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 AnmarHani/SwarmVault --skill swarm-orchestrategit clone --depth 1 https://github.com/AnmarHani/SwarmVaultWrote 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/anmarhani/swarmvault/swarm-orchestrate)<a href="https://agentmods.dev/skills/anmarhani/swarmvault/swarm-orchestrate"><img src="https://agentmods.dev/badge/skills/anmarhani/swarmvault/swarm-orchestrate/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/anmarhani/swarmvault/swarm-orchestrate"><img src="https://agentmods.dev/badge/skills/anmarhani/swarmvault/swarm-orchestrate.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 | $0.00109 | $0.07127 |
| Opus 5.5 | $0.00044 | $0.02851 |
| Sonnet 5.5 | $0.00022 | $0.01425 |
| Haiku 4.5 | $0.00011 | $0.00713 |
Grade A, and why
swarm-orchestrate 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 1mo 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 — 485 lines — stays where its author put it; the contents beside it link to each section on GitHub.
swarm-orchestrate — optional local autonomy
Gate: this add-on is disabled by default. Do not enable it, configure write access, or start workers unless the user explicitly asks. Tickets and atomic claims remain the source of truth; signals and controls never override a healthy claim.
What this is for (read before configuring anything)
The goal is the right model on the right task, at the lowest token cost — parallelism is only one means to that end, and often not the right one. So orchestration has two separate decisions, and conflating them is the classic mistake:
- Fit — always on, at every level. Which platform, model, and reasoning effort each task deserves, from its kind (design / planning / coding / review / docs), its size, and each platform's remaining usage. A docs ticket never burns a flagship model; a design ticket never gets a cheap one. This is not something the user buys by going slower.
- Acceleration — the speed level, and the only thing the user chooses. How eagerly work is handed to other agents instead of done in the current session.
Enable — two design questions, then the numbers only they can see
- Confirm the project is registered and has dependency-ready tickets.
- Ask the two design questions:
- "Which agentic platforms do you have?" — the tools installed on their machine:
claude-code,codex(verified),gemini,opencode,droid,cursor,copilot,amp(best-effort), or any other agent CLI by name. Offer the list and an "other" option; a platform with no adapter still works as a cooperative worker, or gets a--launch-cmdtemplate. - "How much acceleration is allowed?" —
slow|standard|fast(below). Plus: may these workers edit code?
- "Which agentic platforms do you have?" — the tools installed on their machine:
- Never ask for a worker count, a concurrency ceiling, or a model name. Those are not the user's decisions: ceilings derive from the level, and the platform+model per task come from fit. Asking for a model produces exactly the wrong answer — one model cannot be right for both a large design task and a docs chore.
- Do ask for the usage numbers — you cannot read them. Per platform: which plan are you
on · what limits does it show (per session/day, per week, both) · when do they reset · are
any other sessions running I can't see · may I schedule a continuation automatically if a
limit is about to run out? Look up per-model costs yourself first; ask only if the lookup
fails. See Usage — you are blind without the user below; the full interview and the
per-platform notes are in
references/usage-limits.md. - One command:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 485 lines · 109 tokens per session scan A 513ec6c1a06f
swarm-orchestrate is a skill published in the GitHub repository AnmarHani/SwarmVault (5 stars, last pushed 2mo ago), licensed MIT. It adds 109 tokens to every session and 7,127 once invoked, about $0.0004 per session on Opus 5.5. 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 skills, from other repositories
podcast-generation
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
agent-topology-optimizer
Agent skill for topology-optimizer - invoke with $agent-topology-optimizer.
agent-workflow-automation
Agent skill for workflow-automation - invoke with $agent-workflow-automation.
agent-pagerank-analyzer
Agent skill for pagerank-analyzer - invoke with $agent-pagerank-analyzer.
agent-release-manager
Agent skill for release-manager - invoke with $agent-release-manager.
agent-repo-architect
Agent skill for repo-architect - invoke with $agent-repo-architect.