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language-injection

LLM Agent 多语言注入规范。在修改 Agent 提示词、添加新的 Agent 端点、处理用户可见的后端消息(message_code)时使用。

71

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

87%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 dense, action-oriented skill body with executable code and a clean architecture map that respects token budget. The only gap is the absence of explicit verification checkpoints in the multi-step new-language workflow.

Suggestions

Add a verification step to the 'Adding a New Language' flow (e.g. 'Confirm the new locale loads in src/i18n and that build_language_instruction returns the expected fragment for the code').

Add a quick check after injection (e.g. assert the lang_suffix is non-empty for non-English Accept-Language) so Claude can self-verify the injection worked.

DimensionReasoningScore

Conciseness

Lean architecture diagram, compact tables, and tight code examples assume Claude's competence; it does not explain what i18n or translation is, so nearly every token earns its place.

3 / 3

Actionability

Provides executable, copy-paste-ready code (route handler injection, inject_language_instruction with marker, message_code/content_code patterns, frontend translateBackend tsx) with specific module paths and signatures.

3 / 3

Workflow Clarity

The 'Adding a New Language' section is a clear 4-step sequence, but neither it nor the main injection flow include explicit validation/verification checkpoints (e.g. confirm new locale loads, confirm injected instruction appears), which keeps it below level 3.

2 / 3

Progressive Disclosure

Well-organized into clear sections with a single clearly-signaled one-level-deep external reference (docs/dev-guides/6-i18n-language-injection.md) at the top; no deeply nested references and no bundle files to verify.

3 / 3

Total

11

/

12

Passed

Description

85%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 concise, third-person description that clearly states both capability and explicit use-conditions, with three concrete actions. It is held back only by slightly narrow trigger-term coverage that omits common i18n/translation phrasings.

Suggestions

Add natural trigger variations a user might say, e.g. '多语言/i18n/翻译/localization/language' alongside the existing Agent-centric terms to broaden trigger coverage.

DimensionReasoningScore

Specificity

Names three concrete actions — '修改 Agent 提示词' (modify Agent prompts), '添加新的 Agent 端点' (add Agent endpoints), '处理用户可见的后端消息' (handle user-visible backend messages) — matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

States what it is ('LLM Agent 多语言注入规范') and gives an explicit 'when' clause ('在...时使用'), so it clearly answers both what AND when.

3 / 3

Trigger Term Quality

Includes relevant developer-facing terms ('Agent 提示词', 'Agent 端点', 'message_code') but omits common variations a user might say such as '多语言'/'i18n'/'翻译'/'language', so it is not the level-3 broad coverage.

2 / 3

Distinctiveness Conflict Risk

Targets a specific niche (Agent prompt language injection with message_code handling) whose triggers are unlikely to overlap with unrelated skills; written in third person with no first/second-person penalty.

3 / 3

Total

11

/

12

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
microsoft/data-formulator
Reviewed

Table of Contents

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