nw-ab-critique-dimensi…
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence.
$ npx -y skills add nWave-ai/nWave --skill nw-shared-artifact-tracking --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nw-shared-artifact-trackingContext preview
The summary Claude sees to decide when to auto-load this skill.
Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence.
name: nw-shared-artifact-tracking description: Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence. user-invocable: false disable-model-invocation: true
Shared artifacts are data values appearing in multiple places across a journey. Every ${variable} must have a single source of truth and documented consumers. Untracked artifacts are the primary cause of horizontal integration failures.
shared_artifacts:
{artifact_name}:
source_of_truth: "{canonical file path}"
consumers: ["{list of places this value appears}"]
owner: "{responsible feature/component}"
integration_risk: "HIGH|MEDIUM|LOW - {explanation}"
validation: "{How to verify consistency}"Source: `pyproject.toml` | Consumers: CLI --version, about command, README, install output Risk: HIGH -- version mismatch breaks user trust
Source: `config/paths.yaml` or `constants.py` | Consumers: install script, uninstall script, documentation Risk: HIGH -- path mismatch breaks installation
Source: `pyproject.toml` or config | Consumers: README, error messages, install docs Risk: MEDIUM -- URL mismatch breaks external links
Source: config file or environment variable | Consumers: runtime behavior, documentation, defaults display Risk: MEDIUM -- inconsistency causes confusion
Source: CLI argument parser definition | Consumers: help text, documentation, error messages, tutorials Risk: HIGH -- name mismatch makes features undiscoverable
1. List all shared artifacts from journey schema 2. For each artifact, verify source of truth exists 3. For each consumer, verify it references correct source 4. Flag any artifact without documented source 5. Flag any consumer that hardcodes instead of referencing source
Journey completeness: all steps have clear goals | CLI commands/actions | emotional annotations | shared artifacts tracked | integration checkpoints defined
Emotional coherence: emotional arc defined (start/middle/end) | no jarring transitions | confidence builds progressively | error states guide to resolution
Horizontal integration: all shared artifacts have single source of truth | all consumers documented | integration checkpoints validate consistency | CLI vocabulary consistent
CLI UX compliance: command structure follows chosen pattern | help available on all commands | progressive disclosure implemented | error messages actionable
Artifacts: `docs/feature/{feature-id}/discuss/journey-{name}.yaml` (complete journey with emotional arc) | `docs/feature/{feature-id}/discuss/shared-artifacts-registry.md` (tracked artifacts with sources)
Validation: journey complete with all steps | emotional arc defined | shared artifacts documented | CLI vocabulary consistent
Deliverables: `docs/feature/{feature-id}/discuss/journey-{name}.yaml` (journey schema) | `docs/feature/{feature-id}/discuss/journey-{name}.feature` (Gherkin scenarios) | `docs/feature/{feature-id}/discuss/shared-artifacts-registry.md` (integration validation points)
Validation: all product-owner checks passed | Gherkin scenarios generated | integration checkpoints testable | peer review approved
AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
Repo: nWave-ai/nWave
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton…
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance
Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating…