[Pelis Agent Factory Advisor] Daily Agentic Workflow Assessment and Recommendations #956
Description
📊 Executive Summary
This repository has a solid foundation of 28 agentic workflows with strong security focus. However, compared to Pelis Agent Factory best practices, there are significant opportunities to add meta-agents for observability, continuous code improvement workflows, and better automation orchestration. The repository is at maturity level 3/5 with clear paths to reach level 4 through strategic additions of 8-10 high-impact workflows.
Top 3 Quick Wins: Metrics Collector (track workflow health), Code Simplifier (continuous refactoring), and Workflow Audit Trail (meta-agent monitoring).
🎓 Patterns Learned from Pelis Agent Factory
After thoroughly exploring the Pelis Agent Factory documentation and the agentics repository, several key patterns emerged:
Core Philosophy
- "Max out on automated agentic workflows" - Create specialized workflows for every opportunity
- Specialization reveals possibilities - Focused agents find more applications than monolithic ones
- Meta-agents are incredibly valuable - Agents monitoring other agents provide outsized impact
- Causal chains demonstrate value - Issues created by one agent leading to PRs from another shows effectiveness
Success Patterns from gh-aw Repository
- Metrics Collector: 41 daily discussions tracking agent ecosystem performance
- Portfolio Analyst: 7 discussions identifying cost reduction opportunities
- Audit Workflows: 93 discussions as meta-agent analyzing all workflow runs
- CLI Consistency Checker: 80 merged PRs (78% merge rate)
- CI Coach: 9 merged PRs (100% merge rate) optimizing CI pipelines
- Workflow Health Manager: 40 issues monitoring workflow health, leading to 34 PRs
Best Practices Observed
✅ Title prefixes make bot contributions identifiable ([Bot], [docs], [Test Coverage])
✅ Skip conditions prevent duplicate work (skip-if-match queries)
✅ Shared imports reuse pagination patterns (imports: shared/mcp-pagination.md)
✅ Cache-memory stores state across runs for efficiency
✅ Network restrictions limit domains for security
✅ Read-only analysts are powerful (many workflows just analyze and report)
✅ Daily schedules maintain continuous quality pressure
📋 Current Agentic Workflow Inventory
| Workflow | Purpose | Trigger | Assessment |
|---|---|---|---|
| Security & Compliance (6) | |||
| security-guard | PR security review for firewall weakening | PR opened/sync | ✅ Excellent - domain-specific security focus |
| security-review | Daily security review and threat modeling | Daily | ✅ Good - proactive security |
| secret-digger-* (3) | Hourly secret scanning (claude/codex/copilot) | Hourly | |
| dependency-security-monitor | Dependency vulnerability monitoring | Daily | ✅ Good - supply chain security |
| Build & Test Validation (6) | |||
| build-test-* | Language ecosystem testing (bun/cpp/deno/dotnet/node/rust) | PR opened/sync | ✅ Excellent - comprehensive validation |
| Smoke Testing (3) | |||
| smoke-* | End-to-end testing (claude/codex/copilot/chroot) | PR + Schedule | ✅ Good - multi-engine coverage |
| Code Quality (4) | |||
| doc-maintainer | Sync docs with code changes | Daily | ✅ Good - prevents drift |
| cli-flag-consistency-checker | CLI consistency and typos | Weekly | ✅ Good - UX quality |
| test-coverage-improver | Add tests for security-critical paths | Weekly | ✅ Excellent - security-focused testing |
| CI/CD Operations (3) | |||
| ci-doctor | Investigate failed workflows | workflow_run failure | ✅ Excellent - reduces manual triage |
| ci-cd-gaps-assessment | Identify CI/CD pipeline gaps | Daily | ✅ Good - continuous assessment |
| update-release-notes | Auto-generate release notes | Release published | ✅ Good - reduces manual work |
| Issue/PR Management (2) | |||
| issue-duplication-detector | Detect duplicate issues with cache | Issue opened | ✅ Good - uses cache-memory |
| issue-monster | SWE agent for issue resolution | Issue opened + Hourly | ✅ Good - automated fixes |
| Planning & Meta (2) | |||
| plan | ChatOps planning command | /plan slash command | ✅ Good - interactive planning |
| pelis-agent-factory-advisor | This workflow! | Daily | ✅ Self-assessment |
Key Gaps in Current Portfolio
❌ No metrics/analytics workflows - No cost tracking, performance monitoring, or workflow health metrics
❌ No continuous refactoring - No code simplification or duplicate detection workflows
❌ No workflow orchestration - No meta-agents coordinating across workflows
❌ Limited release automation - Only release notes, no changelog, versioning, or artifact validation
❌ No community engagement - No contributor welcome, response templates, or engagement tracking
🚀 Actionable Recommendations
P0 - Implement Immediately (High Impact, Low Effort)
1. Metrics Collector Workflow
What: Daily workflow that tracks performance metrics across all agentic workflows (execution time, cost estimates, success/failure rates, token usage patterns).
Why: Without metrics, you're flying blind. This provides visibility into workflow health, cost patterns, and identifies optimization opportunities. Pelis Factory's Metrics Collector created 41 daily discussions and became the "central nervous system" of their agent ecosystem.
How:
- Trigger: Daily schedule
- Read workflow run history using GitHub Actions tools
- Calculate aggregate metrics (avg runtime, success rate, cost estimates)
- Store trends in cache-memory for historical analysis
- Create daily discussion with metrics dashboard
Effort: Low (1-2 days)
Example Structure:
---
description: Daily metrics tracking for all agentic workflows
on:
schedule: daily
permissions:
contents: read
actions: read
tools:
github:
toolsets: [default, actions]
cache-memory: true
safe-outputs:
create-discussion:
title-prefix: "[Metrics] "
category: "general"
timeout-minutes: 15
---
# Daily Metrics Collector
Track performance across all agentic workflows:
1. Fetch last 24h workflow runs
2. Calculate metrics: success rate, avg duration, estimated cost
3. Compare to historical baseline (cache-memory)
4. Identify trends and anomalies
5. Create daily metrics report discussion2. Workflow Audit Trail
What: Meta-agent that analyzes logs from all workflow runs, identifying patterns, errors, and optimization opportunities.
Why: Pelis Factory's Audit Workflows created 93 discussions by analyzing logs, costs, and success patterns across all runs. Acts as quality control for the entire agent ecosystem.
How:
- Trigger: Daily schedule
- Use GitHub Actions tools to fetch recent workflow runs
- Analyze logs for errors, warnings, timeouts
- Identify workflows with declining success rates
- Track token usage and cost patterns
- Create weekly audit report
Effort: Low-Medium (2-3 days)
Example Structure:
---
description: Meta-agent auditing all agentic workflow runs
on:
schedule: daily
permissions:
contents: read
actions: read
tools:
github:
toolsets: [default, actions]
cache-memory: true
safe-outputs:
create-discussion:
title-prefix: "[Audit] "
create-issue:
title-prefix: "[Workflow Health] "
timeout-minutes: 20
---
# Workflow Audit Trail
Analyze all agentic workflows for health and performance:
1. Fetch last 7 days workflow runs
2. Identify failures, timeouts, and errors
3. Calculate success rates per workflow
4. Compare to historical baseline
5. Create issues for declining workflows
6. Weekly summary discussion3. Code Simplifier Workflow
What: Daily analysis of recently modified code to identify simplification opportunities (reduce complexity, eliminate duplication, improve readability).
Why: Pelis Factory's Code Simplifier created 6 PRs (5 merged, 83% merge rate) by continuously cleaning up after rapid development. Maintains code quality without blocking feature velocity.
How:
- Trigger: Daily schedule
- Analyze git commits from past 3-7 days
- Identify files with high cyclomatic complexity
- Look for repeated patterns, nested conditionals, verbose error handling
- Create PRs with simplifications
Effort: Medium (3-4 days)
Example Structure:
---
description: Continuous code simplification from recent changes
on:
schedule: daily
skip-if-match:
query: 'is:pr is:open in:title "[Simplify]"'
max: 1
permissions:
contents: read
tools:
github:
toolsets: [default]
bash:
- "git log*"
- "cat:*"
safe-outputs:
create-pull-request:
title-prefix: "[Simplify] "
labels: [refactor, ai-generated]
timeout-minutes: 20
---
# Daily Code Simplifier
Analyze recently changed code for simplification:
1. Get commits from past 7 days
2. Identify changed .ts files
3. Look for: nested conditionals, repeated logic, verbose patterns
4. Propose simplifications preserving functionality
5. Create PR with improvementsP1 - Plan for Near-Term (High Impact, Medium Effort)
4. Duplicate Code Detector (Semantic)
What: Weekly analysis using semantic code understanding to find duplicate logic patterns across the codebase (not just textual similarity).
Why: Pelis Factory's Duplicate Code Detector achieved 79% merge rate (76 merged PRs) by understanding code meaning rather than syntax. Identifies patterns where logic is duplicated even with different variable names.
How:
- Use AST parsing or code analysis tools
- Compare function signatures, control flow patterns
- Focus on recent changes (last 2 weeks)
- Create issues for significant duplication (10+ lines, 3+ occurrences)
Effort: Medium-High (5-7 days - requires AST integration)
5. Release Automation Suite
What: Comprehensive release workflow handling version bumping, changelog generation, tag creation, and artifact verification.
Why: Current release automation only generates release notes. A full suite reduces manual release overhead and ensures consistency.
How:
- Trigger: On release published or manual
- Generate changelog from commits
- Update version numbers in package.json
- Verify container image signatures
- Post-release health check
- Create GitHub release with assets
Effort: Medium (4-5 days)
Components:
- Changelog Maintainer (daily, updates CHANGELOG.md)
- Version Bumper (on release, updates versions)
- Release Validator (post-release, verifies artifacts)
6. CI Optimization Coach
What: Weekly analysis of CI pipeline performance identifying slow tests, redundant steps, and caching opportunities.
Why: Pelis Factory's CI Coach achieved 100% merge rate (9/9 PRs) optimizing pipelines. Reduces CI time and cost.
How:
- Analyze workflow run durations
- Identify slow jobs/steps
- Check for redundant test execution
- Recommend caching strategies
- Create PRs with optimizations
Effort: Medium (3-4 days)
7. Firewall Policy Validator
What: Daily automated testing of firewall rule effectiveness (domain blocking, protocol filtering, edge cases).
Why: Domain-specific for this repository! Ensures firewall rules work as expected across different scenarios. Catches regressions in security posture.
How:
- Generate test matrix (allowed/blocked domains, protocols)
- Run automated tests in container
- Verify Squid ACL rules work correctly
- Check iptables rules are enforced
- Create issues for failures
Effort: Medium (3-4 days)
Example Structure:
---
description: Daily validation of firewall policy effectiveness
on:
schedule: daily
permissions:
contents: read
tools:
bash:
- "*"
safe-outputs:
create-issue:
title-prefix: "[Firewall Test] "
timeout-minutes: 15
---
# Firewall Policy Validator
Test firewall rules comprehensively:
1. Build firewall containers
2. Test allowed domains (should succeed)
3. Test blocked domains (should fail)
4. Test edge cases (wildcards, subdomains, protocols)
5. Verify iptables rules active
6. Report any failures as issues8. Performance Benchmark Tracker
What: Weekly network throughput and latency benchmarking to detect performance regressions.
Why: As a firewall, performance is critical. Automated benchmarking catches regressions before users do.
How:
- Run benchmark suite (throughput, latency, connection count)
- Compare to baseline (cache-memory)
- Detect significant regressions (>10% slowdown)
- Create issues for performance degradation
- Track trends over time
Effort: Medium (3-4 days)
P2 - Consider for Roadmap (Medium Impact)
9. Container Image Security Scanner
What: Daily CVE scanning of Squid and agent Docker images.
Why: Container security is critical for a firewall tool. Automated scanning catches vulnerabilities early.
How: Integrate Trivy or Grype, run daily scans, create issues for HIGH/CRITICAL CVEs
Effort: Low-Medium (2-3 days)
10. Attack Simulation Workflow
What: Weekly automated penetration testing attempting to bypass firewall restrictions.
Why: Validates security posture through adversarial testing. Catches bypass techniques before attackers do.
How:
- Test DNS exfiltration attempts
- Try protocol tunneling (DNS over HTTPS)
- Attempt IP-based bypasses
- Test Squid ACL edge cases
- Report any successful bypasses as critical issues
Effort: High (7-10 days - requires security expertise)
11. Log Anomaly Detector
What: Daily analysis of Squid access logs for anomalous patterns (unusual domains, suspicious traffic patterns).
Why: Behavioral analysis can catch attacks that rule-based filtering misses.
How:
- Parse Squid access.log files
- Build baseline of normal traffic (cache-memory)
- Detect anomalies (new domains, unusual patterns)
- Create issues for investigation
Effort: Medium-High (5-6 days)
12. Contributor Welcome Bot
What: Greet new contributors, provide onboarding resources, and help with first issues.
Why: Improves community engagement and reduces onboarding friction.
How: On first issue/PR from a user, add welcome comment with links to CONTRIBUTING.md, good first issues, etc.
Effort: Low (1-2 days)
13. Documentation Multi-Device Tester
What: Weekly Playwright-based testing of documentation across different devices and screen sizes.
Why: Pelis Factory's Multi-Device Docs Tester caught mobile rendering issues. Ensures docs are accessible.
How: Use Playwright to render docs on mobile/tablet/desktop viewports, verify layout, create PRs for issues
Effort: Medium (3-4 days)
14. Dependency Update Automation
What: Weekly automated dependency updates with test runs (like Dependabot but smarter).
Why: Keeps dependencies fresh, reduces security debt. Can auto-merge low-risk updates.
How:
- Check for outdated dependencies
- Create PRs with updates
- Run full test suite
- Auto-merge if tests pass and no breaking changes
Effort: Medium (3-4 days)
P3 - Future Ideas (Low Priority)
15. Stale Issue Closer
What: Monthly cleanup of stale issues (no activity in 90 days).
Why: Reduces noise, keeps issue tracker focused.
Effort: Low (1 day)
16. PR Review Complexity Analyzer
What: Analyze PRs for size/complexity, suggest splitting large PRs.
Why: Smaller PRs get reviewed faster and more thoroughly.
Effort: Low-Medium (2 days)
📈 Maturity Assessment
Current Level: 3/5 (Operational)
Characteristics:
- ✅ Good coverage of basic automation (build, test, security)
- ✅ Strong domain-specific focus (security/firewall)
- ✅ Some meta-workflows (ci-doctor, this advisor)
⚠️ Limited observability (no metrics collection)⚠️ No continuous refactoring workflows⚠️ Missing workflow orchestration- ❌ No cost/performance optimization
Target Level: 4/5 (Optimized)
What's needed:
- Meta-agents monitoring workflow health (Metrics Collector, Audit Trail)
- Continuous code improvement (Simplifier, Duplicate Detector)
- Full release automation suite
- Performance monitoring and benchmarking
- Cost optimization workflows
- Causal chain patterns (issue → PR automation)
Gap Analysis
To reach level 4, implement:
- P0 workflows (3 workflows) - Foundation for observability
- P1 workflows (5 workflows) - Core automation improvements
- Total: 8 high-impact workflows
Timeline: 3-4 months at 1-2 workflows per sprint
🔄 Comparison with Best Practices
What This Repository Does Well
✅ Security-First Approach: Strong focus on security workflows (security-guard, secret-digger, security-review) appropriate for a firewall tool
✅ Comprehensive Build Validation: 6 language ecosystem smoke tests ensure broad compatibility
✅ CI Failure Investigation: ci-doctor workflow matches Pelis Factory pattern of automated fault investigation
✅ Documentation Sync: doc-maintainer prevents docs from drifting (Pelis Factory pattern)
✅ Test Coverage Focus: test-coverage-improver prioritizes security-critical paths
✅ Cache-Memory Usage: issue-duplication-detector uses persistent cache for efficiency
✅ Self-Assessment: This pelis-agent-factory-advisor workflow shows self-awareness
What Could Be Improved
❌ Missing Meta-Agents: No workflow health manager, metrics collector, or audit trail (Pelis Factory has all three)
❌ No Continuous Refactoring: No code simplifier or duplicate detector (Pelis Factory patterns)
❌ Limited Metrics: No tracking of workflow success rates, costs, token usage (Pelis Factory tracks extensively)
❌ No Causal Chains: Workflows don't create issues that lead to PRs from other workflows (missed pattern)
❌ No Portfolio Analysis: No cost optimization or resource analysis workflows
❌ Limited Release Automation: Only release notes, missing changelog, versioning, validation
Unique Opportunities (Security/Firewall Domain)
🎯 Firewall Policy Validator: Automated testing of ACL rules and domain filtering
🎯 Attack Simulation: Penetration testing attempting to bypass restrictions
🎯 Log Anomaly Detection: Behavioral analysis of proxy logs
🎯 Performance Benchmarking: Network throughput and latency tracking
🎯 Container Security Scanning: Daily CVE checks for Docker images
🎯 DNS Exfiltration Testing: Verify DNS-based data leakage prevention
These domain-specific workflows leverage the repository's unique security context and would provide value that generic workflows cannot.
📝 Notes for Future Runs
Saved to /tmp/gh-aw/cache-memory/:
pelis-factory-patterns.md- Comprehensive pattern catalog from Pelis Factoryrepo-analysis-20260218.md- Today's repository analysis baseline
Track Over Time:
- Number of agentic workflows (currently 28)
- Workflow merge rates (need to start tracking)
- Cost per workflow run (need metrics collector first)
- Success/failure trends (need audit trail first)
- Coverage metrics (currently in COVERAGE_SUMMARY.md)
- Issue/PR velocity (manual tracking only)
Next Run Should:
- Compare against today's baseline
- Check if P0 recommendations were implemented
- Measure impact of any new workflows
- Update maturity assessment
- Identify new patterns from recent Pelis Factory updates
🎯 Recommended Action Plan
Week 1-2: Foundation (P0 Workflows)
- Implement Metrics Collector - Visibility into workflow health
- Implement Workflow Audit Trail - Meta-agent for quality control
- Set up baselines and dashboards
Week 3-4: Quick Wins (P0 Continued)
- Implement Code Simplifier - Start continuous refactoring
- Run for 2 weeks, collect merge rate data
Month 2: Core Improvements (P1)
- Implement Duplicate Code Detector (semantic)
- Implement Firewall Policy Validator (domain-specific!)
- Implement CI Optimization Coach
Month 3: Release & Performance (P1)
- Build Release Automation Suite (changelog, versioning)
- Implement Performance Benchmark Tracker
- Review metrics, adjust priorities
Month 4+: Advanced Features (P2/P3)
- Evaluate P2 workflows based on Month 1-3 learnings
- Consider domain-specific security workflows (attack simulation, anomaly detection)
- Explore community engagement workflows if needed
Expected Outcome: Move from maturity level 3/5 to 4/5, with 8+ high-value workflows added and measurable improvements in code quality, release efficiency, and workflow reliability.
This analysis generated by Pelis Agent Factory Advisor on 2026-02-18. Next scheduled run: tomorrow (daily schedule).
Note: This was intended to be a discussion, but discussions could not be created due to permissions issues. This issue was created as a fallback.
AI generated by Pelis Agent Factory Advisor
- expires on Feb 25, 2026, 3:31 AM UTC