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在 OpenClaw 中安装
/install crm-entity-extraction
功能描述
Standard Operating Procedure (SOP) that bridges extraction logic to CRM append operations via atomic nodes.
使用说明 (SKILL.md)
Lean Philosophy (Principles)
- Kaizen (改善): This workflow relies entirely on discrete, single-responsibility atomic nodes rather than a monolithic loop.
- Standardized Work (Hyojun Sagyo): This node represents a strict, step-by-step Standard Operating Procedure (SOP) for data extraction and persistence.
- Jidoka (自働化): Includes autonomous self-healing loops with hard verification stops between every step.
CRM Entity Extraction SOP
This procedure guides the agent to extract structured data and append it to a CRM spreadsheet using explicitly defined atomic nodes.
Cognitive Directives
WHEN [A business-related email or note containing CRM data is received] THEN [ Follow this strict Standard Operating Procedure:
Step 1: Entity Extraction
- Execute the
LLM-Extract-JSONatomic skill to extract structured entities (name, org, date). - Jidoka Stop: Check if the sub-agent returns a valid JSON object matching the requested schema. IF it returns unstructured text, instruct the skill to format correctly and retry. Do NOT proceed until valid JSON is acquired.
Step 2: Append to CRM
- Execute the
Google Sheets Append Row(or equivalent) atomic node, passing the extracted JSON row. - Jidoka Stop: Verify the atomic node returns a successful JSON confirmation. IF the API request fails, retry up to 3 times with the exact error output. IF it still fails, report the error and STOP. ]
Expected Output
A JSON summary of the extracted data and the successful append confirmation.
安全使用建议
Do not enable this skill until the author clarifies two things: (1) why the 'gog' binary is required and what it does, and (2) how Google Sheets/CRM credentials are supplied and what least-privilege scopes are used. Ask whether the atomic nodes (LLM-Extract-JSON and Google Sheets Append Row) run on a trusted platform and whether error outputs are sanitized. If you must test, run in a sandbox account with limited-sheet permissions and sample data, and require explicit approval for any production credential usage.
功能分析
Type: OpenClaw Skill
Name: crm-entity-extraction
Version: 1.0.4
The skill bundle defines a standard operating procedure for extracting structured data from emails or notes and appending it to a CRM spreadsheet. The instructions in SKILL.md focus on data integrity and verification (Jidoka) using atomic nodes like 'LLM-Extract-JSON' and 'Google Sheets Append Row'. No malicious code, data exfiltration, or prompt injection attempts were identified.
能力评估
Purpose & Capability
The skill claims to extract CRM entities and append rows to Google Sheets (or equivalent), which would normally require access/credentials to the target CRM/Sheets. However the registry metadata lists a required binary 'gog' that is never referenced in the SKILL.md and no environment variables/credentials are declared. The presence of an unexplained binary requirement is disproportionate to the stated purpose.
Instruction Scope
SKILL.md stays within a simple two-step SOP (call an 'LLM-Extract-JSON' atomic node, then a 'Google Sheets Append Row' atomic node) with verification and retry logic. However it is vague about how the source email/note is supplied or accessed and it instructs the agent to include exact error outputs when retrying — which could surface sensitive data if not sanitized. The use of sub-agents/atomic nodes is expected but the data-flow and access boundaries are underspecified.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing will be downloaded or written at install time. That minimizes install-time risk.
Credentials
No environment variables or primary credential are declared even though the procedure requires appending to Google Sheets (which normally needs OAuth/service-account credentials). The skill also demands a named binary ('gog') that has no explained role. Either credentials are handled out-of-band by the platform (possible) or the skill is missing required declarations — this mismatch is concerning.
Persistence & Privilege
The skill does not request 'always: true' and uses the platform default for autonomous invocation. It does not request system-wide persistence in its metadata; autonomy is normal for skills but combine with the other inconsistencies if you need caution.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install crm-entity-extraction - 安装完成后，直接呼叫该 Skill 的名称或使用
/crm-entity-extraction触发 - 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
v1.0.4
CRM Entity Extraction 1.0.4
- Updated documentation in SKILL.md to reflect a shift from workflow-driven to step-by-step Standard Operating Procedure (SOP).
- Emphasized the use of discrete atomic nodes for each subprocess instead of a monolithic loop.
- Clarified Jidoka principles: now require explicit verification stops between every step.
- Improved cognitive directives for more granular error handling and retries.
- No changes to core extraction or append logic; update is limited to procedural clarity and documentation.
v1.0.3
- Introduced explicit Jidoka validation steps for increased reliability.
- Added verification and retry logic for both entity extraction and spreadsheet append steps.
- Improved error handling and reporting instructions for failed operations.
v1.0.2
crm-entity-extraction 1.0.2
- Added "gog" binary as a requirement for the skill.
- Updated workflow to use the native terminal command `gog sheets append` for adding data to the CRM spreadsheet.
- Clarified instructions for appending extracted data using the "gog" command in Cognitive Directives.
- No changes to general functionality or output format.
v1.0.1
- Expanded operating system support from Windows-only to all platforms.
- No changes to functionality or workflow—documentation update only.
v1.0.0
- Initial release of CRM Entity Extraction skill.
- Extracts structured data (persons, organizations, dates) from business emails or notes.
- Appends extracted data as a JSON row to a CRM spreadsheet via Google Sheets.
- Includes autonomous defect detection and clear error reporting if extraction or append fails.
元数据
常见问题
CRM Entity Extraction 是什么？
Standard Operating Procedure (SOP) that bridges extraction logic to CRM append operations via atomic nodes. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 107 次。
如何安装 CRM Entity Extraction？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install crm-entity-extraction」即可一键安装，无需额外配置。
CRM Entity Extraction 是免费的吗？
是的，CRM Entity Extraction 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
CRM Entity Extraction 支持哪些平台？
CRM Entity Extraction 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 CRM Entity Extraction？
由 zvirb（@zvirb）开发并维护，当前版本 v1.0.4。
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