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/stophobia/deerflow2.0-enhanced/bootstrapnpx skills add stophobia/deerflow2.0-enhanced --skill bootstrapgit clone --depth 1 https://github.com/stophobia/deerflow2.0-enhancedWrote 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/stophobia/deerflow2.0-enhanced/bootstrap)<a href="https://agentmods.dev/skills/stophobia/deerflow2.0-enhanced/bootstrap"><img src="https://agentmods.dev/badge/skills/stophobia/deerflow2.0-enhanced/bootstrap.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 | $0.00114 | $0.01101 |
| Opus 5 | $0.00057 | $0.00550 |
| Sonnet 5 | $0.00023 | $0.00220 |
| Haiku 4.5 | $0.00011 | $0.00110 |
Grade A, and why
bootstrap 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.
This is a copy
100% identical to bootstrap — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bootstrap Soul
A conversational onboarding skill. Through 5–8 adaptive rounds, extract who the user is and what they need, then generate a tight SOUL.md that defines their AI partner.
Architecture
bootstrap/
├── SKILL.md ← You are here. Core logic and flow.
├── templates/SOUL.template.md ← Output template. Read before generating.
└── references/conversation-guide.md ← Detailed conversation strategies. Read at start.
Before your first response, read both:
references/conversation-guide.md— how to run each phasetemplates/SOUL.template.md— what you're building toward
Ground Rules
- One phase at a time. 1–3 questions max per round. Never dump everything upfront.
- Converse, don't interrogate. React genuinely — surprise, humor, curiosity, gentle pushback. Mirror their energy and vocabulary.
- Progressive warmth. Each round should feel more informed than the last. By Phase 3, the user should feel understood.
- Adapt pacing. Terse user → probe with warmth. Verbose user → acknowledge, distill, advance.
- Never expose the template. The user is having a conversation, not filling out a form.
Conversation Phases
The conversation has 4 phases. Each phase may span 1–3 rounds depending on how much the user shares. Skip or merge phases if the user volunteers information early.
| Phase | Goal | Key Extractions |
|---|---|---|
| 1. Hello | Language + first impression | Preferred language |
| 2. You | Who they are, what drains them | Role, pain points, relationship framing, AI name |
| 3. Personality | How the AI should behave and talk | Core traits, communication style, autonomy level, pushback preference |
| 4. Depth | Aspirations, blind spots, dealbreakers | Long-term vision, failure philosophy, boundaries |
Phase details and conversation strategies are in references/conversation-guide.md.
Extraction Tracker
Mentally track these fields as the conversation progresses. You need all required fields before generating.
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.
- 4d ago First seen · 89 lines · 0 tokens per session scan A d83f595e0803
bootstrap is a skill published in the GitHub repository stophobia/deerflow2.0-enhanced (719 stars, last pushed 5mo ago), licensed MIT. It adds 114 tokens to every session and 1,101 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bootstrap, differing in 8 lines, and is treated as a copy.
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…