Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jmylchreest/aidenpx agentmods add skills/jmylchreest/aide/plan-swarmWrote 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/jmylchreest/aide/plan-swarm)<a href="https://agentmods.dev/skills/jmylchreest/aide/plan-swarm"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/plan-swarm/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/jmylchreest/aide/plan-swarm"><img src="https://agentmods.dev/badge/skills/jmylchreest/aide/plan-swarm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00011 | $0.01233 |
| Opus 5 | $0.00005 | $0.00616 |
| Sonnet 5 | $0.00002 | $0.00247 |
| Haiku 4.5 | $0.00001 | $0.00123 |
Grade A, and why
plan-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 10d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Swarm
Recommended model tier: smart (opus) - this skill requires careful reasoning
Structured planning interview to decompose work into independent stories before running a swarm.
Quick Reference
plan swarm → Full interview workflow (recommended)
plan swarm --fast → Skip interview, state assumptions, decompose directly
Workflow
Phase 1: Understand
Explore the codebase and existing context before asking questions.
- Read existing decisions via
mcp__plugin_aide_aide__decision_listandmcp__plugin_aide_aide__decision_get - Search memories via
mcp__plugin_aide_aide__memory_searchfor relevant past context - Explore the codebase — read key files, understand architecture, identify boundaries
- Identify the scope — what is the user asking for? What are the natural boundaries?
Do NOT ask questions yet. Build understanding first.
Phase 2: Interview
Conduct 2-3 rounds of focused questions. Each round has 2-4 questions. Max 3 rounds total.
Round 1: Scope & Boundaries
- What is in scope vs out of scope?
- What are the success criteria?
- Are there any constraints (time, tech, compatibility)?
Round 2: Dependencies & Risks
- What shared state or files will multiple stories touch?
- What could go wrong? What are the risky parts?
- Are there external dependencies (APIs, services, data)?
Round 3: Acceptance Criteria (if needed)
- How will we know each story is done?
- What tests should exist?
- What does "good enough" look like?
Use the AskUserQuestion tool for each round. Summarize what you've learned before asking the next round.
Fast mode (plan swarm --fast): Skip this phase. State your assumptions explicitly, then proceed directly to Phase 3.
Phase 3: Decompose
Output a structured story list. Each story must be:
- Independent — can be developed in parallel without conflicting file edits
- Complete — has clear boundaries and acceptance criteria
- Testable — has concrete verification steps
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.
- 10d ago First seen · 156 lines · 11 tokens per session scan A 96ee85c6d7a5
plan-swarm is a skill published in the GitHub repository jmylchreest/aide (17 stars, last pushed 3d ago), licensed MIT. It adds 11 tokens to every session and 1,233 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 2026-08-30.
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