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 aAAaqwq/AGI-Super-Team --skill company-analyzergit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/aaaaqwq/agi-super-team/company-analyzer)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/company-analyzer"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/company-analyzer/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/aaaaqwq/agi-super-team/company-analyzer"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/company-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00631 |
| Opus 5.5 | $0.00000 | $0.00252 |
| Sonnet 5.5 | $0.00000 | $0.00126 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
company-analyzer scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash 4+, jq, bc, curl What it actually says
company-analyzer
企业深度分析引擎——多框架 LLM 分析，带缓存、成本追踪、速率限制
使用场景
- 对上市公司进行全面分析（基本面、技术面、竞争格局等）
- 多分析框架并行执行（如 SWOT、估值模型、行业分析等）
- 预算控制下的批量公司分析
- 作为 CRO（研究官）的核心分析工具
使用方法
# Shell 库引用方式（在分析脚本中 source）
source ~/clawd/skills/company-analyzer/scripts/lib/api-client.sh
source ~/clawd/skills/company-analyzer/scripts/lib/cache.sh
source ~/clawd/skills/company-analyzer/scripts/lib/cost-tracker.sh
# 调用 LLM 分析
result=$(call_llm_api "分析 AAPL 的竞争优势" 8192)
content=$(extract_content "$result")
prompt_tokens output_tokens=$(extract_usage "$result" "$original_prompt")
# 缓存管理
key=$(cache_key "AAPL" "01-swot" "$prompt")
cached=$(cache_get "$key") # 返回缓存或空
cache_set "$key" "$response" '{"framework":"swot"}'
# 成本追踪
log_cost "AAPL" "swot" 1500 3000 # 记录 API 调用成本
check_budget # 检查是否超预算（默认 $0.10/天）
核心模块
| 模块 | 文件 | 说明 |
|---|---|---|
| API Client | scripts/lib/api-client.sh |
配置驱动的 LLM 客户端，自动读 OpenClaw 配置 |
| Cache | scripts/lib/cache.sh |
SHA256 键 + 7 天 TTL 持久化缓存 |
| Cost Tracker | scripts/lib/cost-tracker.sh |
动态价格查找 + 日预算检查 |
| Trace | scripts/lib/trace.sh |
日志追踪 |
| Prices | scripts/lib/prices.json |
各模型 token 单价表 |
配置要求
- Bash 4+, jq, bc, curl
- OpenClaw 配置：
~/.openclaw/openclaw.json（模型/提供商/密钥） - 认证配置：
~/.openclaw/agents/main/agent/auth-profiles.json - 默认日预算：$0.10（可修改
DAILY_BUDGET变量）
相关文件
scripts/lib/api-client.sh— LLM API 客户端（速率限制、重试、降级）scripts/lib/cache.sh— 生产级持久化缓存scripts/lib/cost-tracker.sh— 动态成本追踪scripts/lib/prices.json— 模型价格表scripts/lib/trace.sh— 日志工具
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.
- 1mo ago First seen · 53 lines · 0 tokens per session scan A 5566a8b68e7d
company-analyzer is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (111 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 631 tokens. 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 2026-09-05.
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