evidence-bundle-design

Design evidence bundle JSON files with source snapshots and claim dependencies.

3|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/transreal/claudecode --skill evidence-bundle-design
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: evidence-bundle-design
Source: https://github.com/transreal/claudecode/tree/main/Claude%20Directives/skills/evidence-bundle-design
Command: npx skills add https://github.com/transreal/claudecode --skill evidence-bundle-design

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the auditability and long-term reliability problem of generated artifacts by recording exactly which sources and claims they depend on, then automatically detecting when those dependencies become stale or invalid.

Core Features & Use Cases

  • Evidence Bundle data model: Records BundleId, generated files, source snapshots/spans, and linked claims using lazy claim IDs for scalable references.
  • Deterministic status computation: Computes bundle status with an explicit priority order, including ManualInvalidation overriding snapshot lifecycle outcomes.
  • Centralized storage design: Implements a one bundle = one file layout as bundles/<bundleId>.json for straightforward lookup and lifecycle management.
  • Roadmap alignment: Lays groundwork for Phase 2/3 features like hierarchical aggregation, hash-based stale detection, and contradiction detection.
  • Implementation guardrails: Documents Wolfram/Lang-specific pitfalls (e.g., Unicode escape handling and Map/Return behavior) to reduce subtle failures.

Quick Start

Design an evidence bundle record for a generated output (such as simulation.wl) by populating its sources, snapshot spans, claims, and then computing its status from ManualInvalidation and snapshot lifecycle metadata.

Frequently Asked Questions about evidence-bundle-design

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

FAQPage Schema
How do I track source claims and staleness for generated Mathematica or LaTeX artifacts?▼

You track source claims and staleness by designing an evidence bundle that records source snapshots and claim dependencies for each generated artifact, then computes an audit-ready staleness status. It applies to workflows generating Mathematica, LaTeX, and notebook artifacts.

How do I compute lifecycle status for stale dependency detection in a JSON record?▼

You compute lifecycle status using a deterministic priority resolution scheme that evaluates snapshot lifecycle metadata, where ManualInvalidation overrides snapshot outcomes to detect invalid or stale dependencies within the bundle record.

Does this evidence bundle system use a centralized storage model for audit trails?▼

Yes, the evidence bundle system uses a centralized one-bundle-one-JSON-file storage model, storing records as bundles/<bundleId>.json to provide straightforward lookup and lifecycle management for audit trails.

What Wolfram Language pitfalls should I anticipate when building dependency tracking systems?▼

You should anticipate Unicode escape handling and Map/Return behavior pitfalls in Wolfram Language that can cause subtle failures in dependency tracking systems, which are documented as implementation guardrails to reduce errors.

When do I need hash-based checks and hierarchical aggregation for evidence bundles?▼

You need hash-based checks and hierarchical aggregation for evidence bundles during Phase 2/3 roadmap alignment when scaling staleness detection, contradiction detection, and lifecycle status aggregation across multiple dependency layers.