用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/majiayu000/claude-skill-registry --skill freesearch命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据,按主题分组汇总"我都做了什么",并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| name | freesearch |
| description | TRULY FREE research via Exa API - zero Claude tokens. Uses Exa directly, no Gemini CLI wrapper. |
| homepage | https://github.com/Khamel83/oneshot |
| allowed-tools | Read, Write, Edit, Bash |
| metadata | {"oneshot":{"emoji":"🆓","requires":{"bins":["curl"]}}} |
Uses 0 Claude Code tokens. Calls Exa API directly via curl.
User says:
/freesearch [topic] - Slash commandDirect API calls via curl:
docs/research/{date}_{topic}_in_progress.mddocs/research/{date}_{topic}_final.md with:
The EXA_API_KEY is loaded from encrypted secrets:
# Decrypt and load key (done via skill wrapper)
EXA_KEY=$(sops --decrypt --output-type json ~/github/oneshot/secrets/research_keys.json.encrypted | grep -o '"EXA_API_KEY": "[^"]*"' | cut -d'"' -f4)
API Endpoint: https://api.exa.ai/search
curl -s -X POST 'https://api.exa.ai/search' \
-H "x-api-key: $EXA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "[TOPIC]",
"type": "auto",
"numResults": 10,
"contents": {
"text": {
"maxCharacters": 20000
}
}
}'
Project research files:
docs/research/{YYYY-MM-DD}_{topic_slug}_in_progress.md
docs/research/{YYYY-MM-DD}_{topic_slug}_final.md
Historical research:
research/{topic_slug}/research.md
Based on competitor research, these features should be added to ONE_SHOT:
/browse command - Visual skill discovery with fuzzy searchbd test framework - Skill testing frameworkUser says: /freesearch AI coding tools with persistent memory
You do:
Ask clarifying questions:
Create in-progress file with initial query
Search Exa API:
web_search_exa: "AI coding tools persistent memory cross-session"get_code_context_exa: "AI coding task orchestration memory"Update in-progress file with findings
Create final report with executive summary
Return:
Key findings:
- MCP Task Orchestrator, Cipher, Pieces AI Memory, Cursor Rules
- All use RAG + vector stores for persistent context
📄 Full research: docs/research/2025-01-31_ai_persistent_memory_final.md
# Research: {Topic}
**Started:** {timestamp}
**Status:** In Progress
## Search Queries Used
- {query1}
- {query2}
## Raw Results
### Source 1
- **URL:** {url}
- **Title:** {title}
- **Snippet:** {content}
### Source 2
- **URL:** {url}
- **Title:** {title}
- **Snippet:** {content}
## Initial Notes
{ongoing analysis}
# Research: {Topic}
**Completed:** {timestamp}
**Duration:** {duration}
## Executive Summary
{2-3 sentence overview}
## Key Findings
1. {finding with citation}
2. {finding with citation}
## Sources
1. [{Title}]({url}) - {description}
2. [{Title}]({url}) - {description}
## Related Topics
- {topic for further research}
## Full Details
{detailed analysis}
---
📄 **In-progress research:** docs/research/{date}_{topic}_in_progress.md
The deep-research skill wraps Gemini CLI in a Claude sub-agent, which still burns tokens. This skill calls Exa API directly via curl:
docs/research/ (tracked in git)docs/research/ NOT ~/github/oneshot/research/free research, exa api, zero tokens, web search, research save