← Back to Skills Marketplace
kowl64

Data quality & reconciliation with exception

by KOwl64 · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
4806
Downloads
3
Stars
22
Active Installs
1
Versions
Install in OpenClaw
/install data-reconciliation-exceptions
Description
Reconciles data sources using stable identifiers (Pay Number, driving licence, driver card, and driver qualification card numbers), producing exception reports and “no silent failure” checks. Use when you need weekly matching with explicit reasons for non-joins and mismatches.
Usage Guidance
Before installing, treat the input files and exception reports as sensitive because they may contain pay numbers, names, and driver document identifiers. Provide only the datasets needed for the reconciliation, confirm matching rules and thresholds, and review the exception report before changing any source system.
Capability Analysis
Type: OpenClaw Skill Name: data-reconciliation-exceptions Version: 1.0.0 The skill bundle is benign. The `SKILL.md` clearly outlines a data reconciliation task, including explicit safety instructions such as 'Read-only by default; don’t auto-edit source data' and 'STOP AND ASK THE USER' for clarification, which actively mitigate potential risks. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts against the agent. All files are consistent with the stated purpose of data quality and reconciliation.
Capability Assessment
Purpose & Capability
The artifacts coherently match the stated purpose: reconcile CSV/XLSX datasets using stable identifiers such as Pay Number and driver document numbers, then produce explicit exception categories and reports.
Instruction Scope
The workflow is bounded to deterministic matching, normalization, validation, and exception reporting, and it instructs the agent to stop and ask when columns, identifier priority, or tolerances are unclear.
Install Mechanism
The bundle contains instruction/reference text and a CSV report template only; there is no executable code, package install step, shell command, network call, or service integration.
Credentials
The skill expects potentially sensitive employment or driver-identification data, but that access is purpose-aligned, user-provided, and limited to reconciliation.
Persistence & Privilege
No artifact requests credentials, privileged access, persistent memory, background workers, local profile/session stores, or automatic mutation of source data.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install data-reconciliation-exceptions
  3. After installation, invoke the skill by name or use /data-reconciliation-exceptions
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the data-reconciliation-exceptions skill. - Reconciles multiple data sources using stable identifiers (Pay Number, driver documents). - Produces comprehensive exception reports with explicit reasons for each non-match or mismatch. - Implements “no silent failure” checks—pipelines stop when anomalies or tolerance breaches are detected. - Provides clear input requirements, configurable normalization, and threshold options. - Outputs a detailed CSV report categorizing every record (matched, missing, duplicate, mismatch, invalid).
Metadata
Slug data-reconciliation-exceptions
Version 1.0.0
License
All-time Installs 181
Active Installs 22
Total Versions 1
Frequently Asked Questions

What is Data quality & reconciliation with exception?

Reconciles data sources using stable identifiers (Pay Number, driving licence, driver card, and driver qualification card numbers), producing exception reports and “no silent failure” checks. Use when you need weekly matching with explicit reasons for non-joins and mismatches. It is an AI Agent Skill for Claude Code / OpenClaw, with 4806 downloads so far.

How do I install Data quality & reconciliation with exception?

Run "/install data-reconciliation-exceptions" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Data quality & reconciliation with exception free?

Yes, Data quality & reconciliation with exception is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Data quality & reconciliation with exception support?

Data quality & reconciliation with exception is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Data quality & reconciliation with exception?

It is built and maintained by KOwl64 (@kowl64); the current version is v1.0.0.

💬 Comments