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Install in OpenClaw
/install crm-entity-extraction
Description
Standard Operating Procedure (SOP) that bridges extraction logic to CRM append operations via atomic nodes.
README (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.
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install crm-entity-extraction - After installation, invoke the skill by name or use
/crm-entity-extraction - Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Frequently Asked Questions
What is CRM Entity Extraction?
Standard Operating Procedure (SOP) that bridges extraction logic to CRM append operations via atomic nodes. It is an AI Agent Skill for Claude Code / OpenClaw, with 107 downloads so far.
How do I install CRM Entity Extraction?
Run "/install crm-entity-extraction" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is CRM Entity Extraction free?
Yes, CRM Entity Extraction is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does CRM Entity Extraction support?
CRM Entity Extraction is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created CRM Entity Extraction?
It is built and maintained by zvirb (@zvirb); the current version is v1.0.4.
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