verify

Verify BDD scenarios against running system behavior and update the knowledge graph.

Updated Apr 8, 2026
One-click install
npx skills add https://github.com/look-itsaxiom/claudity-assurance --skill verify-look-itsaxiom
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: verify
Source: https://github.com/look-itsaxiom/claudity-assurance/tree/main/skills/verify
Command: npx skills add https://github.com/look-itsaxiom/claudity-assurance --skill verify-look-itsaxiom

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

QA teams often struggle to confirm that written BDD scenarios faithfully reflect runtime system behavior without peering into implementation details. This skill ensures that verification operates purely against observable behavior, reducing bias and drift.

Core Features & Use Cases

  • Ingest new BDD files from bdds/ and parse YAML frontmatter for area, tags, and notes
  • Plan and execute verification using the configured interaction surface, collect evidence, and update the knowledge graph
  • Run regression checks across related areas to detect regressions and ensure stability

Quick Start

Drop new .feature.md files into bdds/ and ask the agent to verify them.

Frequently Asked Questions about verify

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

FAQPage Schema
How do I verify BDD scenarios against a live system?

You can verify BDD scenarios by dropping .feature.md files into the bdds/ directory, which the agent ingests to parse YAML frontmatter, plan verification, execute steps via the interaction surface, and collect behavioral evidence.

What is black-box verification for BDD feature files?

Black-box BDD verification confirms that written scenarios faithfully reflect runtime system behavior by observing external interactions only, reducing implementation bias and drift without requiring access to internal code details.

How do I run regression checks across related BDD areas?

Regression checks across related BDD areas involve ingesting scenarios, planning verification, executing steps through the configured interaction surface, and updating the knowledge graph to detect regressions and ensure system stability.

Does BDD verification update a knowledge graph with test evidence?

Yes, BDD verification updates a knowledge graph by ingesting scenarios, parsing YAML frontmatter, executing steps via the interaction surface, and collecting evidence according to the configured evidence level to map behavioral correctness.

Can I parse YAML frontmatter from .feature.md files during QA verification?

Yes, during QA verification sessions, the system ingests new .feature.md files arriving in bdds/ and parses their YAML frontmatter to extract area, tags, and notes for planning and executing behavioral verification steps.

What are the limitations of black-box BDD verification?

Black-box BDD verification operates purely against observable behavior and does not peer into implementation details, meaning it cannot diagnose internal code-level defects directly and relies entirely on the configured interaction surface and evidence collection levels.