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what-if-oracle

Run structured What-If scenario analysis with 4–6 branch possibility exploration (best, likely, worst, wild card, contrarian, second-order). Use when the user asks speculative what-if questions about uncertain futures, strategic forks, contingency planning, or stress-testing a decision before committing.

65

Quality

77%

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SecuritybySnyk

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tessl review fix ./skills/what-if-oracle/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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.

A well-structured, actionable analysis framework with a clear phased workflow and a properly signaled reference file. The main weakness is conciseness — philosophical framing and analogies pad the core guidance.

Suggestions

Trim philosophical framing (the 0·IF·1 backstory and 'Nature uses this ratio for branching…') to lean operational guidance.

Add one short fully-worked example applying the branch template to a concrete question, to push actionability toward the top anchor.

Consider moving the domain-specific Golden Ratio weighting rationale and 'What This Is NOT' disambiguation into the reference file to tighten the main body.

DimensionReasoningScore

Conciseness

Mostly efficient, but philosophical padding such as 'the mind's way of simulating futures before committing resources' and the golden-ratio nature analogies ('trees, rivers, blood vessels') could be trimmed.

3 / 5

Actionability

Provides a concrete 6-branch table, a fill-in ASCII analysis template with named fields, and a synthesis format with five named modes — highly actionable, though no fully worked end-to-end example is included.

4 / 5

Workflow Clarity

Clear four-phase sequence (Frame → Map → Analyze → Synthesize) with an explicit user-confirmation checkpoint in Phase 1; not a destructive/batch task so the cap does not apply, but additional validation checkpoints are limited.

4 / 5

Progressive Disclosure

Well-organized sections with a clearly signaled, verified one-level-deep reference (references/scenario-templates.md) listed in a Reference Files table; minor organization gaps as some theoretical framing stays inline.

4 / 5

Total

15

/

20

Passed

Description

87%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.

A strong, specific description that explicitly covers both capability and trigger conditions with natural phrasing. Minor room to add a couple more synonyms, but it is well above the midpoint on every dimension.

DimensionReasoningScore

Specificity

States the concrete action ('Run structured What-If scenario analysis') and enumerates six specific branches (best, likely, worst, wild card, contrarian, second-order), giving several concrete actions with only minor coverage gaps.

4 / 5

Completeness

Clearly answers 'what' (structured What-If scenario analysis with 4–6 branches) and 'when' via an explicit 'Use when…' clause with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Includes natural phrases users would say — 'what-if questions', 'strategic forks', 'contingency planning', 'stress-testing a decision' — with good coverage, though a few synonyms are absent.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (speculative possibility-space analysis) with distinct triggers unlikely to fire for unrelated skills, so conflict risk is minimal.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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