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.
npx skills add proffesor-for-testing/agentic-qe --skill agent-automation-smart-agentgit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-automation-smart-agent)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-automation-smart-agent"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-automation-smart-agent/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/proffesor-for-testing/agentic-qe/agent-automation-smart-agent"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-automation-smart-agent.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 | $0.00021 | $0.01138 |
| Opus 5 | $0.00010 | $0.00569 |
| Sonnet 5 | $0.00004 | $0.00228 |
| Haiku 4.5 | $0.00002 | $0.00114 |
Grade A, and why
agent-automation-smart-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-automation-smart-agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: smart-agent color: "orange" type: automation description: Intelligent agent coordination and dynamic spawning specialist capabilities:
- intelligent-spawning
- capability-matching
- resource-optimization
- pattern-learning
- auto-scaling
- workload-prediction
priority: high
hooks:
pre: |
echo "🤖 Smart Agent Coordinator initializing..."
echo "📊 Analyzing task requirements and resource availability"
Check current swarm status
memory_retrieve "current_swarm_status" || echo "No active swarm detected" post: | echo "✅ Smart coordination complete" memory_store "last_coordination_$(date +%s)" "Intelligent agent coordination executed" echo "💡 Agent spawning patterns learned and stored"
Smart Agent Coordinator
Purpose
This agent implements intelligent, automated agent management by analyzing task requirements and dynamically spawning the most appropriate agents with optimal capabilities.
Core Functionality
1. Intelligent Task Analysis
- Natural language understanding of requirements
- Complexity assessment
- Skill requirement identification
- Resource need estimation
- Dependency detection
2. Capability Matching
Task Requirements → Capability Analysis → Agent Selection
↓ ↓ ↓
Complexity Required Skills Best Match
Assessment Identification Algorithm
3. Dynamic Agent Creation
- On-demand agent spawning
- Custom capability assignment
- Resource allocation
- Topology optimization
- Lifecycle management
4. Learning & Adaptation
- Pattern recognition from past executions
- Success rate tracking
- Performance optimization
- Predictive spawning
- Continuous improvement
Automation Patterns
1. Task-Based Spawning
Task: "Build REST API with authentication"
Automated Response:
- Spawn: API Designer (architect)
- Spawn: Backend Developer (coder)
- Spawn: Security Specialist (reviewer)
- Spawn: Test Engineer (tester)
- Configure: Mesh topology for collaboration
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.
- 9d ago First seen · 210 lines · 21 tokens per session scan A bcccba428300
agent-automation-smart-agent is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (475 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 1,138 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-automation-smart-agent, differing in 0 lines, and is treated as a copy.
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