Agent Persona Exploration - 2026-02-21

[github-actions[bot]]

Overview

The agentic-workflows custom agent was tested across 8 scenarios covering 5 software worker personas. The agent demonstrated strong overall performance (4.05/5.0 average), with consistently excellent security practices and trigger configuration. The primary weakness was tool selection for external integrations and a tendency toward over-documentation.

Key Metrics

Dimension	Score
Trigger Appropriateness	4.1/5.0
Tool Selection	3.8/5.0
Security Practices	4.4/5.0 ✅
Prompt Clarity	4.1/5.0
Completeness	3.9/5.0
Overall Average	4.05/5.0

Key Findings

• Security is a strength: Every response applied read-only permissions, strict mode, and safe-outputs — zero insecure configurations observed
• Trigger selection is reliable: PR path-filtered triggers, schedule triggers, and workflow_dispatch were all correctly matched to scenarios
• Tool selection weakens for external monitoring: Scenarios requiring Datadog, CloudWatch, or application metrics received lower tool scores (3/5) due to vague integration guidance
• Over-documentation is a consistent anti-pattern: The agent frequently created 3–6 documentation files per request rather than focusing on the single workflow file
• Playwright recommendation is accurate: Correctly identified for visual regression testing without prompting

Top Patterns

1. Most common triggers: PR path-filtered (4/8 scenarios), schedule (3/8), workflow_dispatch (1/8)
2. Universal tools: GitHub API in all scenarios; bash and cache-memory used when appropriate
3. Security baseline: strict: true, permissions: read-only, safe-outputs for all write operations — applied consistently across all 8 scenarios

View High Quality Responses (Score ≥ 4.2)

be-schema — 4.8/5.0 (Backend: SQL migration review)
Best response overall. Correctly used PR trigger with migration path filters, read-only permissions, safe-outputs for PR comments, and a highly actionable structured prompt. The agent demonstrated domain understanding of SQL safety concerns (missing indexes, destructive ops, backward compatibility).

fe-visual — 4.2/5.0 (Frontend: Visual regression testing)
Correctly identified Playwright as the right tool without being told. Good phase-based prompt structure. Minor: response over-engineered (multiple doc files), but the core workflow configuration was production-ready.

devops-incident — 4.2/5.0 (DevOps: CI failure incident detection)
Strong security posture; cache-memory for failure pattern history was an appropriate and proactive choice. Correct 30-minute schedule trigger. Minor confusion between cache-memory and repo-memory.

qa-coverage — 4.2/5.0 (QA: Test coverage analysis)
Multi-format coverage detection (Jest, pytest, JaCoCo, Go) was excellent. Specific test suggestions with file/line numbers are genuinely useful output. Permissions correctly scoped to actions:read for artifact access.

View Areas for Improvement (Score ≤ 3.8)

be-deploy — 3.6/5.0 (Backend: Post-deployment health check)
Correct workflow_dispatch trigger, but integration with external monitoring tools (Datadog, CloudWatch, Prometheus) was generic. No network firewall config for outbound metrics API calls. Created 6 documentation files — excessive.

devops-capacity — 3.8/5.0 (DevOps: Infrastructure cost report)
The GitHub Actions billing API has limited read access; the workflow assumed availability of detailed cost data that may not be accessible via standard actions:read. This gap in API availability awareness affected usefulness.

pm-digest — 3.8/5.0 (PM: Weekly feature digest)
Schedule correct, Discussion creation appropriate. However, no guidance on GitHub API toolset configuration for accessing cross-repo data. The non-technical language framing in the prompt was generally well-handled.

fe-preview — 3.8/5.0 (Frontend: Stale preview cleanup)
Good platform detection (Vercel, Netlify, etc.) and safety-first approach (no auto-delete). Missing: network access configuration needed to actually validate if preview URLs are still live. Reliance on PR labels for exclusions is fragile.

Recommendations

1. Add external monitoring integration examples to workflow templates — The agent struggles when scenarios require Datadog, CloudWatch, or Prometheus integration. Pre-built network firewall config examples and authentication patterns for common monitoring APIs would significantly improve tool scores for DevOps/Backend scenarios.

2. Guide the agent toward single-file outputs — The agent creates 3–6 documentation files per request, which clutters the workspace and dilutes focus. Explicit guidance to produce one workflow .md file plus a concise inline README section would improve practical utility.

3. Improve GitHub API availability awareness — The agent sometimes suggests reading GitHub Actions billing/cost data that is not accessible via standard actions:read permissions. Adding caveats about GitHub API limitations (especially billing endpoints) would improve reliability of DevOps capacity reports.

References:

• §22247533841

AI generated by Agent Persona Explorer

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