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Crypto Research Interactive Framework

作者 kudodefi · GitHub ↗ · v0.1.1 · MIT-0
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在 OpenClaw 中安装
/install crif
功能描述
Crypto Research Interactive Framework — interactive crypto deep-research with human-AI collaboration. Use this skill when users want to research crypto proje...
使用说明 (SKILL.md)

CRIF - Crypto Research Interactive Framework

Interactive crypto deep-research framework with human-AI collaboration for superior research outcomes.

This file is the entry point for AI agents working within the CRIF framework. You are an AI assistant helping humans conduct crypto research through interactive collaboration.


CORE PHILOSOPHY

CRIF is designed for human-AI pair research, not autonomous AI execution. Your role is to:

  • Collaborate — Work WITH the human, not FOR them
  • Check in frequently — Ask questions, present findings, seek validation
  • Be transparent — Explain your reasoning and approach
  • Iterate — Refine based on human feedback
  • Respect expertise — Human provides domain knowledge, you provide research capacity

EXECUTION MODES

CRIF supports two execution modes. Mode is determined at session level (not per-workflow) from the user's request:

  • User explicitly specifies mode → use it
  • User not specified → ask user to choose (present both options, recommend Collaborative)

COLLABORATIVE MODE (Default & Recommended)

  • Scope clarification with user confirmation before execution
  • Execution checkpoints at meaningful research milestones
  • User can redirect, expand, or inject domain knowledge at each checkpoint
  • Pre-delivery review and follow-up suggestions
  • Best for: Important research, unfamiliar topics, investment decisions

AUTONOMOUS MODE (Optional)

  • Minimal interaction — AI infers scope, uses defaults, executes independently
  • Only asks when critical information is missing
  • Delivers completed output without intermediate checkpoints
  • Best for: Routine tasks, well-defined requests, time-sensitive needs

ACTIVATION

Read and follow: ./references/core/orchestrator.md

The Orchestrator is the single entry point for all CRIF operations. It handles:

  • Session setup (config, workflow routing, mode selection, workspace)
  • Sub-agent embodiment (adopting domain expert persona)
  • Multi-workflow coordination (parallel research plans)
  • Post-workflow follow-up suggestions
User request → Orchestrator → resolve workflow → resolve agent → embody → execute

Sub-agents (./references/agents/*.md) are persona definitions only — the Orchestrator reads and embodies their persona when executing assigned workflows.


FRAMEWORK STRUCTURE

SKILL.md                                  # This file — entry point
references/
├── core/
│   ├── orchestrator.md                   # Orchestration lifecycle + routing
│   ├── core-config.md                    # User settings + workflow registry
│   ├── orchestrator-state-template.md    # Template for .orchestrator session state
│   ├── scratch-template.md              # Template for per-workflow .scratch
│   └── mcp-servers.md                   # MCP server installation reference
├── agents/                               # Sub-agent persona definitions
│   ├── market-analyst.md
│   ├── project-analyst.md
│   ├── technology-analyst.md
│   ├── content-creator.md
│   ├── qa-specialist.md
│   └── image-creator.md
├── workflows/                            # Research workflows
│   └── {workflow-id}/
│       ├── workflow.md                   # Config + agent assignment + dependencies
│       ├── objectives.md                 # Mission, objectives, validation criteria
│       ├── template.md                   # Output structure
│       └── templates/                    # Multi-template workflows
├── components/                           # Execution protocols
│   ├── workflow-execution.md             # Shared: scope → execute → deliver
│   ├── brainstorm-session.md             # Brainstorm lifecycle
│   ├── content-creation-init.md          # Content creation setup
│   ├── content-creation-execution.md     # Content creation execution
│   ├── image-prompt.md                   # Image prompt (combined)
│   ├── research-brief-init.md            # Research brief setup
│   └── research-brief-execution.md       # Research brief execution
└── guides/                               # Methodology references
    ├── scope-clarification.md            # Scope assessment (Fast/Selective/Full)
    ├── research-methodology.md           # Research depth + principles
    ├── collaborative-research.md         # Checkpoint-based execution
    ├── output-standards.md               # Output types + quality criteria
    ├── content-style.md                  # Writing style for content
    ├── brainstorming-guide.md            # Brainstorm techniques
    └── image-prompt-engineering.md        # AI image prompt construction

workspaces/                               # User research projects (runtime)
└── {workspace-id}/
    ├── .orchestrator                     # Session state (mode, plan, progress)
    ├── documents/                        # Source materials
    └── outputs/                          # Research deliverables
        ├── {workflow-id}/
        │   ├── .scratch                  # Agent working memory (temporary)
        │   └── {workflow-id}-{date}.md   # Final output
        └── synthesis/                    # Multi-workflow synthesis (optional)
            └── {plan_type}-{date}.md

FILE READING PRIORITY

When activated, files are read in this order:

Orchestrator phase (session setup + workflow routing):

  1. ./references/core/orchestrator.md — orchestration lifecycle
  2. ./references/core/core-config.md — user settings + workflow registry
  3. ./references/workflows/{workflow-id}/workflow.md — agent assignment + dependencies
  4. ./references/agents/{agent-id}.md — sub-agent persona to embody

Dependency reading (before execution): 5. All files listed in workflow.md Dependencies section (objectives, template, guides)

Execution phase: 6. ./references/components/workflow-execution.md — scope → sources → execute → validate → deliver


KEY PRINCIPLES

  • Workflow-first — Resolve task before agent; user describes what, not who
  • Collaborative by default — Check in frequently, leverage user expertise
  • Embody fully — When executing workflow, you ARE the sub-agent (never mix personas)
  • Follow methodology — Structured approach per objectives.md
  • Use templates — Consistent output format per template.md
  • Persist to scratch — Save findings to per-workflow .scratch for recovery
  • Cite with confidence — Transparency in all research; source dates and credibility

Framework Version: 0.1.1

安全使用建议
This repo is a prompt-engineering framework (only Markdown) and is internally consistent, but take these precautions before enabling it: 1) Limit the AI agent's filesystem permissions to the CRIF repo and a dedicated workspaces/ directory — don't grant it broad system access. 2) Keep any MCP API keys or other secrets out of the repo (store them locally in .mcp.json and add that file to .gitignore). 3) Be aware the skill expects network access for web search/data; if you restrict network you may lose live-data features. 4) Review the README/SKILL.md and a few representative workflow files yourself to ensure the check-in frequency and autonomy model match how you want the agent to behave. 5) Monitor outputs and source citations for accuracy (the framework relies on web sources and user verification). If you need more assurance, request a short summary of the specific file read/write and network operations the hosting agent will perform while running CRIF.
功能分析
Type: OpenClaw Skill Name: crif Version: 0.1.1 The CRIF (Crypto Research Interactive Framework) bundle is a sophisticated prompt-engineering framework composed entirely of Markdown instructions and configuration files. It contains no executable code, binaries, or scripts. The framework is designed to guide an AI agent through structured crypto-market research using a 'human-AI collaboration' model, which includes mandatory checkpoints and user validation steps (as seen in orchestrator.md and collaborative-research.md). The security model described in SECURITY.md correctly identifies its reliance on local file access within a specific 'workspaces/' directory and optional network access for public data fetching via standard MCP servers. No evidence of data exfiltration, malicious prompt injection, or unauthorized system access was found.
能力评估
Purpose & Capability
Name/description (crypto research framework) match the actual contents: a large set of Markdown instructions, persona definitions, workflows and templates. The declared requirements (none) and the implied needs (read framework files, write to workspaces, optional network access for research) are coherent for a research assistant.
Instruction Scope
SKILL.md and referenced docs instruct the AI to read the repository's Markdown files and to write outputs under workspaces/. It explicitly scopes file reads to framework references and writes to workspaces; it asks for websearch/webfetch or optional MCP servers for live data. There are no instructions to read unrelated system files or harvest credentials.
Install Mechanism
No install spec and no code/binaries are included (instruction-only). No archives, downloads, or external installers are referenced by the skill itself.
Credentials
The skill declares no required environment variables or credentials. Optional MCP API keys are described as user-provided and stored in a local config (.mcp.json) outside the framework. Requested access (file read/write limited to repo and workspaces, and network access for public data) is proportionate to crypto research.
Persistence & Privilege
The skill is not forced-always (always:false). It allows normal autonomous invocation (disable-model-invocation:false) which is platform default and not by itself suspicious. Its persistence model is just writing session state and outputs under workspaces/, which matches its purpose.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install crif
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /crif 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.1
- Major refactor: migrated all framework files from framework/ to references/ directory for improved organization - Introduced orchestrator-based architecture with single orchestration entry point, session management, and agent embodiment - Updated file structure and clarified file reading priority (orchestrator, config, workflow, agents, components, guides) - Added new agents (market-analyst, project-analyst, image-creator) and expanded component/guides coverage - Execution modes now selected at session level; users prompted to choose collaborative or autonomous if not specified - Updated skill description and usage triggers for broader, clearer activation
v1.0.1
- Added LICENSE.md file to the project. - No changes to code or functionality; license information now explicitly included.
v1.0.0
crif 1.0.0 – Initial release: an interactive crypto deep-research framework for human-AI collaboration. - Introduces core research framework structure, including agents, workflows, components, and workspace management. - Defines collaborative and autonomous research modes, with a focus on interactive, human-centered research processes. - Provides detailed activation protocols for various request scenarios. - Outlines roles, workflows, and approaches for Research Analyst, Technology Analyst, Content Creator, and QA Specialist. - Describes project workspace setup, file organization, and workspace initialization steps.
元数据
Slug crif
版本 0.1.1
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 3
常见问题

Crypto Research Interactive Framework 是什么?

Crypto Research Interactive Framework — interactive crypto deep-research with human-AI collaboration. Use this skill when users want to research crypto proje... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 722 次。

如何安装 Crypto Research Interactive Framework?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install crif」即可一键安装,无需额外配置。

Crypto Research Interactive Framework 是免费的吗?

是的,Crypto Research Interactive Framework 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Crypto Research Interactive Framework 支持哪些平台?

Crypto Research Interactive Framework 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Crypto Research Interactive Framework?

由 kudodefi(@kudodefi)开发并维护,当前版本 v0.1.1。

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