records-hygiene

Detect lifecycle record drift across ADL surfaces and emit structured findings.

4|1|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/danielbaustin/agent-design-language --skill records-hygiene
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: records-hygiene
Source: https://github.com/danielbaustin/agent-design-language/tree/main/adl/tools/skills/records-hygiene
Command: npx skills add https://github.com/danielbaustin/agent-design-language --skill records-hygiene

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Scan ADL lifecycle records for truth drift, report bounded machine-readable findings, and optionally apply narrow safe repairs.

Core Features & Use Cases

This skill provides deterministic drift detection across STP, SIP, SOR, and related workflow evidence, producing structured findings that can drive follow-on improvements and handoffs. It classifies findings by safety/ambiguity, emits evidence, and supports bounded repairs when explicitly allowed without broad repo changes. Use cases include verifying status consistency, identifying placeholder drift, and aligning PR/run evidence with surface targets.

Quick Start

Resolve the concrete target and run the drift analyzer to produce a structured findings report.

Frequently Asked Questions about records-hygiene

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect lifecycle record drift across ADL surfaces like STP, SIP, and SOR?▼

You can detect lifecycle record drift by scanning ADL surfaces like STP, SIP, and SOR against concrete targets such as issues, branches, or worktrees, producing a structured findings artifact with validation data and handoff guidance.

What is the best way to identify placeholder drift and status inconsistencies in workflow evidence?▼

Identifying placeholder drift and status inconsistencies is handled by running a deterministic drift analyzer that classifies findings by safety and ambiguity, emitting evidence to drive follow-on improvements and handoffs.

Can I automatically apply safe repairs when unambiguous workflow drift is detected?▼

Yes, you can apply narrow safe repairs when unambiguous drift is detected by supplying explicit policy controls, allowing mechanical corrections to bounded targets without executing broad repository changes.

What inputs do I need to provide to run an ADL drift analysis on a repository?▼

To run an ADL drift analysis, you must provide inputs for the repository root, target surface, policy controls, and output formats to generate a structured findings artifact containing validation data and handoff guidance.

How does the drift analyzer classify findings to ensure safe mechanical repairs?▼

The drift analyzer classifies findings by safety and ambiguity, ensuring that only unambiguous drift is eligible for bounded mechanical repairs, while ambiguous issues are reported with evidence for manual review.