Detects workflow failures and inefficient patterns then files GitHub issues. Use when a workflow step repeatedly fails or produces inconsistent output.
npx skills add https://github.com/athola/claude-night-market --skill workflow-monitor
superpowers:systematic-debugging)
sanctum:workflow-improvement)Monitor workflow executions for errors and inefficiencies, automatically creating issues on the detected git platform (GitHub/GitLab) for improvements. Check session context for git_platform: and use Skill(leyline:git-platform) for CLI command mapping.
Workflows should improve over time. When execution issues occur, capturing them systematically enables continuous improvement. This skill hooks into workflow execution to detect problems and propose fixes.
# After a failed workflow
/workflow-monitor --analyze-last
# Monitor a specific workflow execution
/workflow-monitor --session <session-id>
# Analyze efficiency of recent workflows
/workflow-monitor --efficiency-report
When enabled, workflow-monitor observes execution and flags:
| Pattern | Signal | Severity |
|---------|--------|----------|
| Command failure | Exit code > 0 | High |
| Timeout | Exceeded timeout limit | High |
| Retry loop | Same command >3 times | Medium |
| Context exhaustion | >90% context used | Medium |
| Tool misuse | Wrong tool for task | Low |
| Pattern | Signal | Threshold |
|---------|--------|-----------|
| Verbose output | >1000 lines from command | 500 lines recommended |
| Redundant reads | Same file read >2 times | 2 reads max |
| Sequential vs parallel | Independent tasks run sequentially | Should parallelize |
| Over-fetching | Read entire file when snippet needed | Use offset/limit |
workflow-monitor:capture-complete)workflow-monitor:analysis-complete)workflow-monitor:report-generated)workflow-monitor:issue-created)## Background
Detected during workflow execution on [DATE].
**Source:** [workflow name] session [session-id]
## Problem
[Description of the error or inefficiency]
**Evidence:**
[Command that failed or was inefficient]
[Output excerpt]
## Suggested Fix
[What should change to prevent this]
## Acceptance Criteria
- [ ] [Specific fix criterion]
- [ ] Tests added for new behavior
- [ ] Documentation updated
---
*Created automatically by workflow-monitor*
# .workflow-monitor.yaml
enabled: true
auto_create_issues: false # Require approval before creating
severity_threshold: "medium" # Only report medium+ severity
efficiency_threshold: 0.7 # Flag workflows below 70% efficiency
detection:
command_failures: true
timeouts: true
retry_loops: true
context_exhaustion: true
tool_misuse: true
efficiency:
verbose_output_limit: 500
max_file_reads: 2
parallel_detection: true
auto_create_issues: trueworkflow-monitor:capture-completeworkflow-monitor:analysis-completeworkflow-monitor:report-generatedworkflow-monitor:issue-created (if issue created)imbue:proof-of-work: Captures execution evidencesanctum:fix-workflow: Implements suggested fixes## Workflow Efficiency Report
**Session:** [session-id]
**Duration:** 12m 34s
**Efficiency Score:** 0.72 (72%)
### Issues Detected
| Type | Count | Impact |
|------|-------|--------|
| Verbose output | 3 | Medium |
| Redundant reads | 2 | Low |
| Sequential tasks | 1 | Medium |
### Recommendations
1. Use `--quiet` flags for npm/pip commands
2. Cache file contents instead of re-reading
3. Parallelize independent file operations
### Create Issues?
- [ ] Issue 1: Verbose output from npm install
- [ ] Issue 2: Redundant file reads in validation
imbue:proof-of-work: Evidence capture methodologysanctum:fix-workflow: Workflow improvement commandStatus: Skeleton implementation. Requires:
capture-complete,analysis-complete, report-generated, and (if an issue is
created) issue-created
command that failed or was inefficient plus an output excerpt
gh issue list --search beforecreating any issue; duplicate suppressed and existing issue
URL reported instead
how many anomalies are detected; rate limit enforced
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
> Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
Take athola/workflow-monitor from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npm.
Without those the skill loads but fails at the first command.