📊 Agentic Workflow Lock File Statistics - 2025-12-18

[github-actions[bot]]

This comprehensive analysis examines 237 lock files across the githubnext/gh-aw repository to understand the structure, patterns, and characteristics of agentic workflows in production.

Executive Summary

• Total Lock Files Analyzed: 237
• Total Size: 86.61 MB
• Average File Size: 374.20 KB
• Most Common Trigger: workflow_dispatch (204 workflows)
• Typical Structure: ~6.5 jobs per workflow, ~10.5 steps per job
• Workflows with Manual Trigger: 204 (86.1%)

Full Report Details

File Size Distribution

The lock files in this repository vary significantly in size, reflecting the complexity and scope of different agentic workflows.

Size Range	Count	Percentage
< 100 KB	2	0.8%
100-200 KB	10	4.2%
200-400 KB	125	52.7%
400-600 KB	98	41.4%
> 600 KB	2	0.8%

Statistics:

• Smallest: arxiv.lock.yml (80.2 KB)
• Largest: poem-bot.lock.yml (692.6 KB)
• Median: 381.1 KB
• Standard Deviation: 80.9 KB

Trigger Analysis

Most Popular Triggers

Workflow triggers determine when agentic workflows execute. The analysis reveals strong preferences for scheduled and manual execution patterns.

Trigger Type	Count	Percentage	Description
workflow_dispatch	204	86.1%	Manual trigger via GitHub UI or API
schedule	150	63.3%	Cron-based scheduled execution
pull_request	30	12.7%	Triggered on PR events
issue_comment	30	12.7%	Triggered on issue comments
issues	23	9.7%	Triggered on issue events
pull_request_review_comment	12	5.1%	Triggered on PR review comments
discussion	10	4.2%	Triggered on discussion events
discussion_comment	12	5.1%	Triggered on discussion comments

Common Trigger Combinations

Many workflows combine multiple triggers for flexibility:

1. schedule + workflow_dispatch: 134 workflows (56.5%)
2. workflow_dispatch: 38 workflows (16.0%)
3. pull_request + schedule + workflow_dispatch: 14 workflows (5.9%)
4. discussion + discussion_comment + issue_comment + issues + pull_request + pull_request_review_comment: 6 workflows (2.5%)
5. issues: 5 workflows (2.1%)
6. pull_request + workflow_dispatch: 4 workflows (1.7%)
7. issue_comment: 4 workflows (1.7%)
8. workflow_run: 4 workflows (1.7%)
9. issue_comment + issues + workflow_dispatch: 2 workflows (0.8%)
10. workflow_call: 2 workflows (0.8%)

Schedule Patterns

150 workflows use cron-based scheduling. Here are the most common schedules:

Cron Expression	Count	Description
0 9 * * *	14	Daily at 9:00 AM
0 14 * * 1-5	10	Weekdays at 2:00 PM
0 8 * * *	8	Daily at 8:00 AM
0 13 * * 1-5	8	Weekdays at 1:00 PM
0 11 * * 1-5	8	Weekdays at 11:00 AM
0 0,6,12,18 * * *	6	Every 6 hours (midnight, 6am, noon, 6pm)
0 9 * * 1	6	Mondays at 9:00 AM
0 10 * * 1-5	4	Weekdays at 10:00 AM
0 3 * * *	4	Custom schedule
0 9 * * 1-5	4	Custom schedule
0 15 * * 1-5	4	Weekdays at 3:00 PM
0 18 * * *	4	Daily at 6:00 PM
0 0 * * *	4	Daily at midnight
0 */6 * * *	4	Every 6 hours
0 0,7,13,19 * * *	4	Custom schedule

Key Insights:

• 8 workflows run only on weekdays (Monday-Friday)
• 10 workflows run every 6 hours or at 6-hour intervals
• 28 workflows prefer 9:00 AM execution time
• Most scheduled workflows run during business hours (7 AM - 6 PM)

Structural Characteristics

Job Complexity

Agentic workflows in this repository exhibit consistent structural patterns:

• Average Jobs per Workflow: 6.49
• Average Steps per Job: 10.46
• Maximum Steps in Single Job: 56 steps
• Minimum Steps: 1 steps
• Median Jobs per Workflow: 6.0

Distribution of Jobs per Workflow

Jobs	Workflows	Percentage
2	6	2.5%
3	4	1.7%
4	4	1.7%
5	45	19.0%
6	72	30.4%
7	52	21.9%
8	32	13.5%
9	14	5.9%
10	6	2.5%
18	2	0.8%

Average Lock File Structure

Based on statistical analysis, a typical .lock.yml file has:

• Size: ~374 KB (0.37 MB)
• Jobs: ~6 jobs (usually between 5 and 7)
• Steps per Job: ~10 steps (ranging from 1 to 56)
• Triggers: Combined schedule + workflow_dispatch (most common pattern)
• Timeout: 10 minutes (standard across all workflows)

Permission Patterns

Lock files explicitly declare GitHub API permissions for security. The analysis reveals:

Permission	Count	Description
contents: read	6	Read repository contents
actions: read	4	Read workflow run data
issues: write	1	Create and modify issues

Security Note: Most workflows operate with minimal contents:read permissions, following the principle of least privilege.

MCP Servers & Tool Patterns

Agentic workflows leverage Model Context Protocol (MCP) servers to extend agent capabilities:

MCP Server	References	Usage Pattern
github	7924	GitHub API operations (issues, PRs, repos)
brave-search	90	Web search and research

Key Insight: The github MCP server is overwhelmingly the most used, appearing in virtually every workflow for GitHub API interactions.

Timeout Configuration

• Standard Timeout: 10 minutes per job
• Total Jobs Analyzed: 605
• Consistency: 99.8% of jobs use the standard 10-minute timeout
• Exceptions: 1 jobs use different timeouts

Concurrency Patterns

Workflows use concurrency groups to prevent multiple simultaneous runs:

Concurrency Pattern	Count	Use Case
gh-aw-${{ github.workflow }}	174	Global workflow concurrency
`gh-aw-${{ github.workflow }}-${{ github.event.issue.number		github.event.pull_request.number }}`
`gh-aw-${{ github.workflow }}-${{ github.event.pull_request.number		github.ref }}`
gh-aw-${{ github.workflow }}-${{ github.event.issue.number }}	9	Per-issue concurrency
gh-aw-${{ github.workflow }}-${{ github.ref }}	2	Per-branch concurrency
tidy-${{ github.ref }}	2	Per-branch concurrency
${{ github.workflow }}-${{ github.ref }}-cloclo	2	Per-branch concurrency

Most Common Pattern: gh-aw-${{ github.workflow }} - ensures only one instance of each workflow runs at a time globally.

Interesting Findings

1. High Manual Intervention Rate: 86.1% of workflows support manual triggering, indicating these agents are designed for on-demand execution alongside automation.

2. Scheduled Automation Dominance: 150 workflows (63.3%) run on schedules, with a strong preference for business hours and weekday execution.

3. Consistent Timeout Strategy: 99.8% standardization on 10-minute timeouts suggests careful tuning for agent response times.

4. File Size Growth: The largest lock file (693 KB) is 8.6x larger than the smallest (80.2 KB), reflecting a wide range of workflow complexity.

5. Structural Consistency: Despite size variations, workflows maintain consistent structure (~6 jobs, ~10 steps per job), suggesting established patterns and best practices.

6. GitHub-Centric Operations: The GitHub MCP server appears 7924 times across workflows, highlighting that most agentic workflows operate primarily within the GitHub ecosystem.

7. Test Infrastructure: 7 lock files are in test directories, demonstrating significant investment in workflow testing.

Recommendations

Based on this analysis, here are recommendations for agentic workflow development:

1. Size Optimization: Consider splitting workflows exceeding 500 KB into smaller, focused workflows for better maintainability.

2. Schedule Coordination: With many workflows scheduled at popular times (9 AM, 2 PM), consider staggering schedules to reduce concurrent execution pressure.

3. Timeout Tuning: The consistent 10-minute timeout works well, but consider extending for known long-running operations or reducing for quick checks.

4. Trigger Patterns: The combination of schedule + workflow_dispatch provides excellent flexibility - recommend as standard pattern for new workflows.

5. Documentation: With 237 unique workflows, maintaining a workflow inventory/catalog would improve discoverability and reduce duplication.

6. Safe Outputs: Consider standardizing on safe output patterns across workflows for consistent results handling.

Methodology

• Analysis Tool: Python 3 with PyYAML for YAML parsing
• Lock Files Analyzed: 237 files
• Data Collection: Automated parsing of all .lock.yml files in .github/workflows/
• Cache Memory: Scripts and data stored in /tmp/gh-aw/cache-memory/ for reuse
• Analysis Date: 2025-12-18 14:57 UTC

Repository Structure

Lock files are organized as:

• Root workflows: .github/workflows/*.lock.yml (228 files)
• Test workflows: .github/workflows/tests/*.lock.yml (7 files)
• Shared configs: .github/workflows/shared/**/*.lock.yml (2 files)

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Analysis generated by Lockfile Statistics Analysis Agent on 2025-12-18 at 14:57 UTC
Data source: All .lock.yml files in githubnext/gh-aw repository

AI generated by Lockfile Statistics Analysis Agent

[github-actions[bot]]

This discussion was automatically closed because it was created by an agentic workflow more than 3 days ago.