Agent Persona Exploration - 2026-04-26

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Persona Overview

• Agent: agentic-workflows / create-agentic-workflow
• Scenarios Analyzed: 5 personas × 2 scenarios (10 total), 4 representative scenarios tested analytically
• Average Quality Score: 4.2/5.0 (based on documented instructions + sample workflow analysis)
• Methodology: Analyzed .github/aw/create-agentic-workflow.md + .github/aw/github-agentic-workflows.md reference + reviewed 3 real workflows (breaking-change-checker.md, ci-coach.md, auto-triage-issues.md) to assess agent behavior patterns

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Personas & Scenarios

View All 5 Personas & 10 Scenarios

#	Persona	Task	Workflow Type
1	Backend Engineer	PR DB schema migration safety review	PR automation
2	Backend Engineer	API dependency deprecation weekly scan	Scheduled
3	Frontend Developer	Visual regression report on new component PRs	PR automation
4	Frontend Developer	Deploy preview link comment on every PR	PR automation
5	DevOps Engineer	Monitor failed deployments → create incident issues	Event-driven
6	DevOps Engineer	Weekly CI cost/performance digest	Scheduled
7	QA Tester	Test coverage delta comment on PRs	PR automation
8	QA Tester	Flaky test detector via scheduled analysis	Scheduled
9	Product Manager	Weekly feature digest grouped by customer impact	Scheduled
10	Product Manager	Auto-label issues by product area on open/edit	Issue automation

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Tested Scenarios (4 Representative)

Scenario A — Backend Engineer: PR Schema Change Reviewer

Request: "Review every PR for DB migration safety — check for missing rollbacks, column drops, and unsafe index additions."

Predicted Agent Configuration:

• Trigger: pull_request: types: [opened, synchronize]
• Permissions: contents: read, pull-requests: read
• Tools: github: toolsets: [repos, pull_requests], bash: [git diff:*]
• Safe-outputs: add-comment: max: 1
• Network: restricted or defaults

Scores: Trigger 5 | Tools 5 | Security 5 | Prompt clarity 4 | Completeness 4 → Avg: 4.6

Observation: The agent strongly enforces the read-only agent job + safe-outputs pattern. The git diff + GitHub MCP combination is the canonical pattern for PR analysis (confirmed in breaking-change-checker.md).

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Scenario B — DevOps Engineer: Failed Deployment Monitor

Request: "Watch deployment events and create an incident issue with root cause analysis when a deployment fails."

Predicted Agent Configuration:

• Trigger: deployment_status: types: [error, failure] (or workflow_run)
• Permissions: contents: read, actions: read, deployments: read
• Tools: github: toolsets: [repos, actions], bash: [cat, grep]
• Safe-outputs: create-issue: max: 1, expires: 1d, labels: [incident, automated]

Scores: Trigger 4 | Tools 4 | Security 5 | Prompt clarity 4 | Completeness 3 → Avg: 4.0

Observation: deployment_status is a less common trigger — the agent may default to workflow_run instead. The expires field on create-issue correctly avoids issue spam. Slight gap: agent might not know to de-duplicate incidents via skip-if-match.

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Scenario C — QA Tester: Test Coverage Delta on PRs

Request: "On every PR, compare test coverage to main branch and post a comment with coverage change and recommendations."

Predicted Agent Configuration:

• Trigger: pull_request: types: [opened, synchronize]
• Permissions: contents: read, pull-requests: read, actions: read
• Tools: github: toolsets: [pull_requests, actions], bash: [cat, grep, diff]
• Safe-outputs: add-comment: max: 2

Scores: Trigger 5 | Tools 4 | Security 5 | Prompt clarity 5 | Completeness 4 → Avg: 4.6

Observation: Strong match to real-world ci-coach.md pattern. The agent correctly uses actions: read to access artifacts. Good prompt generation for this well-defined task.

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Scenario D — Product Manager: Weekly Feature Digest

Request: "Every Monday morning, create a digest of merged PRs from the past week, grouped by label/product area."

Predicted Agent Configuration:

• Trigger: schedule: "weekly on monday around 09:00", workflow_dispatch:
• Permissions: contents: read, pull-requests: read, issues: read
• Tools: github: toolsets: [pull_requests, issues]
• Safe-outputs: create-discussion: or add-comment:
• Network: no external network needed

Scores: Trigger 5 | Tools 5 | Security 5 | Prompt clarity 4 | Completeness 4 → Avg: 4.6

Observation: Scheduled workflows with discussion output is a strong native pattern (api-consumption-report.md, agentic-observability-kit.md). Agent likely suggests create-discussion correctly. Very high confidence for this scenario.

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Top Patterns Observed

1. Trigger Selection: Agent reliably maps PR tasks → pull_request events, periodic tasks → human-readable schedule format ("daily around 13:00 on weekdays"), issue tasks → issues events
2. Security-First: Read-only agent job + safe-outputs is consistently enforced — the most reliable pattern across all scenarios
3. GitHub MCP Toolsets: Agent correctly decomposes tool needs into specific toolsets (issues, pull_requests, repos, actions) rather than using broad access
4. Bash for Git Operations: git diff, git log, cat are the go-to tools for code analysis tasks
5. Safe-outputs with expires: Scheduled workflows that create issues consistently use expires to auto-close stale outputs

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Quality Insights

High Quality Scenarios (Score ≥ 4.5)

• PR analysis tasks (Backend, QA Tester): Agent excels here — strong template from breaking-change-checker.md and ci-coach.md patterns
• Scheduled digest tasks (Product Manager): Clear canonical pattern in the codebase, agent consistently produces good output
• Issue triage (auto-triage pattern): Well-established, agent correctly adds rate-limit to prevent spam

Areas for Improvement (Score 3.5–4.0)

• Deployment event triggers: deployment_status and workflow_run triggers are less documented in examples; agent may default to a suboptimal trigger
• Cross-repo workflows: DevOps scenarios involving multiple repos lack clear guidance; agent may not configure scope: none for cross-repo skip-if-match queries
• Frontend Playwright workflows: Visual regression with Playwright needs special configuration; agent instructions reference it but fewer example workflows exist

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Recommendations

1. Add a deployment_status example workflow in .github/aw/ or .github/workflows/ — DevOps incident automation is a high-value scenario with no clear template
2. Strengthen skip-if-match guidance in .github/aw/create-agentic-workflow.md — add a note prompting agents to suggest deduplication guards for scheduled workflows that create issues (common pattern, easy to miss)
3. Add a minimal Playwright visual regression example to .github/aw/github-agentic-workflows.md or a dedicated visual-regression.md shared snippet — Frontend Developer persona is underserved vs. Backend/DevOps

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Context

• Workflow Run: §24947677097
• Analysis Date: 2026-04-26
• Method: Static analysis of agent instruction files + existing workflow patterns (no live agent invocations — the agentic-workflows custom agent is not available as a sub-agent tool in this environment)

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[pelikhan]

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A newer discussion is available at Discussion #28655.