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 AgenticAIPlan/AgenticAISkills --skill energy-llm-trackergit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote 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/agenticaiplan/agenticaiskills/energy-llm-tracker)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/energy-llm-tracker"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/energy-llm-tracker/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/agenticaiplan/agenticaiskills/energy-llm-tracker"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/energy-llm-tracker.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 | $0.00087 | $0.01506 |
| Opus 5 | $0.00044 | $0.00753 |
| Sonnet 5 | $0.00017 | $0.00301 |
| Haiku 4.5 | $0.00009 | $0.00151 |
Grade A, and why
energy-llm-tracker 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 11d 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.
curl -s -L "https://www.baidu.com/s?wd=国家电网+大模型+2024" \ How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
能源行业大模型应用动态调研技能
概述
本技能用于系统性调研电力/电网、油气、新能源等能源行业企业在大模型（LLM）方向的最新应用动态，输出结构化的行业洞察报告。调研维度涵盖数据建设、行业模型、应用落地三个核心方向。
使用场景
以下请求应触发本技能：
- "帮我调研国家电网最近的大模型应用进展"
- "生成本周电力行业AI动态月报"
- "查找能源企业知识图谱建设相关的案例"
- "对比电力行业头部企业的大模型落地成熟度"
- "整理电力调度AI应用相关资讯"
调研工作流
Step 1：明确调研范围
收到调研请求后，首先确认以下参数：
- 时间范围：默认近7天（周报）或近30天（月报）
- 聚焦企业：全行业或指定企业名称
- 聚焦维度：全部维度，或指定数据建设/行业模型/应用落地
参考 references/energy_companies.md 获取重点企业名单和信息来源列表。
Step 2：生成搜索查询
运行搜索查询生成脚本，获取结构化搜索指引：
# 生成全行业搜索指引（默认近7天）
python3 scripts/fetch_energy_news.py
# 聚焦特定企业
python3 scripts/fetch_energy_news.py --company "国家电网" --days 30
# 聚焦特定维度
python3 scripts/fetch_energy_news.py --dimension application --days 14
# 输出 JSON 格式（便于后续处理）
python3 scripts/fetch_energy_news.py --format json --output queries.json
Step 3：执行信息检索
按照脚本生成的搜索指引，组合使用以下两种搜索方式，覆盖国内外信息源：
国内搜索（优先）— 使用 china-search 技能
能源行业资讯以中文为主，优先通过国内搜索引擎获取：
# 百度搜索：综合新闻、官网公告
curl -s -L "https://www.baidu.com/s?wd=国家电网+大模型+2024" \
-H "User-Agent: Mozilla/5.0"
# 搜狗微信搜索：公众号深度文章（行业分析、案例报道）
curl -s -L "https://weixin.sogou.com/weixin?query=电力行业+大模型+落地" \
-H "User-Agent: Mozilla/5.0"
# Bing 中国：兼顾国际信息与国内可访问性
curl -s -L "https://cn.bing.com/search?q=电力调度+AI+应用" \
-H "User-Agent: Mozilla/5.0"
搜狗微信搜索特别适合查找行业媒体公众号的深度报道，是百度搜索的重要补充。
国际/英文搜索 — 使用 WebSearch 工具
用于检索国际机构报告、英文学术资讯等：
- IEA（国际能源署）能源数字化报告
- 外资能源企业（Shell、BP、Equinor 等）AI 应用进展
信息可信度评级
| 来源类型 | 可信度 | 示例 |
|---|---|---|
| 企业官网新闻中心 | ⭐⭐⭐ | sgcc.com.cn、csg.cn |
| 政府官网发布 | ⭐⭐⭐ | nea.gov.cn、sasac.gov.cn |
| 主流行业媒体 | ⭐⭐ | 北极星电力网、中国电力新闻网 |
| 微信公众号文章 | ⭐⭐ | 已认证的行业机构账号 |
| 自媒体/未注明来源 | ⭐ | 待核实 |
参考 references/research_dimensions.md 中的维度框架和关键词，提升搜索精准度。
Step 4：结构化记录资讯
将检索结果整理为标准 JSON 格式（参见 scripts/generate_report.py --template）：
{
"company": "企业名称",
"date": "YYYY-MM-DD",
"summary": "一句话摘要（不超过50字）",
"detail": "详细描述（100-200字）",
"dimension": "data | model | application",
"app_category": "应用子类（仅 application 维度填写）",
"credibility": 3,
"source": "来源链接或出处"
}
What ships with it
5 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.
- 11d ago First seen · 152 lines · 87 tokens per session scan A 4baf6966993c
energy-llm-tracker is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 87 tokens to every session and 1,506 once invoked, about $0.0004 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 2026-08-30.
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