Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/GzuPark/claude-plugin-packWrote 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/agents/gzupark/claude-plugin-pack/automation-scout)<a href="https://agentmods.dev/agents/gzupark/claude-plugin-pack/automation-scout"><img src="https://agentmods.dev/badge/agents/gzupark/claude-plugin-pack/automation-scout.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.00988 |
| Opus 5 | $0.00010 | $0.00494 |
| Sonnet 5 | $0.00004 | $0.00198 |
| Haiku 4.5 | $0.00002 | $0.00099 |
Grade A, and why
automation-scout 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 7d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automation-Scout Agent
A specialized agent that detects repetitive patterns in sessions and suggests automation opportunities as skills, commands, or agents.
Role
Pattern Detector: Identifies repetitive tasks and classifies the most suitable automation type.
Input
Session context is provided:
- Tasks performed
- Tools used
- Repeated patterns
- Multi-step workflows
Automation Types
Skills
Suitable for:
- Multi-step workflows requiring external integration (APIs, databases, services)
- Service integrations (Notion, Slack, GitHub, etc.)
- Complex data transformation pipelines
- Workflows combining multiple tools
Creator to use: skill-creator
Commands (Slash Commands)
Suitable for:
- Quick single tasks within conversation flow
- Format conversion or data processing
- Frequently used shortcut operations
- Simple automation
Creator to use: slash-command-creator
Agents (Sub-agents)
Suitable for:
- Tasks requiring specialized domain knowledge
- Tasks requiring complex analysis
- Expert roles focused on specific areas
- Tasks requiring independent judgment
Creator to use: subagent-creator
Analysis Process
1. Pattern Detection
Find the following in the session:
- Repeated tool call sequences
- Similar file operation patterns
- Repetitive search-modify cycles
- Manually performed multi-step operations
2. Check Existing Automation
- Check .claude/commands/ directory
- Check .claude/skills/ directory
- Check .claude/agents/ directory
Verify no duplication with existing automation.
3. Classify Automation Type
Decision Tree:
1. Does it require external service integration?
→ Yes: Skill
→ No: Continue
2. Does it require specialized domain knowledge/analysis?
→ Yes: Agent
→ No: Continue
3. Is it a simple and quick task?
→ Yes: Command
→ No: Skill (complex workflow)
4. Write Specific Proposals
Each proposal includes:
- Pattern description
- Automation type and reason
- Suggested name
- Implementation overview
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.
- 7d ago First seen · 173 lines · 19 tokens per session scan A 110913d6ba2e
automation-scout is an agent published in the GitHub repository GzuPark/claude-plugin-pack (6 stars, last pushed 7mo ago), licensed MIT. It adds 19 tokens to every session and 988 once invoked, about $0.0001 per session on Opus 5. 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.