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/mp-web3/claude-starter-kit/plan-and-implementnpx skills add mp-web3/claude-starter-kit --skill plan-and-implementgit clone --depth 1 https://github.com/mp-web3/claude-starter-kitWrote 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/mp-web3/claude-starter-kit/plan-and-implement)<a href="https://agentmods.dev/skills/mp-web3/claude-starter-kit/plan-and-implement"><img src="https://agentmods.dev/badge/skills/mp-web3/claude-starter-kit/plan-and-implement.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 | $0.00055 | $0.00824 |
| Opus 5 | $0.00028 | $0.00412 |
| Sonnet 5 | $0.00011 | $0.00165 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
plan 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan & Implement Workflow
First: Read LEARNINGS.md (in this skill's directory) before proceeding.
You are executing a structured 6-phase workflow for building or changing project features. Follow each phase in order. Do NOT skip phases or start implementing before approval.
The user's request: $ARGUMENTS
Phase 1: Explore
Understand the current project state before designing anything.
- Read
CLAUDE.mdfor project conventions, key paths, and existing skills - Look for a file map or project structure documentation
- Read any existing skills, scripts, or files that relate to what's being built
- Identify reusable patterns, utilities, or templates from existing code
Do NOT propose anything yet — just gather context.
Phase 1.5: Tool Discovery (autonomy-first)
Before designing a custom solution, search for existing tools that do the job.
- Search for MCP servers — WebSearch for
"<service-name> MCP server"on GitHub/npm/PyPI - Search for official SDKs — Check if the service has an official Python/Node SDK
- Check existing MCP servers — Read
.mcp.jsonfor already-connected servers - Evaluate options: MCP server > official SDK > custom wrapper
- If an MCP server exists: configure it in
.mcp.jsoninstead of writing custom code - If no MCP server: proceed with custom implementation but note it as a future improvement target
Phase 2: Design
Classify what's being built and design the implementation.
- Classify the change type: skill / script / database / config / structure / other
- List files to create (with paths) and files to modify
- Define dependencies between files (what must be created first)
- Detail the design based on type
- Ask clarifying questions via AskUserQuestion if requirements are ambiguous — do NOT guess
Phase 3: Approve
Present the plan and wait for explicit approval.
Format the plan as:
What
- Files to create (path + one-line description each)
- Files to modify (path + what changes)
What ships with it
1 file 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.
- 3d ago First seen · 108 lines · 55 tokens per session scan A 20eb91dc9844
plan is a skill published in the GitHub repository mp-web3/claude-starter-kit (106 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 824 once invoked, about $0.0003 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.
Other skills, from other repositories
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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
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