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/zate/cc-plugins/run-swarmnpx skills add Zate/cc-plugins --skill run-swarmgit clone --depth 1 https://github.com/Zate/cc-pluginsWrote 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/zate/cc-plugins/run-swarm)<a href="https://agentmods.dev/skills/zate/cc-plugins/run-swarm"><img src="https://agentmods.dev/badge/skills/zate/cc-plugins/run-swarm.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 | $0.00017 | $0.01797 |
| Opus 5 | $0.00009 | $0.00898 |
| Sonnet 5 | $0.00003 | $0.00359 |
| Haiku 4.5 | $0.00002 | $0.00180 |
Grade A, and why
run-swarm 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 3d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Devloop Run Swarm
Execute plan tasks via fresh-context subagents. You are the orchestrator.
Bash hygiene: prefer quiet flags to minimize output (npm install --silent, git status -sb, pipe long output through | tail -n 20).
Monitor for validation commands: When the orchestrator runs test or build commands to validate phase completion, use Monitor for real-time streaming. Worker agents (swarm-worker, haiku-worker) also have Monitor available and should use it for long-running commands within their tasks.
Long-running commands that warrant Monitor: test suites (npm test, pytest, go test ./..., cargo test, make test), builds (npm run build, make, cargo build, tsc), and full-codebase linting (eslint ., ruff check ., golangci-lint run).
Orchestrator validation example:
Monitor({ description: "swarm validation tests", command: "npm test 2>&1 | grep --line-buffered -E 'PASS|FAIL|Error|passed|failed'", timeout_ms: 300000, persistent: false })
Fallback: if Monitor errors, use Bash directly.
Step 1: Check Plan State
Run ${CLAUDE_PLUGIN_ROOT}/scripts/check-plan-complete.sh .devloop/plan.md.
- No plan: Show entry points (
/devloop:plan) and STOP. - Complete: AskUserQuestion: Ship it, Archive, or Review. STOP.
- Pending: Continue to Step 2.
Step 2: Parse Arguments
--max-tasks N: Max tasks before pausing.--dry-run: List pending tasks and STOP.--worktrees: Run each worker withisolation: "worktree". Each worker gets an isolated git worktree; the orchestrator merges results back after each batch. Off by default.
Also read the local config to detect git.worktree_isolation:
Bash: ${CLAUDE_PLUGIN_ROOT}/scripts/parse-local-config.sh
If git.worktree_isolation is true in the config, treat it as if --worktrees was passed.
The CLI flag always wins: --worktrees enables isolation regardless of config.
Step 3: Gather Shared Context
Extract max 100 lines from CLAUDE.md (code style, patterns) and plan's Overview/Considerations. Store as shared context.
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.
- 3d ago First seen · 160 lines · 17 tokens per session scan A d0fcb1950370
run-swarm is a skill published in the GitHub repository Zate/cc-plugins (10 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 1,797 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…