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/nicepkg/vsync/resource-scoutnpx skills add nicepkg/vsync --skill resource-scoutgit clone --depth 1 https://github.com/nicepkg/vsyncWhat 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 | $0.00091 | $0.01305 |
| Opus 5 | $0.00046 | $0.00652 |
| Sonnet 5 | $0.00018 | $0.00261 |
| Haiku 4.5 | $0.00009 | $0.00130 |
Grade A, and why
resource-scout 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 2d 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 resource-scout — 0 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resource Scout
Search and discover existing Claude Code skills and MCP servers before building custom solutions.
Quick Search Strategy
For Skills:
- WebSearch:
site:skillsmp.com [topic]orclaude skill [topic] - Check GitHub:
awesome-claude-skills [topic] - Browse: skillhub.club, claudeskills.info
For MCP:
- WebSearch:
MCP server [tool/service name] - Check: glama.ai/mcp/servers, mcpmarket.com
- Official: github.com/modelcontextprotocol/servers
Skill Search Workflow
Step 1: Define Need
Before searching, clarify:
- What task needs to be accomplished?
- What tools/services are involved?
- Is it a common pattern (git, testing, API) or domain-specific?
Step 2: Search Marketplaces
Primary sources (largest catalogs):
| Source | URL | Best For |
|---|---|---|
| SkillsMP | skillsmp.com | 71000+ skills, long-tail search |
| SkillHub.club | skillhub.club | AI-evaluated, quality filter |
| Claude Skills Hub | claudeskills.info | UI-friendly browsing |
Search patterns:
# On SkillsMP
[domain] skill → "marketing skill", "database skill"
[framework] claude → "react claude", "fastapi claude"
[task] automation → "deployment automation"
Step 3: Search GitHub
Curated lists:
github.com/keyuyuan/skillhub-awesome-skills- 精选清单github.com/VoltAgent/awesome-claude-skills- 生态大全github.com/ComposioHQ/awesome-claude-skills- 大量通用技能
Ready-to-use repositories:
github.com/alirezarezvani/claude-skills- Content/Marketinggithub.com/gked2121/claude-skills- Workflow思维github.com/Microck/ordinary-claude-skills- 超大集合github.com/sickn33/antigravity-awesome-skills- 结构化
Search command:
# Use WebSearch tool
site:github.com "claude skill" [topic]
site:github.com "SKILL.md" [topic]
Step 4: Evaluate & Install
When skill found:
- Check last update date (prefer recent)
- Review SKILL.md for quality
- Check if has scripts/references
- Install with skill-downloader or manual copy
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.
- 2d ago First seen · 166 lines · 91 tokens per session scan A 85e027b9ceca
resource-scout is a skill published in the GitHub repository nicepkg/vsync (57 stars, last pushed 7mo ago), licensed MIT. It adds 91 tokens to every session and 1,305 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to resource-scout, differing in 0 lines, and is treated as a copy.
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writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.
setting-up-a-project
Use whenever asked to set up, onboard, initialize, or spec a project — the front door when the workspace has no spec graph yet (brand-new or an existing codebase); also seeded by the app's Set-up-project card (/skill:setting-up-a-project). Not for feature work in an already-specced project — use the brainstorming…
writing-specs
Use when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.