Identify data quality gaps in knowledge graphs and surface actionable issues.
npx skills add https://github.com/i-richardwang/Dossier --skill reconcile-i-richardwang
Please help me install this Agent Skill. Skill: reconcile Source: https://github.com/i-richardwang/Dossier/tree/main/.claude/skills/reconcile Command: npx skills add https://github.com/i-richardwang/Dossier --skill reconcile-i-richardwang
This Skill performs quality checks on the knowledge graph to identify health-standard violations and guide structured repairs or escalations.
Run the reconciliation on the chosen project to generate a health report and surface first-step corrections.
High-intent search queries and answers about installing and using this skill.
To identify data quality gaps in a knowledge graph, you need a validation process that checks for retrievability, uniqueness, time-consistency, and structured facts. This surfaces discrepancies like disputed or deprecated records as actionable issues.
Validating time_end and is_current relationships involves enforcing unique current records and correct temporal boundaries. A targeted reconciliation workflow surfaces time-consistency violations and provides actionable remediation guidance.
Yes, you can run exhaustive validation checks across an entire project knowledge graph by triggering a full run. This provides comprehensive coverage of all entities and relationships to ensure strict health-standard compliance.
The best way to surface deprecated or draft discrepancies in a knowledge graph is to run a health report generation process. This categorizes data quality violations and guides structured repairs or escalations.
Knowledge graph reconciliation requires no specific external dependencies or components to function. It operates natively to enforce health standards and support decision-making workflows.
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