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 skills add malue-ai/dazee-small --skill skill-findergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/skill-finder)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/skill-finder"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/skill-finder/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/malue-ai/dazee-small/skill-finder"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/skill-finder.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00064 | $0.03414 |
| Opus 5 | $0.00032 | $0.01707 |
| Sonnet 5 | $0.00013 | $0.00683 |
| Haiku 4.5 | $0.00006 | $0.00341 |
Grade A, and why
skill-finder scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import urllib.request How it starts
The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 搜索与发现
帮助用户发现和安装新的 Skill,浏览已安装的 Skill,以及从社区搜索和下载 Skill。
使用场景
- 用户说「有没有 XX 的 Skill」「帮我找一个能做 XX 的技能」
- 用户说「我有哪些 Skill」「列出所有技能」
- 用户说「安装一个 XX Skill」「从社区找 Skill」
- 用户想扩展 Agent 的能力,问「能不能做 XX」而当前没有对应 Skill
- 用户提到 skills.sh 或 Agent Skills 生态
- 用户要求安装 MCP Server 或 MCP 工具(如 chrome-mcp、filesystem-mcp 等)
功能 1:浏览已安装的 Skill
列出所有已安装 Skill
读取 skill_registry.yaml 获取完整列表:
import os
import yaml
from pathlib import Path
instance_name = os.environ.get("AGENT_INSTANCE", "xiaodazi")
registry_path = Path(f"instances/{instance_name}/skills/skill_registry.yaml")
registry = yaml.safe_load(registry_path.read_text(encoding="utf-8"))
skills = registry.get("skills", [])
for s in skills:
status_icon = {"ready": "✅", "need_auth": "🔐", "need_setup": "⚙️", "unavailable": "❌"}.get(s.get("status", ""), "❓")
name = s.get("name", "")
enabled = "启用" if s.get("enabled", True) else "禁用"
print(f"{status_icon} {name} ({enabled})")
print(f"\n共 {len(skills)} 个 Skill")
查看 Skill 详情
读取指定 Skill 的 SKILL.md 获取详细信息:
import os
from pathlib import Path
instance_name = os.environ.get("AGENT_INSTANCE", "xiaodazi")
skill_name = "要查看的skill名称"
# 按优先级搜索
for base in [
Path(f"instances/{instance_name}/skills"),
Path("skills/library"),
]:
skill_md = base / skill_name / "SKILL.md"
if skill_md.exists():
content = skill_md.read_text(encoding="utf-8")
print(content[:2000]) # 输出前 2000 字符
break
else:
print(f"未找到 Skill: {skill_name}")
按分类筛选
读取 config/skills.yaml 中的 skill_groups 按分组展示:
import os
import yaml
from pathlib import Path
instance_name = os.environ.get("AGENT_INSTANCE", "xiaodazi")
config_path = Path(f"instances/{instance_name}/config/skills.yaml")
config = yaml.safe_load(config_path.read_text(encoding="utf-8"))
groups = config.get("skill_groups", {})
for group_name, group_info in groups.items():
if group_name.startswith("_"):
continue
desc = group_info.get("description", "")
skills = group_info.get("skills", [])
print(f"\n📂 {group_name} ({len(skills)} 个)")
print(f" {desc}")
for s in skills:
print(f" - {s}")
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.
- 9d ago First seen · 435 lines · 64 tokens per session scan A 6cdcbec2bdfe
skill-finder is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 3,414 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…