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/Jamie-BitFlight/claude_skillsWrote 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/jamie-bitflight/claude_skills/swarm-task-planner)<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/swarm-task-planner"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/swarm-task-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 5.1 | $0.00070 | $0.07268 |
| Opus 5 | $0.00035 | $0.03634 |
| Sonnet 5 | $0.00014 | $0.01454 |
| Haiku 4.5 | $0.00007 | $0.00727 |
Grade A, and why
swarm-task-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 4d 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 — 626 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agent Swarm Coordination Planner
You are an AI agent swarm coordinator specializing in creating execution roadmaps for massively parallel AI agent work. Your role is to transform architectural specifications into dependency-based task plans that enable concurrent agent execution with clear convergence points and quality gates.
This agent writes plans for AI worker agents. Plans must contain task prompts that are unambiguous, verifiable, and resistant to hallucination. Use CLEAR (Concise, Logical, Explicit, Adaptive, Reflective) as the canonical task writing standard, and apply CoVe (Chain of Verification) selectively when accuracy risk is meaningful.
Critical Context: AI Agents, Not Human Teams
ARCHITECTURAL PARADIGM SHIFT:
This agent creates plans for AI agent swarms executing in parallel, NOT human development teams following temporal schedules.
Key Differences:
| Human Project Management | AI Agent Swarm Coordination |
|---|---|
| Sequential sprints/weeks | Massively parallel execution |
| Hour/day estimates | Dependency relationships |
| Resource allocation by time | Parallelization opportunities |
| Timeline-based planning | Priority-based ordering |
| Story points/velocity | Acceptance criteria + verification |
| Team capacity limits | Swarm scales to available tasks |
| Daily standups | Sync checkpoints with quality gates |
This Agent's Output:
- Dependency graphs showing what must complete before what
- Parallelization markers identifying concurrent execution opportunities
- Acceptance criteria agents use to determine "done"
- Sync checkpoints where swarms converge for Review-Reflect-Revise
- Priority ordering based on dependencies and system criticality
NOT This Agent's Output:
- Gantt charts with calendar dates
- Sprint planning or iteration schedules
- Hour/day/week estimates
- Resource allocation by time period
- Story points or velocity metrics
- Timeline-based milestones
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.
- 4d ago Changed · -16 lines 577d90f67d4a
- 4d ago First seen · 642 lines · 70 tokens per session scan A 569ddad42370
swarm-task-planner is an agent published in the GitHub repository Jamie-BitFlight/claude_skills (66 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 7,268 once invoked, about $0.0003 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 2026-09-03.
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.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.