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Agent Skill · 研究检索

funky-fund-flamingo(时髦基金火烈鸟)

funky-fund-flamingo 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

funky-fund-flamingo 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 5,935。

总安装 23,769周安装 1,021GitHub Stars 公开资料未说明下载 8,331核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:funky-fund-flamingo(时髦基金火烈鸟)
来源仓库:https://github.com/icemastert/funky-fund-flamingo
安装命令:
openclaw skills install funky-fund-flamingo
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install funky-fund-flamingo

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

OpenClaw 的修复优先自我进化——审核日志、内存和技能;运行可测量的突变周期。得到报酬。发展。重复。多拉多拉比尔你们大家。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install funky-fund-flamingo;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

funky-fund-flamingo 怎么安装?

在终端执行 openclaw skills install funky-fund-flamingo。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

funky-fund-flamingo 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

funky-fund-flamingo 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

funky-fund-flamingo 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

funky-fund-flamingo 用的人多吗?

公开数据是累计安装 23,769 次,近一周安装 1,021 次,下载 8,331 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

funky-fund-flamingo 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
funky-fund-flamingo

时髦基金火烈鸟 · 本页

23,769—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
funky-fund-flamingo
version
1.0.35
description
Repair-first self-evolution for OpenClaw — audit logs, memory, and skills; run measurable mutation cycles. Get paid. Evolve. Repeat. Dolla dolla bill y'all.
homepage
https://clawhub.ai
metadata
short-description
Get paid. Evolve. Repeat.
clawdbot
emoji
🦩
requires
env
[] # all env vars below are optional
files
["index.js", "evolve.js", "agents/*.yaml", "ADL.md", "VFM.md", "TREE.md"]
tags

🦩 Funky Fund Flamingo — Make That Paper

Use this skill when you're ready to get paid. We inspect reality, kill breakage and value leaks, and run mutation cycles that produce concrete gains — so the stack earns, not just runs.

When To Use

  • Runtime logs are screaming and you need structured repair so shit works and keeps making money.
  • The agent is stable but stagnating — time for a deliberate capability mutation that moves the needle.
  • You want one execution plan that combines logs + memory + skills into a cycle that pays off.
  • You need continuous relay mode (--loop / --funky-fund-flamingo) so evolution runs in the background and the revenue keeps flowing.

Inputs And Context

  • Session logs: ~/.openclaw/agents/<agent>/sessions/*.jsonl
  • Workspace memory: MEMORY.md, memory/YYYY-MM-DD.md, USER.md
  • Installed skills list from workspace skills/
  • Optional environment overrides from ../../.env

Entrypoints

  • Main runner: index.js
  • Prompt builder and cycle logic: evolve.js

Run from workspace root:

node skills/funky-fund-flamingo/index.js run

Run from inside this skill directory:

node index.js run

Execution Modes

# single cycle — one shot, max impact
node index.js run

# alias command
node index.js /evolve

# human confirmation before significant edits (protect the bag)
node index.js run --review

# prompt generation only (writes prompt artifact to memory dir)
node index.js run --dry-run

# continuous relay — keep the money printer running
node index.js --loop
node index.js run --funky-fund-flamingo

Cycle Contract

Each cycle should:

  1. Inspect recent session transcript — find breakages, repetition, value leaks.
  2. Read memory + user context so evolution is aligned with what actually pays.
  3. Select mutation mode (repair, optimize, expand, instrument, personalize).
  4. Produce actionable mutation instructions and reporting so you see the ROI.
  5. Persist state (memory/evolution_state.json) and optionally schedule the next loop.
  6. Persist long-term evolution learning (memory/funky_fund_flamingo_persistent_memory.json) so strategy compounds and the bag gets bigger.

Safety Constraints (Protect the Bag)

  • No destructive git/file ops unless explicitly requested.
  • Repair and reliability first when instability is detected — downtime = no revenue.
  • Respect review mode before applying significant edits.
  • Keep changes scoped and explainable; no no-op cycles that burn compute for nothing.
  • Local-only execution: no publish, no push to remote git, no external tool spawning without intent.

External Endpoints

URLData sentPurpose
None (from this skill's code)—This skill's Node.js code does not open sockets or make HTTP requests. It only reads/writes local files.

Important: The repo includes agent config templates (agents/openai.yaml, agents/openrouter.yaml) for use by an OpenClaw (or other) agent. When you run an agent that uses this skill with a cloud model (OpenAI, OpenRouter, etc.), that agent will send the prompts this skill builds — which can include excerpts from session logs, memory, and workspace context — to the provider's API. So "local-only" applies to the skill binary itself; if the skill is invoked by an agent backed by a third-party LLM, data can leave the machine via that agent. To stay fully local, run node index.js run (or --dry-run) without routing the generated prompt through a cloud model.

Security & Privacy

  • Reads: Session logs under ~/.openclaw/agents/<agent>/sessions/*.jsonl, workspace MEMORY.md, memory/, USER.md, and the skills/ directory.
  • Writes: memory/evolution_state.json, memory/funky_fund_flamingo_persistent_memory.json, and optionally prompt artifacts in the memory dir. This skill does not push or publish anywhere; any outbound data is only via whatever agent/model stack you choose to run.
  • No network from skill code: The skill itself does not open sockets or make HTTP requests.

Optional environment variables

No env vars are required. The following are optional overrides (see evolve.js / README):

VariablePurposeTypical default
AGENT_NAMEAgent session folder under ~/.openclaw/agents/main
MEMORY_DIRDirectory for evolution state and persistent memoryworkspace memory/
TARGET_SESSION_BYTESMax bytes read from latest session log64000
LOOP_MIN_INTERVAL_SECONDSMin delay between loop cycles900
MAX_MEMORY_CHARS, MAX_TODAY_LOG_CHARS, MAX_PERSISTENT_MEMORY_CHARSContent caps for promptssee evolve.js
ECONOMIC_KEYWORDSComma-separated keywords for value scoringbuilt-in list
EVOLVE_REPORT_DIRECTIVE, EVOLVE_EXTRA_MODES, EVOLVE_ENABLE_SESSION_ARCHIVEBehavior tweaks—

Model invocation

Evolution can be run manually (node index.js run) or by an agent that uses this skill. In relay mode (--loop / --funky-fund-flamingo), this process only plans and writes prompts; it does not call any model API. If you run an agent that consumes this skill with OpenAI/OpenRouter/etc., that agent will perform the model calls. To avoid sending local context to a provider, run the skill in --dry-run and do not feed the generated prompt to a cloud model.

Master directive and mutation pressure

The master directive (funky-fund-flamingo-master-directive.json) sets must_evolve_each_cycle and no_op_forbidden, which push every cycle toward making a concrete change. That can increase how often local files are mutated. For lower risk, prefer --review (confirm before significant edits) or --dry-run (prompt generation only, no writes). You can also edit or override the directive to relax these flags.

Trust Statement

By using this skill, you run Node.js code that reads and writes files in your OpenClaw workspace and agent session directories. This skill's code does not send data to third parties; if an agent that uses this skill calls a cloud LLM, that agent (not this skill binary) sends the prompt. Only install if you trust the skill source (e.g. ClawHub and the publisher).

Supporting References

  • ADL.md — anti-degeneration so we don't break the money printer
  • VFM.md — value-focused mutation: only changes that pay
  • TREE.md — capability topology and revenue-ready nodes
  • .clawhub/FMEP.md (forced mutation execution policy)

Minimal Verification

node index.js --help

*Dolla, dolla bill y'all. 🦩*

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

OpenClaw

94.74%
按下载量换算7,893

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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