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claude-api

Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`/`claude_agent_sdk`, or user asks to use Claude API, Anthropic SDKs, or Agent SDK. DO NOT TRIGGER when: code imports `openai`/other AI SDK, general programming, or ML/data-science tasks.

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is claude-api in administrakt0r/AI-Agents-Safe-Coding-Skills

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 router/index skill: concrete model IDs and parameter syntax, a clearly sequenced language-detection and reading workflow with fallback branches, and good task-based navigation to one-level-deep reference files. Its main weaknesses are repetition of the same directives across multiple sections, conversational padding, and reliance on template paths and reference files that cannot be verified from the skill bundle present here.

Suggestions

State the budget_tokens prohibition and the 'always use claude-opus-4-6' default once each (e.g., in Defaults) and reference that section from Thinking & Effort and Common Pitfalls instead of repeating full paragraphs.

Remove conversational asides ('This is non-negotiable', 'we wouldn't mess with you like that') — they add tokens without adding actionable guidance.

Replace {lang} template paths in the Reading Guide with explicit resolved examples (e.g., 'python/claude-api/README.md') or provide an explicit path-resolution note so navigation does not depend on inference.

DimensionReasoningScore

Conciseness

Tables carry dense information efficiently and most content is genuinely non-prior knowledge (new model IDs, adaptive thinking, output_config), but guidance is repeated 3-4 times (the budget_tokens prohibition appears in Defaults, Thinking & Effort, and Common Pitfalls; the 'ALWAYS use claude-opus-4-6' mandate appears in both Defaults and Current Models) and conversational padding exists ('This is non-negotiable', 'we wouldn't mess with you like that'). This matches 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than 4, which would allow only minor trims.

3 / 5

Actionability

Highly concrete: exact model ID strings, exact parameter syntax (thinking: {type: "adaptive"}, output_config: {effort: ...}), the beta header string 'compact-2026-01-12', and a task-keyed reading guide routing to specific files. It falls short of 5 because the body contains no complete executable code (install/quick-start is deferred to referenced files, and no bundle files are present here to verify), leaving minor gaps for the copy-paste-ready standard.

4 / 5

Workflow Clarity

Language detection is a numbered 5-step decision process with explicit fallback branches (ambiguous -> ask the user; can't infer -> AskUserQuestion with listed options; unsupported -> cURL path), followed by a task-to-file reading guide and a surface-selection decision tree. Clear sequence with recovery branches for ambiguity, but no verification checkpoints confirming the chosen reference covers the need, so it sits at 'clear sequence with most checkpoints present; minor validation gaps' rather than 5.

4 / 5

Progressive Disclosure

The body is designed as an overview with well-signaled, one-level-deep references ({lang}/claude-api/README.md, shared/tool-use-concepts.md, shared/error-codes.md, shared/live-sources.md) organized by task need. It falls short of 5 because references use {lang} template paths rather than exact filenames, no bundle files exist alongside SKILL.md to verify the referenced structure, and several detail sections (model pricing, thinking/effort, compaction) carry reference-grade material inline.

4 / 5

Total

15

/

20

Passed

Description

90%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 description: explicit what/when with concrete trigger conditions, exact package import strings, and explicit negative triggers that sharply reduce mis-triggering risk. The only weakness is that the capability statement is a single generic action ("build apps") rather than an enumeration of specific capabilities.

Suggestions

Enumerate 2-3 concrete capabilities in the what-clause (e.g., 'Build apps with the Claude API or Anthropic SDK: tool use, streaming, structured outputs, agents') to raise specificity.

Mention the supported languages (Python, TypeScript, Java, Go, Ruby, C#, PHP) so users of non-Python stacks recognize the skill applies to them.

DimensionReasoningScore

Specificity

"Build apps with the Claude API or Anthropic SDK" names the domain with 1-2 concrete actions but does not enumerate several specific capabilities (e.g., tool use, streaming, batching, agents), matching the 'names domain and 1-2 concrete actions, but not comprehensive' anchor. It is not 4 because no list of several specific actions is present, only a single generic action verb.

3 / 5

Completeness

It explicitly answers what ("Build apps with the Claude API or Anthropic SDK") and when ("TRIGGER when: code imports ... or user asks to use ..."), plus negative triggers ("DO NOT TRIGGER when: code imports openai/other AI SDK"). Both what and when are explicit with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

The description covers both exact import strings users' code will contain ("anthropic", "@anthropic-ai/sdk", "claude_agent_sdk") and the natural phrases a user would say ("asks to use Claude API, Anthropic SDKs, or Agent SDK"). This is comprehensive natural-term coverage including package-level identifiers, matching or exceeding the anchor that lists synonyms and extensions.

5 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (Claude/Anthropic SDK development) and explicitly fences off the highest-conflict neighbors ("DO NOT TRIGGER when: code imports openai/other AI SDK, general programming, or ML/data-science tasks"). Minimal conflict risk with other skills.

5 / 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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills/skills/claude-api/SKILL.md

Reviewed

Table of Contents

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