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Agent Skill · 研究检索

strangers-eye(陌生人的眼睛)

strangers-eye 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。

strangers-eye 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 61,288。

总安装 353周安装 15GitHub Stars 公开资料未说明下载 124核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:strangers-eye(陌生人的眼睛)
来源仓库:https://github.com/pentaxis93/aiandi
仓库路径:skills/strangers-eye
安装命令:
npx skills add pentaxis93/aiandi --skill "strangers-eye"
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。

AgentSkills.tonpx skills
npx skills add pentaxis93/aiandi --skill "strangers-eye"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

strangers-eye 用于查找、检索和筛选相关信息,适合在多平台环境中快速定位内容。支持基于关键词或任务场景进行信息组织与筛选。通过 npx 命令从 GitHub 安装,建议查阅原始文档了解细节。使用前需确认权限、维护状态及是否触发联网或命令执行。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/strangers-eye

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add pentaxis93/aiandi --skill "strangers-eye";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

strangers-eye 怎么安装?

在终端执行 npx skills add pentaxis93/aiandi --skill "strangers-eye"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

strangers-eye 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

strangers-eye 需要什么权限?

权限级别是调用外部服务。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。

strangers-eye 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

strangers-eye 用的人多吗?

公开数据是累计安装 353 次,近一周安装 15 次,下载 124 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

strangers-eye 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
strangers-eye

陌生人的眼睛 · 本页

353—调用外部服务MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
strangers-eye
description
Multi-persona documentation review that catches quality failures AND signal mismatches. Produces prioritized edits, not assessment. Quality before signals.

Strangers-Eye: Multi-Persona Documentation Review

See what strangers see. Catch what makes them leave.

When to Use This Skill

  • Before publishing documentation (README, guides, landing pages)
  • When documentation "feels off" but you can't articulate why
  • After major rewrites to verify clarity
  • When documentation serves multiple audiences with different intended relationships

The Core Insight

Documentation fails in two distinct ways:

  1. Quality failures - Readers leave because the writing is incoherent, confusing, or trust-breaking. They never receive any signal at all.
  1. Signal mismatches - Readers receive the wrong relationship signal (welcomed when they should be warned, redirected when they should be welcomed).

Quality failures are MORE urgent. Signal calibration on a broken foundation is meaningless.

The Three Relationships

Every documentation has an intended relationship with each audience segment:

RelationshipIntentSuccess Looks Like
WELCOME"This is for you, come in"Reader feels invited, sees value, wants to engage
WARN"This might not be for you, proceed with awareness"Reader understands the tradeoff, can make informed choice
REDIRECT"This isn't for you, here's where you should go"Reader quickly knows this isn't their path

Critical: A negative reaction from a REDIRECT persona isn't a problem. It's success - the signal worked. Only signal MISMATCHES require edits.


The Five-Phase Process

Phase 1: Intent Mapping

Before any personas exist, establish intended relationships.

Agent action: Infer from the documentation what relationship is intended with each audience segment. Present mapping for user approval.

Output format:

Intent Mapping (Proposed)

| Audience Segment | Intended Relationship | Rationale |
|------------------|----------------------|-----------|
| [Segment 1]      | WELCOME / WARN / REDIRECT | [Why] |
| [Segment 2]      | WELCOME / WARN / REDIRECT | [Why] |
| ...              | ...                  | ...       |

Does this capture your intent? (User can adjust before proceeding)

User gate: Do not proceed until user approves or adjusts the mapping.


Phase 2: Dimensional Analysis

Determine which dimensions are relevant for THIS documentation.

Possible dimensions (not exhaustive - emerge from material):

  • Technical literacy (beginner → expert)
  • Philosophical openness (resistant → seeking)
  • Role (evaluator → end-user → contributor)
  • Arrival context (stumbled upon → intentionally sought)
  • Domain expertise (specific to the field)
  • Time investment (quick scan → deep read)

Agent action: Define the dimensional space that meaningfully differentiates how readers will experience this documentation.

Output format:

Dimensional Space

1. [Dimension name]: [Low end] → [High end]
   Why relevant: [Brief rationale]

2. [Dimension name]: [Low end] → [High end]
   Why relevant: [Brief rationale]

...

No user gate. Agent proceeds after defining dimensions.


Phase 3: Persona Construction

Construct exactly the personas needed to cover the dimensional space and test all intended signal paths.

Each persona includes:

  • Name (memorable, descriptive)
  • Dimensional coordinates (position on each axis)
  • Intended relationship (from Phase 1 mapping)
  • Quality lens (what would make them leave due to confusion?)
  • Signal lens (what relationship would they perceive?)

Output format:

Constructed Personas

1. [Name] - [Brief archetype]
   Coordinates: [Dim1: value], [Dim2: value], ...
   Intended signal: [WELCOME/WARN/REDIRECT]
   Quality vulnerabilities: [What confuses this persona?]
   Signal sensitivities: [What signals resonate or repel?]

2. ...

No user gate. Agent proceeds after constructing personas.


Phase 4: Independent Reviews

Each persona reviews the documentation. No cross-contamination between reviews.

Each review assesses TWO dimensions:

A. Quality Assessment (Always first)

Questions the persona asks:

  • Does the opening make sense? Would I keep reading?
  • Are sentences clear and logical?
  • Do I trust this author's competence?
  • Is the value proposition communicated?
  • Are there passages that simply don't work?

Quality failures are flagged regardless of intended signal. Incoherent writing fails for ALL audiences.

A persona can report: "I would leave at line X because [quality reason]" - this terminates their review. They never got far enough for signal assessment.

B. Signal Assessment (Only if quality permits)

Questions the persona asks:

  • What signal did I receive? (WELCOMED / WARNED / REDIRECTED / CONFUSED)
  • Does this match the intended signal for my segment?
  • If mismatch: what specific content caused the wrong signal?

Working signals generate no edits. A REDIRECT persona who feels redirected is success, not a problem.

Output format (per persona):

Review: [Persona Name]

QUALITY ASSESSMENT:
- Opening: [Clear/Confusing] - [Specifics if problematic]
- Trust: [Intact/Damaged] - [Specifics if problematic]  
- Clarity: [Passages that don't work, if any]
- Would continue reading: [Yes/No at line X]

[If quality permits continuing:]
SIGNAL ASSESSMENT:
- Signal received: [WELCOMED/WARNED/REDIRECTED/CONFUSED]
- Signal intended: [From Phase 1]
- Match: [Yes/No]
- [If mismatch: specific content that sent wrong signal]

No user gate. Agent completes all persona reviews.


Phase 5: Synthesis into Edits

Consolidate findings into prioritized edits.

Priority ordering:

  1. QUALITY FAILURES (P1) - Incoherent, confusing, trust-breaking content

- These block everything. Fix first. - Flagged regardless of intended signal category.

  1. SIGNAL MISMATCHES (P2) - Wrong relationship communicated

- Only relevant once quality is sound. - Working redirects generate NO edits.

Output format:

Suggested Edits (Prioritized)

## Priority 1: Quality Failures

### Edit 1.1: [Location/Line]
Problem: [What fails]
Personas affected: [Who caught this]
Suggested fix: [Concrete recommendation]

### Edit 1.2: ...

## Priority 2: Signal Mismatches

### Edit 2.1: [Location/Line]
Problem: [Signal sent vs intended]
Personas affected: [Who experienced mismatch]
Suggested fix: [Concrete recommendation]

### Edit 2.2: ...

---

Summary: [X] quality edits, [Y] signal edits
Document assessment: [Poor/Decent/Excellent]

Output volume scales to document quality:

  • Poor document: many edits (quality + signal)
  • Decent document: few edits (signal only)
  • Excellent document: "No changes recommended"

Example Invocation

/strangers-eye README.md

Phase 1: Agent presents intent mapping, user approves Phase 2-4: Agent executes independently Phase 5: User receives prioritized edits


Critical Distinctions

Quality vs Signal

AspectQuality FailureSignal Mismatch
What happensReader leaves confusedReader receives wrong relationship
PriorityP1 (fix first)P2 (fix after quality)
AffectsAll audiencesSpecific audience segments
ExampleGrammatically ambiguous taglineTechnical jargon alienating beginners

Working Redirect vs Failed Redirect

OutcomeIs This a Problem?
REDIRECT persona feels unwelcomeNo - signal worked
REDIRECT persona feels confusedYes - quality failure
WELCOME persona feels redirectedYes - signal mismatch

Anti-Patterns

Quality-Blind Signal Assessment

Assessing whether audiences feel welcomed/warned/redirected without first checking if they'd even finish reading. Fix quality first.

Treating All Negative Reactions as Problems

A REDIRECT persona having a negative reaction is SUCCESS. The signal worked. Only mismatches need fixing.

Assessment Narration in Output

Output is EDITS, not assessment tables. The synthesis phase produces actionable recommendations, not persona monologues.

Predefined Persona Libraries

Personas are bespoke to each documentation. The dimensional space emerges from the material.


Integration Notes

Complements aiandi-docs skill: That skill provides writing guidelines. This skill provides review methodology. Use strangers-eye to verify documentation meets aiandi-docs standards.

Minimal orchestration required: Only Phase 1 (intent mapping) requires user input. Phases 2-4 execute independently. Phase 5 delivers results.


The Compassion Frame (Invisible in Output)

The goal isn't documentation that pleases everyone. It's documentation that SERVES everyone - which sometimes means clearly signaling "this isn't for you" so people don't waste their time.

Honest signaling serves readers better than accommodation. Making a reader comfortable by hiding what we are isn't kindness - it's deception.

This frame shapes methodology. It does not appear in output.


*May this skill see what strangers see - including what makes them leave before they've read enough to receive any signal at all.*

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cline

3.77%
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安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

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。目前只有一个公开来源,建议同时核对源仓库。

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