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Agent Skill · 研究检索

parallax(parallax 开发)

parallax 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

parallax 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 14,314。

总安装 8,661周安装 347GitHub Stars 公开资料未说明下载 2,804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-0
版本
1.0.0

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:parallax(parallax 开发)
来源仓库:https://github.com/jcools1977/parallax
安装命令:
openclaw skills install parallax
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install parallax

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。

用于查找、检索和筛选相关信息,适合在 OpenClaw 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。适用于从五个利益相关者角度(用户、开发人员、操作员等)查看决策视角分析。通过 clawhub 安装,结合来源仓库和原始 README 核验具体用法,支持多视角决策分析。

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操作。当前主要用于研究检索类任务,需配合具体决策场景使用。

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 OpenClaw;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 openclaw skills install parallax;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

    它需要需要联网,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

parallax 怎么安装?

在终端执行 openclaw skills install parallax。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

parallax 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

parallax 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

parallax 是免费的吗?

来源标注的许可证是 MIT-0。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。

parallax 用的人多吗?

公开数据是累计安装 8,661 次,近一周安装 347 次,下载 2,804 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。

parallax 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
parallax

parallax 开发 · 本页

8,661—需要联网MIT-0通过

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
parallax
version
1.0.0
description
>
author
J. DeVere Cooley
category
decision-intelligence
tags
metadata
openclaw
emoji
🔭
os
["darwin", "linux", "win32"]
cost
free
requires_api
false
tags

Parallax

"In astronomy, parallax is the apparent shift of an object when viewed from two different positions. The shift reveals depth. Without it, the universe is flat."

What It Does

Parallax forces every significant decision through five simultaneous perspectives before a single line of code is written. Not as a checklist. Not as an afterthought. As the *primary mode of reasoning*.

Most architectural mistakes aren't wrong from every angle. They're wrong from the angle nobody was standing at.

The Five Parallax Lenses

LensPersonaCore QuestionFailure Mode When Ignored
UserThe person touching the interface"Does this feel right?"Feature nobody uses despite being technically sound
MaintainerThe developer reading this code in 6 months"Can I understand and change this?"Code that works but can't evolve
OperatorThe engineer deploying and monitoring this"Can I run this at 3am when it breaks?"System that works in dev, nightmare in prod
AdversaryThe attacker probing for weaknesses"Where does this trust too much?"Vulnerability hiding in a convenient assumption
SponsorThe business funding this work"Does this create or capture value?"Technical excellence that generates zero revenue

How Each Lens Works

Lens 1: The User

The User lens doesn't ask "is the UX good?" — it asks "what story does this interface tell?"

ANALYSIS AXES:
├── Cognitive Load: How many things must the user hold in mind?
├── Error Recovery: When (not if) they make a mistake, what happens?
├── Trust Signal: Does this interaction build or erode confidence?
├── Time Respect: Does this value the user's time or waste it?
└── Accessibility: Can someone with different abilities use this equally?

What it catches: Features that are powerful but unusable. Flows that make sense to the developer but confuse the user. Efficiency optimizations that sacrifice clarity.

Lens 2: The Maintainer

The Maintainer lens asks "what will confuse the next person who reads this?"

ANALYSIS AXES:
├── Naming Clarity: Do names describe actual behavior?
├── Abstraction Depth: How many layers deep must you go to understand?
├── Change Locality: To change this behavior, how many files do you touch?
├── Test Confidence: If I modify this, will the tests tell me if I broke something?
└── Knowledge Required: What unwritten context is needed to work here?

What it catches: Clever code that requires tribal knowledge. Abstractions that obscure rather than clarify. Designs that are optimal for writing but hostile to reading.

Lens 3: The Operator

The Operator lens asks "what happens when this fails at 3am on a holiday weekend?"

ANALYSIS AXES:
├── Observability: Can I see what's happening without reading source code?
├── Failure Modes: Does it fail loudly, quietly, or in a way that looks like success?
├── Recovery Path: Can I fix it without a deploy?
├── Blast Radius: If this fails, what else fails?
└── Resource Behavior: Does it degrade gracefully or cliff-edge?

What it catches: Systems with no logging. Failures that cascade silently. Recovery paths that require the original developer. Memory leaks that only manifest under production load.

Lens 4: The Adversary

The Adversary lens asks "where does this assume good faith?"

ANALYSIS AXES:
├── Trust Boundaries: Where does external input enter?
├── Assumption Surface: What would break if I lied to this system?
├── Privilege Scope: Does this have more access than it needs?
├── Information Leakage: What does the error message reveal?
└── Timing Attacks: Can I learn secrets from how long things take?

What it catches: Input that's validated for format but not intent. Error messages that reveal internal architecture. APIs that trust client-side state. Rate limits that don't exist.

Lens 5: The Sponsor

The Sponsor lens asks "does this advance the mission or just feel productive?"

ANALYSIS AXES:
├── Value Delivery: Does this solve a problem someone will pay for?
├── Opportunity Cost: What are we NOT building while we build this?
├── Time to Value: How long until this generates measurable impact?
├── Reversibility: If this is wrong, how expensive is the course correction?
└── Leverage: Does this multiply future capability or just add linearly?

What it catches: Over-engineered solutions to low-value problems. Refactors that improve code quality but delay features. Infrastructure investments with unclear ROI.

The Parallax Process

INPUT: A proposed change, feature, or architectural decision

STEP 1: SINGLE-PERSPECTIVE PASS
├── Generate the default analysis (whatever perspective comes naturally)
└── Document: which lens did you instinctively use?

STEP 2: FULL PARALLAX
├── Run the remaining four lenses
├── For each lens, generate:
│   ├── Top concern from this perspective
│   ├── Blind spot this lens reveals
│   └── Modification this perspective demands
└── Flag conflicts between lenses

STEP 3: TRIANGULATION
├── Identify where 3+ lenses agree (high confidence)
├── Identify where lenses conflict (design tension)
├── For each conflict:
│   ├── Which lens has priority given the current project phase?
│   ├── Can the tension be resolved or must it be managed?
│   └── What's the least-bad tradeoff?
└── Produce final recommendation with explicit tradeoff map

OUTPUT: Decision with full perspective coverage and documented tradeoffs

Conflict Resolution Matrix

When lenses disagree, priority depends on project phase:

PhasePrimary LensSecondaryRationale
PrototypeSponsor → UserMaintainerValidate value before investing in quality
MVPUser → SponsorAdversaryShip something real, don't ship something dangerous
GrowthOperator → AdversaryMaintainerScale without breaking or being broken into
MaturityMaintainer → OperatorUserLong-term sustainability over short-term features
TurnaroundSponsor → UserOperatorRe-find product-market fit, fast

Output Format

╔══════════════════════════════════════════════════════════════╗
║                    PARALLAX ANALYSIS                        ║
║         Decision: "Add caching layer to user API"           ║
╠══════════════════════════════════════════════════════════════╣
║                                                              ║
║  👤 USER:       Faster responses (+). Stale data risk (-).   ║
║                 → Ensure cache invalidation is immediate     ║
║                   for profile changes.                       ║
║                                                              ║
║  🔧 MAINTAINER: New complexity layer (-). Clear boundary (+) ║
║                 → Cache must be a swappable interface,       ║
║                   not hardcoded to Redis.                    ║
║                                                              ║
║  📟 OPERATOR:   Reduces DB load (+). New failure point (-).  ║
║                 → Need cache hit/miss metrics and            ║
║                   graceful fallback to direct DB.            ║
║                                                              ║
║  🗡️ ADVERSARY:  Cache poisoning vector (-). Rate limit       ║
║                 bypass via cache (-).                        ║
║                 → Cache keys must not be user-controllable.  ║
║                                                              ║
║  💼 SPONSOR:    Reduces infra cost (+). Delays feature X (-) ║
║                 → Worth it only if current p95 latency is    ║
║                   actually causing churn.                    ║
║                                                              ║
║  CONFLICTS:                                                  ║
║  ├── User (freshness) vs Operator (DB load) → TTL tradeoff  ║
║  └── Sponsor (cost) vs Maintainer (complexity) → Phase check ║
║                                                              ║
║  RECOMMENDATION: Proceed with 60s TTL, swappable interface,  ║
║  cache metrics dashboard, and cache-poisoning guards.        ║
║  Defer if p95 latency is under 200ms.                        ║
╚══════════════════════════════════════════════════════════════╝

When to Invoke

  • Before any architectural decision that will be expensive to reverse
  • During design reviews and RFC discussions
  • When a decision "feels right" but you can't articulate why (you're stuck in one lens)
  • When stakeholders disagree (they're each looking through a different lens)
  • Before adding any new dependency, service, or abstraction layer

Why It Matters

The #1 cause of architectural regret isn't choosing the wrong solution. It's choosing a solution that's optimal from one perspective while being catastrophic from another perspective nobody considered.

Parallax doesn't make decisions for you. It makes sure you're making decisions with depth perception.

Zero external dependencies. Zero API calls. Pure multi-perspective reasoning.

平台分布

OpenClaw

89.07%
按下载量换算2,498

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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