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Extruct List Building Skill

作者 zkid18 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install extruct-list-building
功能描述
Build targeted company lists for outbound campaigns using Extruct. Use when the user wants to: (1) find companies matching an ICP, (2) build a prospect or ou...
使用说明 (SKILL.md)

List Building

Build company lists using Extruct, guided by a decision tree. Reads from the company context file for ICP and seed companies.

Extruct API Operations

This skill delegates all Extruct API calls to the extruct-api skill.

For all Extruct API operations, read and follow the instructions in skills/extruct-api/SKILL.md.

All company search, lookalike search, deep search, table creation, row uploads, and enrichment runs are handled by the extruct-api skill. This skill focuses on what to search for and why — the extruct-api skill handles the how.

Decision Tree

Before running any queries, determine the right approach:

Have a seed company from win cases or context file?
  YES → Lookalike Search (pass seed domain)
  NO  ↓

New vertical, need broad exploration?
  YES → Semantic Search (3-5 queries from different angles)
  NO  ↓

Need qualification against specific criteria?
  YES → Deep Search (criteria-scored async research)
  NO  ↓

Need maximum coverage?
  YES → Combine Search + Deep Search (~15% overlap expected)

Before You Start

Read the company context file if it exists:

claude-code-gtm/context/{company}_context.md

Extract:

  • ICP profiles — for query design and filters
  • Win cases — for seed companies in lookalike mode
  • DNC list — domains to exclude from results. If no DNC list exists in the context file, ask the user: (1) run an Extruct search for competitors to auto-populate, (2) accept a CSV of existing customers/partners, or (3) skip for now

Also check for a hypothesis set at claude-code-gtm/context/{vertical-slug}/hypothesis_set.md. If it exists, use the Search angle field from each hypothesis to design search queries — these are pre-defined query suggestions tailored to each pain point.

Method 1: Lookalike Search

Use when you have a seed company (from win cases, existing customers, or user input). Delegate to the extruct-api skill to run a lookalike search with the seed domain.

When to use:

  • You have a happy customer and want more like them
  • Context file has win cases with domains
  • User says "find companies similar to X"

Tips:

  • Run multiple lookalike searches with different seed companies for broader coverage
  • Combine with filters to constrain geography or size
  • Deduplicate across runs by domain

Method 2: Semantic Search — Fast, Broad

Delegate to the extruct-api skill to run semantic company search queries.

Query strategy:

  • Write 3-5 queries per campaign, each from a different angle on the same ICP
  • Describe the product/use case, not the company type
  • Deduplicate across queries by domain — overlap is expected
  • Target 200-800 companies total across all queries

Method 3: Deep Search — Deep, Qualified

Delegate to the extruct-api skill to create and run deep search tasks.

Query strategy:

  • Write queries like a job description — 2-3 sentences describing the ideal company
  • Use criteria to auto-qualify — each company gets graded 1-5 per criterion
  • Default 50 results for first pass; expand after quality review
  • Use up to 5 criteria per task; keep criteria focused and non-overlapping
  • Run separate tasks for different ICP segments

Upload to Table

After collecting results, delegate to the extruct-api skill to create a company table and upload domains. Extruct auto-enriches each domain with a Company Profile.

Re-run After Enrichment

After the list-enrichment skill adds data points to this list, consider re-running list building using enrichment insights as Deep Search criteria. For example:

  • If enrichment reveals that "companies using legacy ERP" are the best fit, create a Deep Search task with that as a criterion
  • If enrichment shows a geographic cluster, run a Search with tighter geo filters
  • This creates a feedback loop: list → enrich → learn → refine list

Result Size Guidance

Campaign stage Target list size Method
Exploration 50-100 Search (2-3 queries)
First campaign 200-500 Search (5 queries) + Deep Search
Scaling 500-2000 Deep Search (high result count) + multiple Search

Workflow

  1. Read context file for ICP, seed companies, and DNC list
  2. Follow the decision tree to pick the right method
  3. Draft queries (3-5 for Search, 1-2 for Deep Search)
  4. Delegate to the extruct-api skill to run queries and collect results
  5. Deduplicate across all results by domain
  6. Remove DNC domains
  7. Delegate to the extruct-api skill to upload to a company table
  8. Add agent columns if user needs custom research
  9. Ask user for preferred output: Extruct table link, local CSV, or both
安全使用建议
This skill is mostly a query-design and orchestration guide that delegates all API calls to an extruct-api skill. Before installing or enabling it: (1) Verify you have the extruct-api skill available and that its SKILL.md and metadata are from a trusted source—this skill implicitly depends on it but does not declare that dependency. (2) Review the extruct-api skill for required credentials and network endpoints, because those credentials will be used to run searches/enrichments. (3) Confirm the workspace paths referenced (claude-code-gtm/context/...) only contain data you want the agent to read; the skill instructs the agent to read those files but does not list them as required config paths. (4) If you cannot inspect the extruct-api skill or confirm provenance, do not enable autonomous agent invocation for this skill; require explicit user approval for any actions that run queries or upload tables. If the extruct-api dependency and provenance are provided and valid, this skill would be coherent and lower risk.
功能分析
Type: OpenClaw Skill Name: extruct-list-building Version: 1.0.0 The skill bundle provides instructions for an AI agent to automate company research and lead generation using the Extruct API. It defines a logical workflow for searching, filtering, and deduplicating company data based on local context files (e.g., ICP profiles and DNC lists) located in the 'claude-code-gtm/context/' directory. No malicious code, data exfiltration of sensitive system files, or harmful prompt injection attempts were found.
能力评估
Purpose & Capability
The skill's described purpose (build company lists via Extruct) matches the instructions: all API calls are delegated to an extruct-api skill and the SKILL focuses on query design and workflows. HOWEVER the skill does not declare any dependency on the extruct-api skill in its metadata or requirements even though it repeatedly instructs the agent to call that skill and to read its SKILL.md. The implicit dependency should be declared so users can verify the other skill.
Instruction Scope
The SKILL.md explicitly instructs the agent to read local context files at claude-code-gtm/context/{company}_context.md and claude-code-gtm/context/{vertical-slug}/hypothesis_set.md. Reading workspace context files is reasonable for building lists, but the skill does not declare these config paths in its manifest. Confirm that the agent's workspace contains only intended files and that the agent is allowed to access them. There are no instructions to access unrelated system paths, credentials, or external endpoints beyond delegating to extruct-api.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, which minimizes installation risk.
Credentials
The skill requests no environment variables, credentials, or config paths. That is proportionate to an orchestration/decision skill that delegates actual API access to another skill. However, because it delegates all Extruct API calls, any credential needs will be handled by the extruct-api skill—review that skill before trusting end-to-end behavior.
Persistence & Privilege
The skill does not request always:true nor request persistent system changes. It is user-invocable and uses normal agent invocation.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install extruct-list-building
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /extruct-list-building 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the list-building skill for creating targeted company lists using Extruct. - Guides users through a decision tree to select the best approach: lookalike search, semantic search, or deep search. - Reads ICP, win cases (seed companies) from the company context file to inform searches. - Integrates with the extruct-api skill to handle all API operations and data uploads. - Supports context-aware query design, deduplication, and fit-based filtering for high-quality outbound lists. - Provides clear workflow steps and guidance for use at different campaign stages.
元数据
Slug extruct-list-building
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Extruct List Building Skill 是什么?

Build targeted company lists for outbound campaigns using Extruct. Use when the user wants to: (1) find companies matching an ICP, (2) build a prospect or ou... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 75 次。

如何安装 Extruct List Building Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install extruct-list-building」即可一键安装,无需额外配置。

Extruct List Building Skill 是免费的吗?

是的,Extruct List Building Skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Extruct List Building Skill 支持哪些平台?

Extruct List Building Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Extruct List Building Skill?

由 zkid18(@zkid18)开发并维护,当前版本 v1.0.0。

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