draft privacy policies,' or 'audit compliance checklists.'

1 / 3

Completeness

The description partially addresses 'what' (compliance across jurisdictions) but in very vague terms, and completely lacks a 'when' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the weak 'what' brings it to 1.

1 / 3

Trigger Term Quality

It includes some relevant keywords like 'legal,' 'compliance,' 'regulations,' 'jurisdictions,' and 'data handling,' which users might naturally mention. However, it misses common variations like 'GDPR,' 'privacy policy,' 'terms of service,' 'contract review,' 'regulatory,' or specific legal domains.

2 / 3

Distinctiveness Conflict Risk

The legal/compliance domain is somewhat specific, but the extremely broad scope ('business operations, data handling, and content creation across multiple jurisdictions') could overlap with data privacy skills, content moderation skills, business advisory skills, or contract-related skills.

2 / 3

Total

6

/

12

Passed

Implementation

0%

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

This skill is an extremely verbose, largely non-actionable document that reads more like a legal compliance textbook outline than an operational skill for Claude. The code examples are non-functional stubs, the workflows are abstract aspirations rather than concrete procedures, and the entire 400+ line document could be reduced to a fraction of its size while providing more useful guidance. It explains concepts Claude already knows while failing to provide the specific, executable instructions that would actually help with legal compliance tasks.

Suggestions

Replace the non-functional Python classes with either truly executable code or remove them entirely in favor of concise, specific instructions for each compliance task (e.g., 'When reviewing a contract, check for these specific clauses and flag these specific risks').

Reduce the document to under 100 lines by removing the lengthy YAML config, assessment template, and success metrics sections—move these to separate reference files and link to them.

Add concrete validation checkpoints to the workflow, such as 'Before finalizing any privacy policy, verify it includes: [specific checklist items]. If any are missing, add them before proceeding.'

Replace vague bullet points like 'Conduct comprehensive compliance audits' with specific, actionable instructions like 'For GDPR compliance review: 1. Check data processing records exist for each data category 2. Verify retention periods are documented 3. Confirm DPA exists for each processor.'

DimensionReasoningScore

Conciseness

Extremely verbose at 400+ lines. Explains basic legal concepts Claude already knows (e.g., what GDPR articles mean, what user rights are), includes lengthy template sections that are mostly placeholder text, and the Python code examples are largely pseudocode with stub methods that don't execute. The YAML config is a generic reference document, not actionable guidance.

1 / 3

Actionability

Despite containing code blocks, the Python classes are non-functional with numerous undefined methods (check_legal_basis, check_data_categories, add_gdpr_specific_collection_terms, etc.). The workflow steps are vague bullet points ('Monitor regulatory changes', 'Conduct comprehensive compliance audits') rather than concrete, executable instructions. The bash block in Step 1 contains only comments with no actual commands.

1 / 3

Workflow Clarity

The 4-step workflow is entirely abstract with no validation checkpoints, no concrete sequencing, and no feedback loops. Steps like 'Conduct comprehensive compliance audits with gap identification and remediation planning' are aspirational descriptions, not actionable procedures. There are no verification steps for any of the legal review processes described.

1 / 3

Progressive Disclosure

Monolithic wall of text with no references to external files. The massive compliance assessment template, full YAML config, and multiple large Python classes are all inlined. The final line references 'core training' vaguely rather than pointing to specific supplementary documents. Content that should be in separate reference files (templates, code examples, checklists) is all crammed into one document.

1 / 3

Total

4

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (557 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

9

/

11

Passed

Repository
OpenRoster-ai/awesome-openroster
Reviewed

Table of Contents

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