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claude-opus-4-5-guide

Comprehensive guide to Claude Opus 4.5, Anthropic's most intelligent model with effort parameter for reasoning control. Covers model capabilities, benchmarks, effort levels (high/medium/low), hybrid reasoning, and model selection. Use when working with Opus 4.5, optimizing reasoning depth, choosing models, or understanding effort parameter trade-offs.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./.claude/skills/claude-opus-4-5-guide/SKILL.md

The canonical home for this skill is claude-opus-4-5-guide in fernandezbaptiste/Skrillz

SKILL.md
Quality
Evals
Security

Quality

Content

61%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 body is well-organized with executable code and properly signaled reference files that exist in the bundle. Its main weaknesses are marketing-fluff verbosity in the Overview and the absence of an explicit multi-step workflow with checkpoints, which limits workflow clarity for a reference-style skill.

Suggestions

Trim marketing language in the Overview (e.g., "revolutionary", "best model in the world", "model tier reduction") to lean factual statements Claude can act on.

Move the full benchmark and model-spec comparison tables into the existing references, keeping only a compact summary inline to improve token efficiency and progressive disclosure.

Add a short explicit decision flow (e.g., pick model → pick effort level → call API) with a validation note to raise workflow clarity from a reference path to a guided sequence.

DimensionReasoningScore

Conciseness

The Overview is padded with marketing language ("revolutionary", "best model in the world", "state-of-the-art", "model tier reduction") that Claude does not need, though the tables and code sections are mostly efficient.

3 / 5

Actionability

Quick Start provides copy-paste-ready Python with real model IDs and effort-parameter beta flags, plus concrete spec/benchmark tables; minor gaps in TypeScript examples and edge-case coverage.

4 / 5

Workflow Clarity

The guide offers a reasonable When-to-Use → Quick-Start → Key-Features → References navigation path, but it is a reference skill with no multi-step process or validation checkpoints, so sequence clarity is implicit rather than explicit.

3 / 5

Progressive Disclosure

Body is well-structured with clear sections and three real, well-signaled one-level-deep references (effort-parameter-guide.md, model-selection-guide.md, model-capabilities.md) that exist on disk; minor gap is that full benchmark and spec tables are inlined rather than fully delegated to references.

4 / 5

Total

14

/

20

Passed

Description

88%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 is specific, third-person, and answers both what and when with concrete trigger phrases. It is a strong, well-targeted description with only minor gaps in synonym/extension coverage and slight overlap risk on model-selection triggers.

DimensionReasoningScore

Specificity

Lists multiple concrete coverage areas—"model capabilities, benchmarks, effort levels (high/medium/low), hybrid reasoning, and model selection"—giving comprehensive, specific scope rather than vague language.

5 / 5

Completeness

Explicitly states what ("Comprehensive guide... Covers...") and when ("Use when working with Opus 4.5, optimizing reasoning depth, choosing models..."), with concrete trigger phrases in third person.

5 / 5

Trigger Term Quality

Includes natural trigger phrases ("working with Opus 4.5", "optimizing reasoning depth", "choosing models", "effort parameter trade-offs") but omits some synonyms and concrete identifiers like model IDs or "Claude API".

4 / 5

Distinctiveness Conflict Risk

Clearly scoped to the Opus 4.5 niche with distinct triggers, though "choosing models" creates minor overlap risk with broader model-selection skills.

4 / 5

Total

18

/

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

relative_links

Relative link issues: 3 suspicious

Warning

Total

15

/

16

Passed

Repository
fernandezbaptiste/Skrillz
Reviewed

Table of Contents

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