gz-adr-eval — community gz-adr-eval, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
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About this Skill

Perfect for AI Agents involved in human-AI collaboration needing structured quality evaluation for ADRs and OBPI decompositions. GovZero Kit: A Development Covenant for Human-AI Collaboration - gzkit is cognitive infrastructure for extended human-AI collaboration - a protocol that preserves human intent across agent context bou

tvproductions tvproductions
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Updated: 3/26/2026

Agent Capability Analysis

The gz-adr-eval skill by tvproductions is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for AI Agents involved in human-AI collaboration needing structured quality evaluation for ADRs and OBPI decompositions.

Core Value

Empowers agents to ensure trustworthy interactions by providing rubrics, challenge protocols, and a red-team prompt, enabling reliable human-AI collaboration through blocking QC steps and evaluation scorecards.

Capabilities Granted for gz-adr-eval

Evaluating newly authored ADRs
Retroactively assessing existing ADR packages
Generating evaluation scorecards for ADR documents

! Prerequisites & Limits

  • Requires access to ADR documents
  • Limited to ADR and OBPI decomposition evaluation
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SKILL.md
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gz-adr-eval (v6.0.0)

Purpose

Structured quality evaluation for ADRs and their OBPI decompositions. This skill provides rubrics, challenge protocols, and a red-team prompt that form a blocking QC step between ADR authoring and human proposal/defense review.

It can be invoked for newly authored ADRs or for retroactive evaluation of an existing ADR package.


Trust Model

Layer 1 - Evidence Gathering. This tool reads ADR documents and produces evaluation scorecards. It does not modify ADR or brief content.

  • Reads: ADR document, OBPI briefs, evaluation framework template
  • Writes: EVALUATION_SCORECARD.md in the ADR directory
  • Does NOT modify: ADR content, brief content, registries, or ledgers

Invocation

text
1/gz-adr-eval ADR-X.Y.Z # evaluate a specific ADR 2/gz-adr-eval ADR-X.Y.Z --red-team # include the 10-challenge red-team protocol

Arguments:

ArgumentRequiredDescription
adr_idYesADR identifier (for example ADR-0.13.0)
--red-teamNoInclude the 10-challenge adversarial review protocol

When to Use

  • After drafting a new ADR and its OBPIs
  • Before moving a Draft ADR to Proposed / human defense review
  • When benchmarking the quality of an existing ADR package
  • When you want a structured red-team pass against scope, evidence, and decomposition

Procedure

Step 1: Locate the ADR and its OBPIs

  1. Resolve the ADR document under docs/design/adr/**/ADR-X.Y.Z-*/ADR-X.Y.Z-*.md
  2. List all OBPI briefs in obpis/ (preferred) or briefs/ (legacy)
  3. Read the evaluation framework from assets/ADR_EVALUATION_FRAMEWORK.md

Step 2: Score ADR Quality (Part 1 - 8 Dimensions)

Read Part 1 of the framework and score the ADR on each dimension (1-4 scale):

#DimensionWeight
1Problem Clarity15%
2Decision Justification15%
3Feature Checklist Completeness15%
4OBPI Decomposition Quality15%
5Lane Assignment Correctness10%
6Scope Discipline10%
7Evidence Requirements10%
8Architectural Alignment10%

For each dimension, work through the checklist items in the framework and score based on how many checklist items pass with path-level evidence.

Step 3: Score OBPI Quality (Part 2 - 5 Dimensions)

For each OBPI, score on 5 dimensions (1-4 scale):

DimensionQuestion
IndependenceCan this OBPI be completed without waiting for others?
TestabilityCan completion be verified with commands?
ValueWhat concrete capability would be lost if this OBPI were removed?
SizeIs this a 1-3 day work unit?
ClarityCould a different agent implement this without ambiguity?

Step 4: Run Red-Team Challenges (Optional - Part 3)

If --red-team is specified, or if the evaluator wants stronger adversarial review, work through all 10 structured challenges from the framework.

Every challenge must be engaged. N/A is not acceptable.

Step 5: Determine Verdict

Apply the framework thresholds:

ADR Weighted TotalVerdict
>= 3.0GO - Ready for proposal/defense review
2.5 - 3.0CONDITIONAL GO - Address weaknesses, then re-evaluate
< 2.5NO GO - Structural revision required

OBPI threshold: Average >= 3.0 per OBPI. Any OBPI scoring 1 on any dimension must be revised.

Red-team threshold: <= 2 failures = GO, 3-4 = CONDITIONAL GO, >= 5 = NO GO.

Step 6: Record Scorecard

Write EVALUATION_SCORECARD.md in the ADR directory using the summary template from the framework. Include:

  • All ADR dimension scores with weighted totals
  • All OBPI dimension scores with averages
  • Red-team challenge results when run
  • Overall verdict (GO / CONDITIONAL GO / NO GO)
  • Action items for any deficiencies

Step 7: Gate Decision

  • GO: proceed to human proposal/defense review
  • CONDITIONAL GO: revise the ADR or OBPIs, then re-run evaluation
  • NO GO: return to authoring; do not proceed to proposal/defense

External Red-Team Review

For adversarial review by a separate model:

  1. Read the red-team model prompt from Part 4 of the framework
  2. Copy the prompt and append the target ADR document
  3. Send it to a separate model
  4. Review the challenge report and address findings before proposal/defense

Assets

  • Evaluation Framework: assets/ADR_EVALUATION_FRAMEWORK.md
    • Part 1: ADR quality rubric (8 weighted dimensions)
    • Part 2: OBPI quality rubric (5 dimensions)
    • Part 3: Red-team challenge protocol (10 challenges)
    • Part 4: Red-team model prompt
    • Part 5: Scoring summary template

Failure Modes

FailureCauseResolution
Framework not foundassets/ADR_EVALUATION_FRAMEWORK.md missingRepair skill directory structure
ADR not foundNo ADR package matches the requested IDVerify ADR exists and uses canonical naming
No OBPIs foundobpis/ and briefs/ are emptyADR must have co-created OBPIs before evaluation
Scorecard not writtenPath or permission errorVerify ADR directory is writable
NO GO verdictADR has structural deficienciesRevise ADR and re-run evaluation before proposal/defense

Acceptance Rules

  • All 8 ADR dimensions are scored with evidence-based rationale
  • All OBPIs are scored on all 5 dimensions
  • EVALUATION_SCORECARD.md is written to the ADR directory
  • Verdict follows the threshold rules with no manual override
  • NO GO blocks progression to human proposal/defense

Related Skills

SkillRelationship
gz-adr-createAuthoring workflow that should invoke evaluation before proposal
gz-adr-managerCompatibility alias that inherits gz-adr-create behavior
gz-adr-checkEvidence/coverage checks; different concern
gz-adr-auditPost-completion audit; downstream phase
gz-adr-closeout-ceremonyCloseout occurs after implementation, not authoring

References

  • Evaluation framework: assets/ADR_EVALUATION_FRAMEWORK.md
  • ADR lifecycle: docs/governance/GovZero/adr-lifecycle.md
  • GovZero charter: docs/governance/GovZero/charter.md
  • Parity origin: ../airlineops/.github/skills/gz-adr-eval/SKILL.md

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is gz-adr-eval?

Perfect for AI Agents involved in human-AI collaboration needing structured quality evaluation for ADRs and OBPI decompositions. GovZero Kit: A Development Covenant for Human-AI Collaboration - gzkit is cognitive infrastructure for extended human-AI collaboration - a protocol that preserves human intent across agent context bou

How do I install gz-adr-eval?

Run the command: npx killer-skills add tvproductions/gzkit/gz-adr-eval. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for gz-adr-eval?

Key use cases include: Evaluating newly authored ADRs, Retroactively assessing existing ADR packages, Generating evaluation scorecards for ADR documents.

Which IDEs are compatible with gz-adr-eval?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for gz-adr-eval?

Requires access to ADR documents. Limited to ADR and OBPI decomposition evaluation.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add tvproductions/gzkit/gz-adr-eval. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use gz-adr-eval immediately in the current project.

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