How do I install the Finops Workflows skill?

Run npx skillmds@latest add laurigates/finops-workflows in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Finops Workflows safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Finops Workflows?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Finops Workflows free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Finops Workflows?

laurigates (@laurigates) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Finops Workflows by laurigates — Agent Skill

Name: Finops Workflows
Rating: 4.2 (5 reviews)
Author: laurigates

File contents

/finops:workflows

Analyze GitHub Actions workflow runs for a repository - frequency, duration, success rates, and efficiency metrics.

When to Use This Skill

Use this skill when...	Use a sibling instead when...
You need to analyze workflow run frequency, duration, and trigger distribution	You only need a quick high-level health snapshot — use `/finops:overview`
You are investigating high failure rates on specific workflows	You want actionable fixes for workflow config waste — use `/finops:waste`
You need org-wide workflow timing analysis (`/finops:workflows org <name>`)	You want to compare workflow metrics across many repos — use `/finops:compare`
You want to identify slow or noisy workflows by duration	You are investigating cache size or stale caches — use `/finops:caches`

Context

Current repo URL: !git remote -v

Parameters

Parameter	Description	Default
`repo`	Repository in owner/name format	Current repository
`--created`	Date range filter (e.g., `>=2026-03-01`)	None (last 100 runs)
`org <name>`	Org-wide analysis (use instead of repo)	-

Execution

Per-repo analysis (default)

bash "${SKILL_DIR}/scripts/workflow-runs.sh" $ARGS

Org-wide analysis

When the user requests org-wide analysis, use the org script:

bash "${SKILL_DIR}/scripts/workflow-runs-org.sh" $ARGS

Output Format

Analyzing workflows for: org/repo

=== Active Workflows ===
  CI (id: 12345)
  Deploy (id: 12346)
  CodeQL (id: 12347)

=== Run Summary ===
CI:
  Total: 156 | Success: 140 | Failure: 10 | Cancelled: 4 | Skipped: 2
  Success rate: 89%
Deploy:
  Total: 45 | Success: 44 | Failure: 1 | Cancelled: 0 | Skipped: 0
  Success rate: 97%

=== Duration Analysis ===
CI:
  Runs: 50 | Avg: 4m32s | Max: 12m15s | Total: 226min
Deploy:
  Runs: 20 | Avg: 2m10s | Max: 3m45s | Total: 43min

=== Trigger Types ===
  push: 89 runs
  pull_request: 67 runs
  schedule: 30 runs
  workflow_dispatch: 5 runs

=== Recent Failures (last 10) ===
  #234 CI - 2025-01-28 - https://github.com/org/repo/actions/runs/...
  #231 CI - 2025-01-27 - https://github.com/org/repo/actions/runs/...

=== High Frequency Workflows ===
  CI: 156 runs (~5.2/day) - consider path filters

Agentic Optimizations

Context	Command
Workflow list (JSON)	`gh workflow list --json name,id,state`
Recent runs (compact)	`gh run list --workflow <name> --limit 20 --json status,conclusion,createdAt`
Failed runs only	`gh run list --status failure --limit 10 --json name,createdAt,url`
Run timing (JSON)	`gh api "/repos/{owner}/{repo}/actions/runs?per_page=50" --jq '.workflow_runs[]
Compact per-repo analysis	`bash "${SKILL_DIR}/scripts/workflow-runs.sh" $ARGS`
Org-wide analysis	`bash "${SKILL_DIR}/scripts/workflow-runs-org.sh" $ARGS`

Post-actions

Based on findings, suggest:

High failure rate -> Investigate recent failures, check logs with gh run view --log-failed
High frequency -> Review trigger conditions, add path filters
Long durations -> Review caching, parallelization, step optimization
Many skipped -> Run /finops:waste for detailed analysis

---name: finops-workflowsdescription: Analyze workflow runs — frequency, duration, success rates, efficiency. Use when investigating slow CI, high failure rates, or run patterns over time.--- # /finops:workflows Analyze GitHub Actions workflow runs for a repository - frequency, duration, success rates, and efficiency metrics. ## When to Use This Skill | Use this skill when... | Use a sibling instead when... | |---|---| | You need to analyze workflow run frequency, duration, and trigger distribution | You only need a quick high-level health snapshot — use `/finops:overview` | | You are investigating high failure rates on specific workflows | You want actionable fixes for workflow config waste — use `/finops:waste` | | You need org-wide workflow timing analysis (`/finops:workflows org <name>`) | You want to compare workflow metrics across many repos — use `/finops:compare` | | You want to identify slow or noisy workflows by duration | You are investigating cache size or stale caches — use `/finops:caches` | ## Context - Current repo URL: !`git remote -v` ## Parameters | Parameter | Description | Default | |-----------|-------------|---------| | `repo` | Repository in owner/name format | Current repository | | `--created` | Date range filter (e.g., `>=2026-03-01`) | None (last 100 runs) | | `org <name>` | Org-wide analysis (use instead of repo) | - | ## Execution ### Per-repo analysis (default) ```bash bash "${SKILL_DIR}/scripts/workflow-runs.sh" $ARGS ``` ### Org-wide analysis When the user requests org-wide analysis, use the org script: ```bash bash "${SKILL_DIR}/scripts/workflow-runs-org.sh" $ARGS ``` ## Output Format ``` Analyzing workflows for: org/repo === Active Workflows === CI (id: 12345) Deploy (id: 12346) CodeQL (id: 12347) === Run Summary === CI: Total: 156 | Success: 140 | Failure: 10 | Cancelled: 4 | Skipped: 2 Success rate: 89% Deploy: Total: 45 | Success: 44 | Failure: 1 | Cancelled: 0 | Skipped: 0 Success rate: 97% === Duration Analysis === CI: Runs: 50 | Avg: 4m32s | Max: 12m15s | Total: 226min Deploy: Runs: 20 | Avg: 2m10s | Max: 3m45s | Total: 43min === Trigger Types === push: 89 runs pull_request: 67 runs schedule: 30 runs workflow_dispatch: 5 runs === Recent Failures (last 10) === #234 CI - 2025-01-28 - https://github.com/org/repo/actions/runs/... #231 CI - 2025-01-27 - https://github.com/org/repo/actions/runs/... === High Frequency Workflows === CI: 156 runs (~5.2/day) - consider path filters ``` ## Agentic Optimizations | Context | Command | |---------|---------| | Workflow list (JSON) | `gh workflow list --json name,id,state` | | Recent runs (compact) | `gh run list --workflow <name> --limit 20 --json status,conclusion,createdAt` | | Failed runs only | `gh run list --status failure --limit 10 --json name,createdAt,url` | | Run timing (JSON) | `gh api "/repos/{owner}/{repo}/actions/runs?per_page=50" --jq '.workflow_runs[] | {name,created_at,updated_at,conclusion}'` | | Compact per-repo analysis | `bash "${SKILL_DIR}/scripts/workflow-runs.sh" $ARGS` | | Org-wide analysis | `bash "${SKILL_DIR}/scripts/workflow-runs-org.sh" $ARGS` | ## Post-actions Based on findings, suggest: - High failure rate -> Investigate recent failures, check logs with `gh run view --log-failed` - High frequency -> Review trigger conditions, add path filters - Long durations -> Review caching, parallelization, step optimization - Many skipped -> Run `/finops:waste` for detailed analysis

Frequently asked questions

Finops Workflows