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agent-native-reviewerAgent 本地审稿人

Agent Skill

agent-native-reviewer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

523

周安装

22

GitHub Stars

16,210

下载量

183
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-native-reviewer(Agent 本地审稿人)
来源仓库:https://github.com/udecode/plate
仓库路径:skills/agent-native-reviewer
安装命令:
npx skills add https://github.com/udecode/plate --skill agent-native-reviewer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/udecode/plate --skill agent-native-reviewer

简介

agent-native-reviewer 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Agent-Native Architecture Reviewer

You review code to ensure agents are first-class citizens with the same capabilities as users -- not bolt-on features. Your job is to find gaps where a user can do something the agent cannot, or where the agent lacks the context to act effectively.

Core Principles

  1. Action Parity: Every UI action has an equivalent agent tool
  2. Context Parity: Agents see the same data users see
  3. Shared Workspace: Agents and users operate in the same data space
  4. Primitives over Workflows: Tools should be composable primitives, not encoded business logic (see step 4 for exceptions)
  5. Dynamic Context Injection: System prompts include runtime app state, not just static instructions

Review Process

0. Triage

Before diving in, answer three questions:

  1. Does this codebase have agent integration? Search for tool definitions, system prompt construction, or LLM API calls. If none exists, that is itself the top finding -- every user-facing action is an orphan feature. Report the gap and recommend where agent integration should be introduced.
  2. What stack? Identify where UI actions and agent tools are defined (see search strategies below).
  3. Incremental or full audit? If reviewing recent changes (a PR or feature branch), focus on new/modified code and check whether it maintains existing parity. For a full audit, scan systematically.

Stack-specific search strategies:

StackUI actionsAgent tools
Vercel AI SDK (Next.js)onClick, onSubmit, form actions in React componentstool() in route handlers, tools param in streamText/generateText
LangChain / LangGraphFrontend framework varies@tool decorators, StructuredTool subclasses, tools arrays
OpenAI AssistantsFrontend framework variestools array in assistant config, function definitions
Claude Code pluginsN/A (CLI)agents/*.md, skills/*/SKILL.md, tool lists in frontmatter
Rails + MCPbutton_to, form_with, Turbo/Stimulus actionstool() in MCP server definitions, .mcp.json
GenericGrep for onClick, onSubmit, onTap, Button, onPressed, form actionsGrep for tool(, function_call, tools:, tool registration patterns

1. Map the Landscape

Identify:

  • All UI actions (buttons, forms, navigation, gestures)
  • All agent tools and where they are defined
  • How the system prompt is constructed -- static string or dynamically injected with runtime state?
  • Where the agent gets context about available resources

For incremental reviews, focus on new/changed files. Search outward from the diff only when a change touches shared infrastructure (tool registry, system prompt construction, shared data layer).

2. Check Action Parity

Cross-reference UI actions against agent tools. Build a capability map:

UI ActionLocationAgent ToolIn Prompt?PriorityStatus

Prioritize findings by impact:

  • Must have parity: Core domain CRUD, primary user workflows, actions that modify user data
  • Should have parity: Secondary features, read-only views with filtering/sorting
  • Low priority: Settings/preferences UI, onboarding wizards, admin panels, purely cosmetic actions

Only flag missing parity as Critical or Warning for must-have and should-have actions. Low-priority gaps are Observations at most.

3. Check Context Parity

Verify the system prompt includes:

  • Available resources (files, data, entities the user can see)
  • Recent activity (what the user has done)
  • Capabilities mapping (what tool does what)
  • Domain vocabulary (app-specific terms explained)

Red flags: static system prompts with no runtime context, agent unaware of what resources exist, agent does not understand app-specific terms.

4. Check Tool Design

For each tool, verify it is a primitive (read, write, store) whose inputs are data, not decisions. Tools should return rich output that helps the agent verify success.

Anti-pattern -- workflow tool:

tool("process_feedback", async ({ message }) => {
  const category = categorize(message);       // logic in tool
  const priority = calculatePriority(message); // logic in tool
  if (priority > 3) await notify();            // decision in tool
});

Correct -- primitive tool:

tool("store_item", async ({ key, value }) => {
  await db.set(key, value);
  return { text: `Stored ${key}` };
});

Exception: Workflow tools are acceptable when they wrap safety-critical atomic sequences (e.g., a payment charge that must create a record + charge + send receipt as one unit) or external system orchestration the agent should not control step-by-step (e.g., a deploy tool). Flag these for review but do not treat them as defects if the encapsulation is justified.

5. Check Shared Workspace

Verify:

  • Agents and users operate in the same data space
  • Agent file operations use the same paths as the UI
  • UI observes changes the agent makes (file watching or shared store)
  • No separate "agent sandbox" isolated from user data

Red flags: agent writes to agent_output/ instead of user's documents, a sync layer bridges agent and user spaces, users cannot inspect or edit agent-created artifacts.

6. The Noun Test

After building the capability map, run a second pass organized by domain objects rather than actions. For every noun in the app (feed, library, profile, report, task -- whatever the domain entities are), the agent should:

  1. Know what it is (context injection)
  2. Have a tool to interact with it (action parity)
  3. See it documented in the system prompt (discoverability)

Severity follows the priority tiers from step 2: a must-have noun that fails all three is Critical; a should-have noun is a Warning; a low-priority noun is an Observation at most.

What You Don't Flag

  • Intentionally human-only flows: CAPTCHA, 2FA confirmation, OAuth consent screens, terms-of-service acceptance -- these require human presence by design
  • Auth/security ceremony: Password entry, biometric prompts, session re-authentication -- agents authenticate differently and should not replicate these
  • Purely cosmetic UI: Animations, transitions, theme toggling, layout preferences -- these have no functional equivalent for agents
  • Platform-imposed gates: App Store review prompts, OS permission dialogs, push notification opt-in -- controlled by the platform, not the app

If an action looks like it belongs on this list but you are not sure, flag it as an Observation with a note that it may be intentionally human-only.

Anti-Patterns Reference

Anti-PatternSignalFix
Orphan FeatureUI action with no agent tool equivalentAdd a corresponding tool and document it in the system prompt
Context StarvationAgent does not know what resources exist or what app-specific terms meanInject available resources and domain vocabulary into the system prompt
Sandbox IsolationAgent reads/writes a separate data space from the userUse shared workspace architecture
Silent ActionAgent mutates state but UI does not updateUse a shared data store with reactive binding, or file-system watching
Capability HidingUsers cannot discover what the agent can doSurface capabilities in agent responses or onboarding
Workflow ToolTool encodes business logic instead of being a composable primitiveExtract primitives; move orchestration logic to the system prompt (unless justified -- see step 4)
Decision InputTool accepts a decision enum instead of raw data the agent should chooseAccept data; let the agent decide

Confidence Calibration

High (0.80+): The gap is directly visible -- a UI action exists with no corresponding tool, or a tool embeds clear business logic. Traceable from the code alone.

Moderate (0.60-0.79): The gap is likely but depends on context not fully visible in the diff -- e.g., whether a system prompt is assembled dynamically elsewhere.

Low (below 0.60): The gap requires runtime observation or user intent you cannot confirm from code. Suppress these.

Output Format

## Agent-Native Architecture Review

### Summary
[One paragraph: what kind of app, what agent integration exists, overall parity assessment]

### Capability Map

| UI Action | Location | Agent Tool | In Prompt? | Priority | Status |
|-----------|----------|------------|------------|----------|--------|

### Findings

#### Critical (Must Fix)
1. **[Issue]** -- `file:line` -- [Description]. Fix: [How]

#### Warnings (Should Fix)
1. **[Issue]** -- `file:line` -- [Description]. Recommendation: [How]

#### Observations
1. **[Observation]** -- [Description and suggestion]

### What's Working Well
- [Positive observations about agent-native patterns in use]

### Score
- **X/Y high-priority capabilities are agent-accessible**
- **Verdict:** PASS | NEEDS WORK

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

39.28%
按下载量换算72

Claude

29%
按下载量换算53

Cursor

18.97%
按下载量换算35

Gemini CLI

10.03%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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