Borrowing it
Nothing to install: this file belongs to pskoett/measuring-ai-proficiency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pskoett/measuring-ai-proficiency/main/.claude/skills/agentic-workflow/SKILL.mdgit clone --depth 1 https://github.com/pskoett/measuring-ai-proficiencyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pskoett/measuring-ai-proficiency/agentic-workflow)<a href="https://agentmods.dev/skills/pskoett/measuring-ai-proficiency/agentic-workflow"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/agentic-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pskoett/measuring-ai-proficiency/agentic-workflow"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/agentic-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00930 |
| Opus 5.5 | $0.00000 | $0.00372 |
| Sonnet 5.5 | $0.00000 | $0.00186 |
| Haiku 4.5 | $0.00000 | $0.00093 |
Grade A, and why
agentic-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Workflow Creator
Create natural language GitHub Actions workflows using the agentic workflows pattern from GitHub Next.
Description
This skill creates markdown-based agentic workflows that can be compiled to GitHub Actions YAML. Instead of writing traditional scripts, you describe repository behaviors in plain language.
Usage
/agentic-workflow <task description>
Or invoke with specific parameters:
/agentic-workflow --trigger "issue opened" --task "triage and label issues"
Workflow Structure
Agentic workflows use this markdown format:
# Workflow Name
Brief description of what this workflow does.
## Triggers
- on: [trigger events]
## Permissions
- issues: write
- pull-requests: write
- contents: read
## Safe-outputs
- Maximum 1 pull request per run
- Only modify files in specific directories
## Tools
- edit: Modify files in the repository
- web-fetch: Fetch external documentation
- web-search: Search for solutions
## Instructions
Natural language instructions for the agent to follow.
Be specific about:
- What to look for
- How to make decisions
- What actions to take
- When to stop or escalate
Best Use Cases
Agentic workflows work best for:
- Issue Triage - Auto-label, assign, and categorize issues
- Quality Assurance - Propose tests for uncovered code paths
- Accessibility - Scan and suggest WCAG fixes
- Documentation - Sync docs with code changes
- Dependency Updates - Review and merge safe updates
- Code Review - Automated first-pass reviews
Examples
Issue Labeler
# Auto-Label Issues
Automatically categorize and label new issues based on content.
## Triggers
- on: issues.opened
## Permissions
- issues: write
## Safe-outputs
- Maximum 3 labels per issue
- Never close issues automatically
## Tools
- None required (uses GitHub API only)
## Instructions
When a new issue is opened:
1. Read the issue title and body
2. Categorize as: bug, feature, question, or documentation
3. Add appropriate labels:
- `bug` for error reports and broken functionality
- `enhancement` for feature requests
- `question` for help requests
- `docs` for documentation issues
4. Add priority label if keywords suggest urgency:
- `priority:high` if contains "critical", "urgent", "blocking"
- `priority:low` if contains "minor", "nice-to-have"
5. Add component labels based on file paths mentioned
6. Comment acknowledging the issue was triaged
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 175 lines · 0 tokens per session scan A 048265729999
agentic-workflow is a skill published in the GitHub repository pskoett/measuring-ai-proficiency (13 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 930 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
agentic-workflow compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| agentic-workflowpskoett/measuring-ai-proficiency | Skill | 13 | 3mo ago | MIT | A | 0 | Claude Code |
| chinese-git-workflowjnMetaCode/superpowers-zh | Skill | 8.5k | 11d ago | MIT | A | 69 | Claude Code |
| atmos-profilescloudposse/atmos | Skill | 1.4k | yesterday | Apache-2.0 | A | 35 | Claude Code |
| webhook-managementhoangsonww/Claude-Code-Agent-Monitor | Skill | 1.1k | yesterday | MIT | A | 56 | Claude Code, Codex |
| monorepo-managementwshobson/agents | Skill | 42k | yesterday | MIT | C | 54 | Claude Code |
| managing-github-actions-secretsPostHog/posthog-foss | Skill | 728 | yesterday | MIT | A | 67 | Claude Code, Codex |
| postman-newman-automationLambdaTest/agent-skills | Skill | 390 | yesterday | MIT | A | 156 | Claude Code, Codex |