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exam-forecast

Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.

74

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

A well-structured, highly actionable instruction skill with a concrete forecast template and explicit validation checkpoints. Its only weakness is mild verbosity in the framing/prose sections that partly duplicate the workflow.

Suggestions

Collapse the 'Purpose' and 'What this skill does not do' sections into the existing Confidence discipline / Step-4 framing so each idea appears once; the limitations are already implied by the [UNCERTAIN] and thin-sample handling.

Trim the repeated 'forecast, not a prediction' framing — it appears in Purpose, Confidence discipline, and the [UNCERTAIN] block; stating it once in Step 4's template header is sufficient.

Move the detailed intake question bullets under Step 1 into the forecast template's Caveats handling where they already surface, reducing duplication between Step 1 and the output schema.

DimensionReasoningScore

Conciseness

Mostly efficient and free of Claude-already-knows padding, but the Purpose section, 'What this skill does not do' list, and parts of Confidence discipline restate ideas already conveyed elsewhere in the body and could be tightened.

2 / 3

Actionability

Provides a complete copy-paste-ready forecast markdown template with exact headers, tables, and placeholders, plus concrete intake questions and an explicit output file path — fully actionable.

3 / 3

Workflow Clarity

Steps 1–5 are clearly sequenced with explicit checkpoints: thin-sample flagging (<3 exams), sample-confidence tiers, [UNCERTAIN] framing discipline, and a new-professor fallback.

3 / 3

Progressive Disclosure

No bundle files exist or are needed; the body is self-contained and cleanly sectioned with no nested external references, which is appropriate organization for a single-file skill.

3 / 3

Total

11

/

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.

A strong, third-person description that pairs a specific capability list with explicit natural-language triggers. It answers what and when with no padding.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix' and 'forecast likely emphases' — rather than vague abstractions.

3 / 3

Completeness

Explicitly answers both what (analyze past exams to surface patterns and forecast emphases) and when ('Use when the user says…'), satisfying the explicit-trigger requirement.

3 / 3

Trigger Term Quality

Includes natural phrasings a user would actually say: 'what's on the exam', 'analyze past exams', 'predict the exam', plus the 'shares past exams' action trigger.

3 / 3

Distinctiveness Conflict Risk

The same-professor past-exam forecasting niche with these triggers is clearly distinguishable and unlikely to fire for the wrong skill.

3 / 3

Total

12

/

12

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
anthropics/claude-for-legal
Reviewed

Table of Contents

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