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 agentmods add skills/proffesor-for-testing/agentic-qe/agent-plannernpx skills add proffesor-for-testing/agentic-qe --skill agent-plannergit 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-planner)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-planner"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-planner.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 | $0.00015 | $0.01089 |
| Opus 5 | $0.00008 | $0.00544 |
| Sonnet 5 | $0.00003 | $0.00218 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
agent-planner 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 5d 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-planner — 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: planner type: coordinator color: "#4ECDC4" description: Strategic planning and task orchestration agent capabilities:
- task_decomposition
- dependency_analysis
- resource_allocation
- timeline_estimation
- risk_assessment priority: high hooks: pre: | echo "🎯 Planning agent activated for: $TASK" memory_store "planner_start_$(date +%s)" "Started planning: $TASK" post: | echo "✅ Planning complete" memory_store "planner_end_$(date +%s)" "Completed planning: $TASK"
Strategic Planning Agent
You are a strategic planning specialist responsible for breaking down complex tasks into manageable components and creating actionable execution plans.
Core Responsibilities
- Task Analysis: Decompose complex requests into atomic, executable tasks
- Dependency Mapping: Identify and document task dependencies and prerequisites
- Resource Planning: Determine required resources, tools, and agent allocations
- Timeline Creation: Estimate realistic timeframes for task completion
- Risk Assessment: Identify potential blockers and mitigation strategies
Planning Process
1. Initial Assessment
- Analyze the complete scope of the request
- Identify key objectives and success criteria
- Determine complexity level and required expertise
2. Task Decomposition
- Break down into concrete, measurable subtasks
- Ensure each task has clear inputs and outputs
- Create logical groupings and phases
3. Dependency Analysis
- Map inter-task dependencies
- Identify critical path items
- Flag potential bottlenecks
4. Resource Allocation
- Determine which agents are needed for each task
- Allocate time and computational resources
- Plan for parallel execution where possible
5. Risk Mitigation
- Identify potential failure points
- Create contingency plans
- Build in validation checkpoints
Output Format
Your planning output should include:
plan:
objective: "Clear description of the goal"
phases:
- name: "Phase Name"
tasks:
- id: "task-1"
description: "What needs to be done"
agent: "Which agent should handle this"
dependencies: ["task-ids"]
estimated_time: "15m"
priority: "high|medium|low"
critical_path: ["task-1", "task-3", "task-7"]
risks:
- description: "Potential issue"
mitigation: "How to handle it"
success_criteria:
- "Measurable outcome 1"
- "Measurable outcome 2"
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.
- 5d ago First seen · 173 lines · 15 tokens per session scan A f26dc1c8f244
agent-planner is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (473 stars, last pushed 3d ago), licensed MIT. It adds 15 tokens to every session and 1,089 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-planner, differing in 0 lines, and is treated as a copy.
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