Nano Banana Pro Prompts Recommend Skill
YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill
Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs.
使用本机 fleet 分派 Codex GPT-6、Gemini、Grok 或 JEV 任务,或调用 Kollab 图片/视频/音频/多模态能力时使用;包括用户点名 agent-fleet、Nano Banana、nanobanana、香蕉、便宜模型、多模型并行,用户说“让 Codex 或 GPT-6 做某事”的编码、调研与 review 派单,以及按全局 CLAUDE.md §2…
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-fleet --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .claude/skills/agent-fleet && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .claude/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skillsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-fleet --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .agents/skills/agent-fleet && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .agents/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-fleet --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .cursor/skills/agent-fleet && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .cursor/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/majiayu000/claude-skill-registry.git --path skills/bash/skill-yan-labs-yan-skills--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-fleet --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .gemini/skills/agent-fleet && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .gemini/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install majiayu000/claude-skill-registry agent-fleetInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .github/skills/agent-fleet && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .github/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-fleet --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/bash/skill-yan-labs-yan-skills .opencode/skills/agent-fleet && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agent-fleet" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/skill-yan-labs-yan-skills into .opencode/skills/agent-fleet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-fleet", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agent-fleet使用本机 fleet 分派 Codex GPT-6、Gemini、Grok 或 JEV 任务,或调用 Kollab 图片/视频/音频/多模态能力时使用;包括用户点名 agent-fleet、Nano Banana、nanobanana、香蕉、便宜模型、多模型并行,用户说“让 Codex 或 GPT-6 做某事”的编码、调研与 review 派单,以及按全局 CLAUDE.md §2…
Agent Fleet is an agent skill from majiayu000/claude-skill-registry. 使用本机 fleet 分派 Codex GPT-6、Gemini、Grok 或 JEV 任务,或调用 Kollab 图片/视频/音频/多模态能力时使用;包括用户点名 agent-fleet、Nano Banana、nanobanana、香蕉、便宜模型、多模型并行,用户说“让 Codex 或 GPT-6 做某事”的编码、调研与 review 派单,以及按全局 CLAUDE.md §2 路由任务。只做单一模型的直接任务且无需 fleet 时不触发;用户明确要直接操作 Codex CLI 原生命令(自选 sandbox、codex review、apply、resume)时用 codex Skill;普通生成图片也可用 imagegen。
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).
It sits in Media & Creative, covering Image generation. It works with Google Gemini and Bash. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and json).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
KOLLAB_API_KEYKOLLAB_STANDALONE_API_KEYKOLLAB_API_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agent Fleet loads about 2.3k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 583 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 583 words, ~2,260 tokens.
.claude/skills/agent-fleet/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.本机多模型任务入口:使用 fleet 运行 brief,结束后按实际产物验收。先核对目标模型当前配置、真实 Key 是否存在、工作目录信任边界和任务归属;密钥只看状态,不打印值。
| 命令 | 用途 |
|---|---|
fleet copy brief.md | Gemini 文案、翻译 |
fleet grok brief.md | Grok 调研 |
fleet web start/say/close/list;兼容 fleet web "问题" [--followup "追问" ...] [--close] | 网页版 ChatGPT,少量串行问答 |
fleet bulk brief.md | Gemini 批量处理 |
fleet gpt brief.md | 托管 GPT 任务 |
fleet code brief.md [--low] [--cwd dir] | 本机 Codex GPT-6:默认入口 |
fleet code brief.md --review | 本机 Codex 只读审查 |
fleet judge state.txt questions.json | JEV 结构化判断 |
fleet run --model name --prompt "任务" | 旧的完整模型入口 |
fleet run-many --config batch.json | 批量任务 |
fleet status / fleet tail [--follow] | 看任务和日志 |
fleet say latest "消息" | 向运行中的任务插话 |
fleet stop latest / fleet resume latest | 收尾或续跑 |
fleet list-models / fleet help | 看配置或用法 |
fleet media list | 看 Kollab 当前托管的图片、视频、音频、视觉工具与必填参数 |
fleet media run <tool> --model <id> --prompt "..." [--input-json '{}'] [--out dir] | 调用托管多模态工具并落盘 |
fleet media models [--source openrouter] [--search text] | 查 Kollab 模型目录 |
brief 若是现存文件路径就读取内容,否则作为任务文本。短命令和 run 默认当前目录、不限轮数、安静写日志;--verbose 输出进度。--cwd、--max-turns、--system-prompt 等可显式指定。旧的 agent-fleet run ... 写法仍可用。完整结果在 ~/.agent-fleet/runs/*.result.md,过程在同名 .log;stdout 默认只给简报。
多模态认证优先用 KOLLAB_API_KEY 或 KOLLAB_STANDALONE_API_KEY(kollab api-key create 获取),其次用进程级 KOLLAB_API_TOKEN 或 kollab login 会话;TEST 必须显式设置 KOLLAB_API_URL,不要复用生产 profile。先运行 fleet media list 看实时支持清单和模型 id,再用 fleet media run generate_image --model <id> --prompt "一只猫";默认文件写入当前目录 fleet-media/。其他工具按清单传 --input-json 的必填字段,详见 多模态用法。普通配图也可用 imagegen。
fleet 任务一律这样启动:一条 Bash 调用,只放 fleet ... 这一条命令,用工具参数 run_in_background: true、timeout: 7200000,输出用 > 文件 2>&1 重定向。命令里绝不写结尾的 &、nohup、disown。
Bash(command="fleet code brief.md --cwd <目录> > /tmp/<名>.out 2>&1", run_in_background=true, timeout=7200000)原因:命令自己再加 &,外层 shell 立刻退出,harness 马上发「后台命令已完成」的假通知,真正的 fleet/codex 进程变成无人认领的孤儿,之后不会有真实完成通知,主线程只能靠轮询或补 Monitor(2026-10-04 hotellobby 的 P0a/P0b 就这样出过错)。不套 & 时,fleet 进程退出才会触发完成通知。
&。pgrep -fl 'agent-fleet.mjs code' 能看到进程,且 Bash 任务状态仍是 running。&:不要杀进程,用 Monitor 补一个带硬超时的 until 循环等报告文件;pgrep 的模式必须写成 '[p]0a-xxx' 这种括号形式,否则会匹配到 Monitor 自己的命令行,永远等不到结束。pgrep -fl 'codex exec.*<worktree>',杀 fleet 外壳不等于杀掉 codex。写文案必须使用 /marketing-psychology、/marketing-ideas、/write 的原则并遵守 references/copy-voice.md,fleet copy 自动注入;写文案 brief 仍要给事实清单和禁止项。仅纯机械改写可用 --no-voice 跳过。
大部分任务(编码、修 bug、补测试、调研、技术文档、报告、数据整理)优先 fleet code:本机 Codex gpt-6.1-sol,默认 medium,单文件且边界明确时用 --low。页面、营销和产品文案、翻译、多语言及母语校对一律 fleet copy,写能做什么和带来什么好处,不贬低竞品或用恐吓式对比。Grok 可分担擦边题材、其他调研或作为 GPT-6 备选;JEV 只做结构化判断。Claude 只做全局 CLAUDE.md §2 明确归它的任务。
GPT-6 只做 brief 点名的事。除非逐项要求,不写测试或测试脚本、不先写测试、不加安全校验/防御代码/权限边界/输入校验/异常兜底、不重构或抽象封装、不加配置项、文档或注释、不改无关文件、不装依赖、不提交/推送/部署/发布、不调用外部写接口。已有测试和构建只在 brief 要求时运行;拿不准的事不做,最终回复用一行列「建议但未做」。未点名的产物算越界。brief 必须逐字包含:「只做本 brief 列出的事。不写测试、不加安全防护或边界校验、不重构、不做任何未点名的额外工作或 action;拿不准就不做,在回复里列一行建议。」
GPT-6 走 ChatGPT 会员额度,按现有账号约定不额外花钱;其 brief 必须限定最终回复只给结论、改动路径和验证结果,约 15 行内,长内容写入文件。面向读者的文案交 Gemini。
| 短名 | 实际模型 | 适合 |
|---|---|---|
copy | kollab-gateway-copy(Gemini) | 文案、翻译(必须走这里,正面写) |
grok | kollab-gateway-research | 擦边题材、其他调研、GPT-6 备选 |
bulk | kollab-gateway-bulk | 批量转换 |
gpt | kollab-gateway-gpt-sol | GPT 托管任务 |
code | 本机 Codex gpt-6.1-sol | 默认执行者:编码、调研、报告、通用任务;默认 medium,--low 为 low |
judge | jev | 分类、选择、打分 |
web | 网页版 ChatGPT(chatgpt-web-ask.mjs) | 联网调研、综述、对比、选题发散、竞品功能核对 |
code 在本机 Codex 缺失、登录失效或模型明确不支持时,自动改走 kollab-gateway-gpt-sol;其他失败不自动重试。选择以当前配置和实际结果为准;查看其他模型用 fleet list-models。Codex 审查范围见 编程与 review。
与 Rankup 探针共用网页驱动,适合少量串行调研、综述与对比;每轮约 30–110 秒。不适合读本地文件、执行命令、改代码或批量任务。
fleet web start "问题" --name research-signatures
fleet web say chatgpt-web-research-signatures "追问"
fleet web list
fleet web close chatgpt-web-research-signatures
fleet web "问题" --followup "追问1" --followup "追问2" --out answer.md --jsonclose。兼容问答命令加 --close 在结束后关闭;失败、报错或中断也关闭,页面文字保留在输出中。追问间至少隔 8 秒。AI_PROBE_WEB_WINDOW 可覆盖。常驻对话打开时使用 --keep-alive,不自动回收,需显式 fleet web close;一次性问答(无追问且带 --close)仍默认 10 分钟空闲回收;旧 CLI 不认识该参数时提示并退回原 env 保活方案;页面丢失须重新 start,临时聊天无法找回。start/say 支持 --json、--out file;会话名、回答和引用一起输出。直接调用脚本与 fleet web 等价。窗口机制见 opencli Skill。执行者会自己找方向、顺手做没点名的事、做不成就绕路凑数。派单时把范围写死,一单只一个方向、一个目标:
fleet code 在 brief 前自动加上下面这段,网关模型则追加进默认执行者系统提示(src/scope.mjs 的 SCOPE_LOCK,文字与此逐字一致;改一处必须同步另一处)。brief 里仍要写自己的边界,兜底只防漏写:【行动范围】你有 brief 指定的这一个任务目标:围绕它做事,目标所必需的相关改动(相邻文件、同类键、配置、让验收通过所需的小修)可以做,不必逐项点名;不要节外生枝:不自己新增或切换方向,不主动加测试、安全防护、重构,不做与目标无关的事;发现的无关线索只在最终回复里用一行列出,不执行。怎么做、怎么测、怎么验证由你自己决定:遇到办法、测量方式、环境小障碍(浏览器崩溃、弹窗遮挡、残留的同名分支或工作区、验收条件在现实中做不到等),选最保守的可行方案继续,把选择和理由记在报告的「偏差」里,不要停;验收条件做不到时先用 brief 给的备用办法,没有备用就做最接近的版本并如实写明差距。只有这几种情况才立刻停止并如实报告:需要改动生产环境或线上数据;需要碰任务明显之外的系统;需要花钱或使用未授权的凭据;缺权限或缺输入导致目标本身无法交付。停止时写明已完成什么、卡在哪里,不降低目标凑数。brief 已列出多条路径时,单条路径不可用就改用 brief 列出的其他路径。
验收时,执行者做了 brief 之外的事、改了方向、或做不到却用替代品交差,都算越界,按 CLAUDE.md §4.3 先向用户报告,不自行掩盖。
| verdict | 含义与处理 |
|---|---|
ok | 正常结束;按任务核对产物和测试 |
partial | 到轮数上限但已有改动;验收现有产物或 resume |
suspect | 疑似假成功或要求改动却零改动;核对结果和 diff |
needs-review | JEV 置信度不足;人工核对 |
fail | 执行失败、空结果或裸控制 token;看错误后修复 |
stopped | 已收尾中断;检查已完成部分 |
ok 只说明进程结果,不能代替任务验收;空结果、裸 tool-call 控制 token、suspect 或 fail 都不能算成功。核对 brief、产物和要求的检查;dirty 和 commits 也可能包含同一工作树里其他人的改动。细节见 README。
开头说明目标、真实交付物、允许改的文件、不可碰的范围、并行工作边界、必须跑的检查和完成标准;方向只写一个,写法见上文「行动范围」。
派单前先核实路径,再写进 brief。 允许读写清单里的每个路径都用 ls 或 test -e 确认:已有文件确认存在;新文件确认上级目录存在,并明确写成「新建,路径为……」,不要写「放在已有的脚本目录」这类要执行者自己去猜的说法。执行者遇到路径对不上会按「行动范围」直接停止、不会自行换路径,一处路径写错就白跑一轮。各 Skill 的布局并不统一(例如 agent-fleet 的说明在 agent-fleet/skill/SKILL.md、可执行脚本在 bin/;rankup 与 opencli 的说明在各自根目录的 SKILL.md、脚本在 scripts/),以派单时的实际 ls 为准,不凭记忆。需要改文件时加 --expect-changes;涉及浏览器时写明用 opencli(opencli browser <会话名>),禁止 Playwright/agent-browser。最终回复列改动与验证结果,不能只说“已完成”。 取证类 brief(打开外站、查 DNS/RDAP、批量读页面)还要写重试与降级规则:打开失败先同 URL 重开或刷新,间隔约 5 秒,最多 5 次;单项仍取不到记「无法验证」继续后面的项,只有站点整体不可达、验证码、限流、登录墙才整体停;否则执行者会因一次瞬时失败按「做不到就停」整单收工。
brief 里带上已知坑清单(避免白跑一轮):浏览器自动化 Chromium 在重页面会崩,直接写 firefox.launch({headless:true}) 并每页独立实例(用的是 Playwright 自带的 Firefox,装在 ~/Library/Caches/ms-playwright/firefox-*,本机不需要安装 Firefox 应用,也不会弹窗);页面有 Cookie 提示时先点「拒绝」或预置 localStorage 再测量;创建 worktree 前先 git worktree remove --force 并 git branch -D 清掉同名旧工作区;指定模型前先 fleet list-models 确认真有(gemini-3.1-pro 当前不在配置里,默认用 gemini-3.8-flash);fleet code 整条命令放 Bash 后台,不套 &;pull --rebase 超时重试一次;macOS 的 sed 用 sed -i ''。
把 --cwd 指向的目录及其项目配置当作不可信输入核对;网关路径使用 Claude Agent SDK 的 bypassPermissions,执行者可读写文件和运行命令,没有工具调用沙箱。只对可信目录派单,保护他人改动,不打印密钥。默认执行者系统提示禁止调用 Agent/Task 工具或再次转派,额外 --system-prompt 会追加其后。fleet code 默认 danger-full-access(可读写任意路径、可联网,含本机代理),--review 使用 read-only;详见 README 的安全边界。
fleet judge state.txt questions.json [--json]:state 为文本或 .json 文件;questions 是 { "key": { "type": "noul"|"choice"|"score", "instructions": "..." } }。choice 和 score 必须带 criteria。JEV 只做结构化判断,不生成自由文本,也不能用 run。旧写法 fleet judge --model jev --state-file state.txt --questions-file questions.json 仍可用。
questions.json 可按需选用其中一种或组合使用:
{
"is_urgent": { "type": "noul", "instructions": "这条消息是否紧急?" },
"team": { "type": "choice", "instructions": "该由哪个团队处理?", "criteria": { "billing": "付款或退款", "technical": "故障或集成" } },
"frustration": { "type": "score", "instructions": "客户有多沮丧?", "criteria": ["平静", "沮丧", "愤怒"] }
}© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/bash/skill-yan-labs-yan-skills of majiayu000/claude-skill-registry.
Open the folder on GitHubat commit 2d14a69
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 8, 2026.
Agent Fleet next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agent Fleet this skillmajiayu000/claude-skill-registry | 666 | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Nano Banana Pro Prompts Recommend SkillYouMind-OpenLab/nano-banana-pro-prompts-recommend-skill | 1.9k | 1 repos | ~4.1k | Automated safety check: Pass | None | |
| Seedance Storyboard Generatorliangdabiao/Seedance2-Storyboard-Generator | 2.5k | — | ~2.2k | Automated safety check: Pass | None | |
| AI Image Creatorcentminmod/my-claude-code-setup | 2.7k | — | ~8.1k | Automated safety check: Notes | MIT | |
| Nano Banananexu-io/nexu | 3.3k | — | ~757 | Automated safety check: Pass | MIT | |
| Gemini Imagetyrchen/geektime-bootcamp-ai | 236 | 1 repos | ~1.1k | Automated safety check: Pass | None |
YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill
Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs.
liangdabiao/Seedance2-Storyboard-Generator
专业的Seedance 2.0平台AI视频脚本和分镜生成器。当用户要求:(1) 将文章/故事转换为视频脚本,(2) 生成Seedance 2.0分镜提示词,(3) 规划多集AI视频系列,(4) 为GPT-Image-2、Seedream、Nano Banana…
centminmod/my-claude-code-setup
Generate, edit-from-reference, or analyze images with AI via OpenRouter (Gemini, GPT Image, Seedream, Qwen, MAI, Grok, FLUX.2, Recraft, Muse, Riverflow; Cloudflare AI Gateway BYOK).
nexu-io/nexu
Generate or edit images via Nano Banana image models. An agent skill from nexu-io/nexu.
tyrchen/geektime-bootcamp-ai
Reference guide for using google-genai Python library to generate images with gemini-3-pro-image-preview model.
WJZ-P/gemini-skill
通过 Gemini 官网(gemini.google.com)执行生图、对话等操作。用户提到"生图/画图/绘图/nano banana/nanobanana/生成图片"等关键词时触发。操作方式分三级优先级:首选 MCP 工具 → 次选 Skill 脚本 → 最次连接 Skill 浏览器手动操作(需用户授权)。禁止自行启动外部浏览器访问 Gemini。
majiayu000/claude-skill-registry
Multi-source deep research using firecrawl and exa MCPs. An agent skill from majiayu000/claude-skill-registry.
majiayu000/claude-skill-registry
Neural search via Exa MCP for web, code, and company research.
majiayu000/claude-skill-registry
Unified media generation via fal.ai MCP — image, video, and audio.
majiayu000/claude-skill-registry
Interact with Zotero reference management libraries using the pyzotero Python client.
majiayu000/claude-skill-registry
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server.
majiayu000/claude-skill-registry
Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner.
Works with
Categories
使用本机 fleet 分派 Codex GPT-6、Gemini、Grok 或 JEV 任务,或调用 Kollab 图片/视频/音频/多模态能力时使用;包括用户点名 agent-fleet、Nano Banana、nanobanana、香蕉、便宜模型、多模型并行,用户说“让 Codex 或 GPT-6 做某事”的编码、调研与 review 派单,以及按全局 CLAUDE.md §2…. Agent Fleet is an agent skill from majiayu000/claude-skill-registry.
Agent Fleet fits situations like: tasks that involve Image generation.
Run `npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a claude-code`. Or copy the skill folder (skills/bash/skill-yan-labs-yan-skills in majiayu000/claude-skill-registry) into .claude/skills/agent-fleet in your project. Claude Code loads it when a task matches its description.
Run `npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a codex`. Or copy the skill folder (skills/bash/skill-yan-labs-yan-skills in majiayu000/claude-skill-registry) into .agents/skills/agent-fleet in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill agent-fleet -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-fleet, .gemini/skills/agent-fleet, .github/skills/agent-fleet and .opencode/skills/agent-fleet in your project.
Going by SKILL.md and its folder, Agent Fleet needs credentials named KOLLAB_API_KEY, KOLLAB_STANDALONE_API_KEY and KOLLAB_API_TOKEN. Our summary lists: A credential in KOLLAB_API_KEY; A credential in KOLLAB_STANDALONE_API_KEY.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Agent Fleet is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Agent Fleet: Nano Banana Pro Prompts Recommend Skill (YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill, 1.9k stars), Seedance Storyboard Generator (liangdabiao/Seedance2-Storyboard-Generator, 2.5k stars), AI Image Creator (centminmod/my-claude-code-setup, 2.7k stars) and Nano Banana (nexu-io/nexu, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.
Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.