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 commands/liortesta/clawdagent/swarmgit clone --depth 1 https://github.com/liortesta/ClawdAgentWrote 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/commands/liortesta/clawdagent/swarm)<a href="https://agentmods.dev/commands/liortesta/clawdagent/swarm"><img src="https://agentmods.dev/badge/commands/liortesta/clawdagent/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 | $0.00000 | $0.00947 |
| Opus 5 | $0.00000 | $0.00474 |
| Sonnet 5 | $0.00000 | $0.00189 |
| Haiku 4.5 | $0.00000 | $0.00095 |
Grade A, and why
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 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Swarm Mode — Coordinated Agent Team
Launch a coordinated multi-agent team with a shared task board and Leader→Workers pattern.
Process:
1. Task Analysis
- Break the task into independent, parallelizable sub-tasks
- Identify dependencies between sub-tasks
- Assign each sub-task a priority (P0=blocker, P1=critical, P2=normal)
2. Team Assembly
Choose the right team pattern:
Leader→Workers (default):
- 1 Leader agent (CTO or Architect) coordinates
- 2-5 Worker agents execute in parallel
- Leader reviews all output before merging
Ensemble (for review/debugging):
- 3-5 agents work on the SAME problem independently
- Compare results, pick best or synthesize
Pipeline (for sequential work):
- Each agent handles one stage, passes output to next
- Stage 1: Design → Stage 2: Implement → Stage 3: Test → Stage 4: Review
3. Task Board
Create a shared task board:
## SWARM TASK BOARD
| # | Task | Assignee | Status | Branch | Depends On |
|---|------|----------|--------|--------|-----------|
| 1 | ... | agent-1 | pending | feat/task-1 | - |
| 2 | ... | agent-2 | pending | feat/task-2 | - |
| 3 | ... | agent-3 | pending | feat/task-3 | 1,2 |
4. Execution
- Spawn agents in parallel using subagents or agent teams
- Each agent works in its own git branch (or worktree if available)
- Use @mentions to request help: "@security-auditor review this auth logic"
- Leader monitors progress and resolves conflicts
5. Integration
- Leader reviews all completed tasks
- Merge branches in dependency order
- Run /ship to verify everything works together
- Resolve any integration conflicts
Team Templates:
Full Stack Feature
Leader: CTO
Workers:
- architect → API design + DB schema
- dev-backend → API implementation
- dev-frontend → UI implementation
- qa-engineer → Tests for all layers
- security-auditor → Real-time audit
Bug Investigation
Pattern: Ensemble (3 investigators)
- Agent A: Top-down (start from error, trace back)
- Agent B: Bottom-up (start from data, trace forward)
- Agent C: Bisect (git bisect to find breaking commit)
→ Compare findings, identify root cause
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 First seen · 127 lines · 0 tokens per session scan A 36937aa78a4e
swarm is a command published in the GitHub repository liortesta/ClawdAgent (11 stars, last pushed 7d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 947 tokens. 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.