Crawler Summary

fagan-code-review answer-first brief

Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. --- name: fagan-code-review description: Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. license: Apache-2.0 version: 1.0.0 tags: [code-review, quality-assurance, inspection, methodology, error-detection] --- Fagan Code Review A systematic code inspection metho Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

Best For

fagan-code-review is best for general automation workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 94/100

fagan-code-review

Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. --- name: fagan-code-review description: Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. license: Apache-2.0 version: 1.0.0 tags: [code-review, quality-assurance, inspection, methodology, error-detection] --- Fagan Code Review A systematic code inspection metho

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Nikolasrieble

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Setup snapshot

git clone https://github.com/nikolasrieble/fagan-inspection-skill.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Nikolasrieble

profilemedium
Observed Apr 15, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 15, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

3

Snippets

0

Languages

typescript

Parameters

Executable Examples

text

"Conduct a Fagan inspection on src/auth/login.js"

text

✅ DO:
- Focus solely on finding errors
- Let the reader paraphrase the logic
- Cover every line and every branch
- Note error type and severity immediately
- Pursue questions only until error is identified
- Keep moving to cover all material

❌ DON'T:
- Discuss how to fix errors
- Debate design alternatives
- Go down solution rabbit holes
- Let meetings exceed 2 hours (efficiency drops)
- Skip "obvious" or "simple" sections
- Use inspection results for performance reviews

bash

# Interactive mode (prompts for all data)
python3 scripts/inspection_report.py --interactive

# Generate from JSON file
python3 scripts/inspection_report.py --from-file inspection_data.json

# Generate specific report type
python3 scripts/inspection_report.py --from-file data.json --report-type summary

# All reports to custom directory
python3 scripts/inspection_report.py --from-file data.json --output-dir ./reports

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. --- name: fagan-code-review description: Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. license: Apache-2.0 version: 1.0.0 tags: [code-review, quality-assurance, inspection, methodology, error-detection] --- Fagan Code Review A systematic code inspection metho

Full README

name: fagan-code-review description: Systematic code inspection methodology for finding errors through structured team review. Based on Michael Fagan's formal inspection process (1976). Use for code reviews, design reviews, and quality audits. license: Apache-2.0 version: 1.0.0 tags: [code-review, quality-assurance, inspection, methodology, error-detection]

Fagan Code Review

A systematic code inspection methodology based on Michael Fagan's formal inspection process (1976). This skill teaches structured error detection through team-based review with separated objectives, defined roles, and measurable outcomes.

Quick Start

For AI-assisted inspection:

"Conduct a Fagan inspection on src/auth/login.js"

For detailed usage instructions: See HOW-TO-USE.md for step-by-step guides and examples.

For human teams: Follow the 5-phase process below with your inspection team.

When to Use This Skill

  • Conducting formal code inspections (design or implementation)
  • Reviewing pull requests with systematic rigor
  • Performing quality audits on critical code
  • Training teams in structured review processes
  • Establishing inspection checkpoints in development workflow
  • Analyzing error patterns and improving code quality

Core Principles

Separation of Objectives: Never mix error finding with error fixing, or education with inspection.

Systematic Coverage: All code inspected, all branches examined, all logic verified.

Role-Based Process: Moderator, designer, implementor, and tester each have specific responsibilities.

Measurable Outcomes: Track errors by type, severity, and density for continuous improvement.

Early Detection: Find errors as close to origin as possible (10-100× cost savings).

The 5-Phase Process

1. Overview (Optional - Team Meeting)

  • When: New material or new team members
  • Duration: As needed to understand context
  • Who: Designer presents to entire team
  • Output: Shared understanding of what's being reviewed
  • Skip if: Same team reviewed the design

2. Preparation (Individual)

  • Duration: Study material individually
  • Rate: 100-125 LOC/hour
  • Activities:
    • Study code/design and documentation
    • Review error checklists (load references/checklists.md)
    • Note questions and potential errors
    • Do NOT fix errors during preparation
  • Output: Prepared participants ready for inspection

3. Inspection Meeting (Team - MOST CRITICAL)

  • Duration: Maximum 2 hours per session
  • Rate: 130-150 LOC/hour
  • Focus: FIND ERRORS ONLY - no fixing, no design discussions
  • Process:
    • Reader paraphrases how they will implement
    • Cover every piece of logic at least once
    • Take every branch at least once
    • Questions pursued only to point of error recognition
    • Moderator notes errors with type and severity
    • NO solution hunting
  • Output: List of errors with classifications

4. Rework (Individual)

  • Who: Original author
  • Duration: Until all errors resolved
  • Activities: Fix all errors identified in inspection
  • Output: Corrected code/design

5. Follow-Up (Moderator-Led)

  • Critical Rule: ALL errors must be resolved before proceeding
  • Reinspection Required If: >5% of material reworked
  • Moderator Verifies: All issues from inspection are correctly fixed
  • Output: Signed-off inspection report

Conducting an Inspection

Before the Meeting

  1. Moderator schedules meeting with all roles filled
  2. Distribute materials to all participants 1-2 days before
  3. All participants prepare individually (critical for success)
  4. Review checklists for error types (load references/checklists.md)

During the Meeting (2 Hours Max)

✅ DO:
- Focus solely on finding errors
- Let the reader paraphrase the logic
- Cover every line and every branch
- Note error type and severity immediately
- Pursue questions only until error is identified
- Keep moving to cover all material

❌ DON'T:
- Discuss how to fix errors
- Debate design alternatives
- Go down solution rabbit holes
- Let meetings exceed 2 hours (efficiency drops)
- Skip "obvious" or "simple" sections
- Use inspection results for performance reviews

After the Meeting

  1. Moderator produces report within 24 hours
  2. Author fixes all identified errors
  3. Moderator verifies all fixes in follow-up
  4. Reinspect if >5% reworked
  5. Update error metrics and distributions

Roles and Responsibilities

Load references/roles-responsibilities.md for complete details.

Quick summary:

  • Moderator: Manages process, notes errors, ensures follow-up (most critical role)
  • Designer: Presents the design or architecture
  • Implementor/Coder: Acts as reader, paraphrases implementation
  • Tester: Reviews testability and test coverage

Team Size: 4 people optimal

Error Classification

Classify each error by three dimensions:

Type: LO (Logic), IC (Interconnection), TB (Test/Branch), DE (Design Error), etc. Category: M (Missing), W (Wrong), E (Extra) Severity: Major (causes malfunction) or Minor (lesser impact)

Example: LO/M/MAJ = Logic error, Missing, Major severity

Load references/error-classification.md for complete taxonomy.

Metrics and Tracking

Key Metrics

  • Errors per K.LOC: Primary quality metric
  • Error detection efficiency: (Errors found / Total errors) × 100
  • Inspection rate: LOC per hour
  • Rework effort: Hours per K.LOC

Target Results (from Fagan 1976 research)

  • 60-82% error detection efficiency
  • 20%+ productivity improvement vs. no inspection
  • 38% fewer errors vs. informal reviews

Use Metrics For

  • Identifying error-prone modules
  • Allocating testing effort
  • Process improvement
  • Training focus areas

Use the inspection report tool to track metrics over time. Aggregate data manually or via custom tooling.

Inspection Types

I₁ - Design Inspection: Review design before coding

  • Entry: Design complete to level of 3-10 code instructions per statement
  • Focus: Logic, design decisions, interfaces
  • Use design checklists

I₂ - Code Inspection: Review implementation

  • Entry: First clean compilation
  • Focus: Implementation correctness, test/branch logic, interconnections
  • Use code checklists

Modified Code Inspection: Review changes/fixes

  • ALL modifications must be inspected
  • Error rate in modified code is higher than new code
  • Group small changes for batch inspection

Checklists

Load references/checklists.md when conducting inspections.

The checklists provide systematic prompts for finding common error types:

  • Design inspection: Logic missing/wrong, interface issues
  • Code inspection: Test/branch errors, interconnection errors
  • Modified code: Change impact, regression concerns

Process Details

Load references/inspection-phases.md for complete phase documentation.

Key insights:

  • Preparation is individual, inspection is team
  • 2-hour time limit is critical for efficiency
  • Moderator training is essential
  • Follow-up is mandatory, not optional
  • Reinspection threshold: >5% rework

Best Practices

Critical Success Factors

  1. ONE objective at a time - never mix finding and fixing
  2. Moderator training - brief but essential
  3. 2-hour time limit - efficiency drops after this
  4. 100% coverage - no exceptions for "simple" code
  5. Scheduling discipline - make time for inspection or it won't happen
  6. No performance reviews - data is for programmer benefit only

Common Pitfalls to Avoid

  • Skipping preparation phase
  • Letting meetings become debugging sessions
  • Not following up on rework
  • Using inspection data against programmers
  • Exceeding 2-hour meeting duration
  • Skipping "trivial" modifications

Inspection vs. Walkthrough

| Aspect | Fagan Inspection | Walkthrough | |--------|-----------------|-------------| | Moderator training | Required | No | | Defined roles | Yes | No | | Who drives | Moderator | Code author | | Checklists | Yes | No | | Formal follow-up | Yes | No | | Metrics tracked | Yes | No | | Process improvement | Yes | No |

Generating Reports

Run scripts/inspection_report.py --help for report generation.

Report Types

The script generates four types of formal reports:

  1. Error List (error-list) - Detailed list of all errors found

    • Each error with location, classification, description
    • Possible solutions if identified
    • Use for: Rework phase, tracking specific issues
  2. Module Detail (module-detail) - Statistical analysis

    • Error counts by type, category, severity
    • Reinspection decision with rationale
    • Use for: Quality metrics, process improvement
  3. Inspection Summary (summary) - Executive overview

    • Participants and roles
    • Size estimates and effort metrics
    • Error totals and quality metrics
    • Sign-off section for approval
    • Use for: Management reporting, audit trail
  4. JSON Data (json) - Machine-readable export

    • Complete inspection data in structured format
    • Use for: Metrics aggregation, tool integration

Usage Examples

# Interactive mode (prompts for all data)
python3 scripts/inspection_report.py --interactive

# Generate from JSON file
python3 scripts/inspection_report.py --from-file inspection_data.json

# Generate specific report type
python3 scripts/inspection_report.py --from-file data.json --report-type summary

# All reports to custom directory
python3 scripts/inspection_report.py --from-file data.json --output-dir ./reports

Reports must be completed within 24 hours of inspection meeting.

Adapting for Modern Development

For Pull Requests

  • Author = Designer + Implementor
  • Reviewer(s) = Moderator + team roles
  • Use async preparation, sync discussion (or structured async)
  • Apply checklists in review comments
  • Track error types in review analytics

For Solo Development

  • Conduct self-inspection with checklists
  • Focus on systematic coverage
  • Track personal error patterns
  • Use metrics to improve over time
  • Consider pair programming as inspection variant

For Agile Teams

  • Inspection as definition of done
  • Quick I₁ for design spikes
  • I₂ for critical features
  • Modified code inspection for bug fixes
  • Sprint retrospective reviews error patterns

Reference Materials

Load these on-demand during inspections:

  • references/checklists.md - Systematic error-finding prompts
  • references/error-classification.md - Complete error taxonomy
  • references/roles-responsibilities.md - Detailed role descriptions
  • references/inspection-phases.md - Complete 5-phase process guide
  • HOW-TO-USE.md - Step-by-step usage guide with examples
  • QUICK-REFERENCE.md - One-page quick reference card
  • examples/sample-inspection-session.md - Complete example inspection with AI

Scripts and Tools

  • scripts/inspection_report.py - Generate formal inspection reports with error tracking and metrics

References

Based on: Fagan, M.E. (1976). "Design and Code Inspections to Reduce Errors in Program Development." IBM Systems Journal, 15(3), 182-211.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/snapshot"
curl -s "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/contract"
curl -s "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T03:41:17.556Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Nikolasrieble",
    "href": "https://github.com/nikolasrieble/fagan-inspection-skill",
    "sourceUrl": "https://github.com/nikolasrieble/fagan-inspection-skill",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T03:16:38.519Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T03:16:38.519Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/nikolasrieble-fagan-inspection-skill/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

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