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cell-opc-case-research细胞 OPC 案例研究

Agent Skill

cell-opc-case-research 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。

总安装

2,970

周安装

119

GitHub Stars

1

下载量

962
OpenClaw

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

MIT-0

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:cell-opc-case-research(细胞 OPC 案例研究)
来源仓库:https://github.com/cellinlab/cell-opc-case-research
安装命令:
openclaw skills install cell-opc-case-research
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 cell-opc-case-research

简介

cell-opc-case-research 提供针对 OPC、超个人及创作者 IP 的商业案例研究支持。

  • 适合在内容策略规划或商业分析中快速检索中国及全球相关案例信息。
  • 基于关键词和线索筛选公开资料,侧重中文产出的内容策略方向。
  • 安装命令:openclaw skills install cell-opc-case-research;注意权限范围与维护更新频率。
  • 建议结合具体需求验证信息来源可靠性,避免直接引用未核实的案例数据。

SKILL.md

name
opc-case-research
description
Systematic public-information research for OPC, super-individual, creator IP, and one-person business cases, with Chinese outputs focused on content strategy, IP positioning, channel strategy, business models, timelines, and replicable lessons. Use when Codex needs to research a named person, creator brand, or one-person company case; produce a case brief or structured report; map sources and evidence; compare facts versus inferences; or turn scattered public materials into a reusable research deliverable.
metadata
{"openclaw":{"homepage":"https://github.com/cellinlab/cell-skills/tree/main/skills/opc-case-research"}}

OPC Case Research

Overview

Use this skill to research a specific person, creator brand, or one-person business case as an "OPC / super-individual / creator IP" example.

Default to:

  • public information only
  • Chinese output
  • single-case research
  • emphasis on content strategy, IP positioning, and business model
  • explicit separation of facts, inferences, and unknowns

Quick Start

  1. Confirm the target and scope. If the user did not specify depth, use the standard mode.
  2. Build a base profile and source map before writing conclusions.
  3. Build the timeline before interpreting strategy or causality.
  4. Analyze content system, IP positioning, channels, and business model together.
  5. End with replicability analysis instead of generic praise.

If the request is only a fast initial screen, do not load every reference file. Read only what is needed.

Default Inputs

Treat these as the input contract:

  • Required: target person, brand, or case name
  • Optional: focus areas such as content, IP, business model, channels, key decisions, or methods
  • Optional: depth

- quick: short case brief - standard: structured research output - deep: standard output plus evidence tables, samples, and estimates

  • Optional: time range
  • Optional: comparison target

If the user does not specify otherwise, assume:

  • use public information
  • write in Chinese
  • prioritize content strategy, IP building, and monetization
  • analyze one case at a time
  • include a minimum evidence slice in standard and deep outputs

Workflow

1. Scope the Request

Resolve only the ambiguity that blocks the work. If the target is clearly identifiable, start immediately.

Set the working mode:

  • quick: decide whether the case is worth deeper study
  • standard: produce the default structured case study
  • deep: add evidence tables, sampling, and cautious estimates

2. Build the Base Profile and Source Map

Collect:

  • identity labels
  • platform presence
  • official pages or landing pages
  • visible business entry points
  • likely primary and secondary sources

Prefer source types in this order:

  • A: first-party statements, official pages, original program or event pages
  • B: mainstream media, platform profile pages, databases, partner pages
  • C: reposts, forums, summaries, comments, only for leads

Read references/search-playbook.md when constructing search queries, sampling plans, or source maps.

3. Build the Timeline First

Do not jump straight into opinions. Build an event sequence first.

Minimum expectations:

  • quick: 5+ meaningful nodes
  • standard: 10+ nodes
  • deep: 10-20 nodes plus notes on why each node matters

Track:

  • role shifts
  • platform shifts
  • format shifts
  • commercialization upgrades
  • major public launches or collaborations

4. Analyze the Four Core Layers

Analyze these together, not in isolation:

  1. Identity and positioning
  2. Content system and channel strategy
  3. Business model and monetization structure
  4. Key decisions, turning points, and path evolution

Read references/research-standard.md for the full checklist and evaluation rules.

5. Classify Evidence Carefully

Every important point should be marked as one of:

  • fact
  • inference
  • unknown

When in doubt, downgrade confidence instead of overstating certainty.

Use cautious language for:

  • revenue structure
  • team size
  • conversion assumptions
  • audience profile assumptions
  • operational scale

Read references/evidence-schema.md when building evidence tables or appendices.

6. Build a Minimum Evidence Slice

Even in standard mode, do not leave evidence fully implicit.

Default to a minimum evidence slice with 6-12 rows or bullet-equivalents that support the most important claims across:

  • identity or self-positioning
  • timeline
  • content or IP
  • channels
  • business model

If the user did not ask for tables, the evidence slice can be a compact appendix or a short "evidence snapshot" section instead of a full spreadsheet.

7. Shrink Claims When Public Information Is Thin

When evidence is weak, incomplete, or highly indirect:

  • narrow the scope instead of compensating with confident writing
  • separate confirmed facts, best-effort inferences, and unknowns
  • reduce the depth of business-model claims first
  • keep a to verify next list if the case is still worth researching

A smaller but more reliable output is better than a complete-looking report built on speculation.

8. Produce the Right Deliverable

Choose the smallest deliverable that still answers the user.

For quick, produce:

  • one-line positioning
  • identity tags
  • main platforms
  • visible monetization entry points
  • 3-5 reasons the case matters
  • open questions

For standard, produce:

  • case brief
  • source map summary
  • timeline
  • content and IP analysis
  • channel analysis
  • business model analysis
  • evidence snapshot or minimum evidence slice
  • replicability analysis
  • limitations and unknowns

For deep, add:

  • full evidence table
  • content sampling table
  • business model table
  • estimate disclosures when needed

Read references/report-template.md before drafting a full report. Use the copyable templates in assets/ when the output should become a reusable document or table.

Output Requirements

Always aim for:

  • Chinese writing
  • research tone, not fan tone
  • visible structure
  • evidence awareness
  • at least a small evidence trail for the main claims
  • explicit dates or time ranges when claims depend on time
  • direct linkage between content strategy, channel choice, and business model
  • actionable takeaways for people studying super-individual paths

Hard Rules

Do not:

  • use private or non-public information
  • present unverified claims as facts
  • invent revenue, team, or deal details
  • turn gossip into business analysis
  • hide uncertainty behind confident phrasing

When information is weak, say so clearly and narrow the claim.

Resource Map

- Read for the full SOP, evidence rules, deliverables, quality bar, and uncertainty handling.

- Read for search query patterns, source mapping, verification rules, and sampling.

- Read for field definitions for evidence, timeline, content samples, and business model tables.

- Read when drafting a standard long-form report.

- Use when creating a short case brief.

- Use when creating a full report draft.

- Use when creating the evidence table.

- Use when creating the timeline table.

- Use when creating the content sampling table.

- Use when creating the business model table.

Not for This Skill

This skill is not for:

  • celebrity gossip
  • private intelligence gathering
  • legal, financial, or investment due diligence
  • unsupported claims about real income or private operations

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

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按下载量换算936

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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。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。

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