Object Storage
sickn33/agentic-awesome-skills
Configure object storage with S3, GCS, and MinIO. An agent skill from sickn33/agentic-awesome-skills.
StelloAgent 创建配置教程。完整说明 createStelloAgent 的每个配置项,包含 sessionDefaults、storage、tools、skills、forkProfiles、session 层接入、orchestration 等。
$ npx skills add stello-agent/stello --skill stello-agent-creation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install stello-agent/stello stello-agent-creation --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/stello-agent/stello.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/stello-agent-creation .claude/skills/stello-agent-creation && 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 "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .claude/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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/stello-agent/stello/tree/main/.agents/skills/stello-agent-creationType 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 stello-agent/stello --skill stello-agent-creation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install stello-agent/stello stello-agent-creation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/stello-agent/stello.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/stello-agent-creation .agents/skills/stello-agent-creation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .agents/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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 stello-agent/stello --skill stello-agent-creation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install stello-agent/stello stello-agent-creation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/stello-agent/stello.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/stello-agent-creation .cursor/skills/stello-agent-creation && 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 "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .cursor/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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/stello-agent/stello.git --path .agents/skills/stello-agent-creation--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 stello-agent/stello --skill stello-agent-creation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install stello-agent/stello stello-agent-creation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/stello-agent/stello.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/stello-agent-creation .gemini/skills/stello-agent-creation && 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 "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .gemini/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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 stello-agent/stello stello-agent-creationInstalls 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 stello-agent/stello --skill stello-agent-creation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/stello-agent/stello.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/stello-agent-creation .github/skills/stello-agent-creation && 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 "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .github/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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 stello-agent/stello --skill stello-agent-creation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install stello-agent/stello stello-agent-creation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/stello-agent/stello.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/stello-agent-creation .opencode/skills/stello-agent-creation && 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 "stello-agent-creation" agent skill from https://github.com/stello-agent/stello/tree/main/.agents/skills/stello-agent-creation into .opencode/skills/stello-agent-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stello-agent-creation", 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.
stello-agent-creationStelloAgent 创建配置教程。完整说明 createStelloAgent 的每个配置项,包含 sessionDefaults、storage、tools、skills、forkProfiles、session 层接入、orchestration 等。
Stello Agent Creation is an agent skill from stello-agent/stello. StelloAgent 创建配置教程。完整说明 createStelloAgent 的每个配置项,包含 sessionDefaults、storage、tools、skills、forkProfiles、session 层接入、orchestration 等。
Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Conversations aren't linear — why should AI chats be? The first open-source conversation topology engine. Auto-branching session trees, inherited memory, star-map visualization… The licence is Apache-2.0.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 3bc9493. 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 typescript).
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:
OPENAI_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Stello Agent Creation loads about 3.2k tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 280 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 stello-agent/stello at commit 3bc9493, republished under its Apache-2.0 licence (© stello-agent). 280 words, ~3,247 tokens.
.claude/skills/stello-agent-creation/SKILL.md (or your agent's skills folder).import {
createStelloAgent,
ToolRegistryImpl,
SkillRouterImpl,
type EngineLifecycleAdapter,
type ConfirmProtocol,
type SessionTree,
} from '@stello-ai/core'
import type { SessionStorage } from '@stello-ai/session'
const agent = createStelloAgent({
sessions, // SessionTree 实例(拓扑)
storage: sessionStorage, // SessionStorage 实例(内容;orchestrator-facing SDK 依赖)
capabilities: {
lifecycle, // EngineLifecycleAdapter
tools: new ToolRegistryImpl(),
skills: new SkillRouterImpl(),
confirm: { ... },
},
session: {
sessionLoader: async (id) => ({ session: loadedSession, config: null }),
},
})interface StelloAgentConfig {
sessions: SessionTree // 拓扑树(必填)
storage?: SessionStorage // 内容存储(orchestrator-facing 数据 SDK 依赖)
sharedMemory?: SharedMemoryStore // Agent 级共享 memory;注入后索引每 send 前由 adapter 自动注入
sessionDefaults?: SessionConfig // 所有 session 的 agent 级默认(fork 合成链最低优先级)
capabilities: { // 能力注入(必填)
lifecycle: EngineLifecycleAdapter
tools: EngineToolRuntime // 用户自定义工具
skills: SkillRouter // Skill 注册表
confirm: ConfirmProtocol
profiles?: ForkProfileRegistry // Fork 模板(可选)
}
session?: StelloAgentSessionConfig // Session 层接入(可选)
runtime?: StelloAgentRuntimeConfig // Runtime 策略(可选)
orchestration?: StelloAgentOrchestrationConfig // 编排策略(可选)
}所有 Session 共用
sessionDefaults。Root 没有专属配置,与子 session 走同一套 fork 合成链(详见 fork-design)。 "全 memory → 反思 → 定向 insight" 的循环由应用层基于 orchestrator-facing SDK 自行实现(不在配置注入点里)。
storage —— Orchestrator-facing 数据 SDKstorage: SessionStorage 注入后,StelloAgent 暴露以下 data-IO 方法(详见 stello-agent-usage):
listSessionDigests(filter?) —— 批量收集所有 Session 的 { id, label, status, memory, insight }getSessionMetadata(id) —— 单个 Session 的 { memory, insight }listMessages(id, options?) —— 读取指定 Session 的 L3 消息putMemory(id, content) / putInsight(id, content) / clearInsight(id)重要:应用层需保证 sessions(拓扑)与 storage(内容)指向同一份后端——SessionTree.listAll() 返回的 id 必须能在 SessionStorage 上 getMemory。
未注入 storage 时,上述方法会抛错;其余编排能力(turn / stream / fork / archive)不受影响。
sessionDefaults —— Agent 级默认配置所有 Session 的配置基线,fork 合成链的最低优先级层。
createStelloAgent({
sessionDefaults: {
llm: defaultLlm, // 默认 LLM
consolidateFn: defaultConsolidateFn, // 默认 L3→memory 提炼函数
compressFn: defaultCompressFn, // 默认上下文压缩函数
systemPrompt: '你是一个助手。', // 默认 system prompt(可被 fork 覆盖)
skills: undefined, // undefined = 继承全局 SkillRouter(默认)
},
// ...
})SessionConfig 完整字段:
interface SessionConfig {
systemPrompt?: string
llm?: LLMAdapter
tools?: LLMCompleteOptions['tools']
skills?: string[] // undefined=继承全局;[]=禁用所有 skill;['a','b']=白名单
consolidateFn?: SessionCompatibleConsolidateFn
compressFn?: SessionCompatibleCompressFn
}Root session 的固化配置由你创建 root 时通过
agent.createSession({ label })+ 后续sessions.putConfig(rootId, ...)设置——或在sessionDefaults给出全局默认即可。Root 没有特殊待遇。
capabilities — 能力注入tools — 用户自定义工具import { ToolRegistryImpl } from '@stello-ai/core'
const toolRegistry = new ToolRegistryImpl()
toolRegistry.register({
name: 'save_note',
description: '保存笔记到当前会话',
parameters: {
type: 'object',
properties: {
note: { type: 'string', description: '笔记内容' },
},
required: ['note'],
},
execute: async (args, _ctx) => {
await db.saveNote(String(args.note))
return { success: true, data: { saved: true } }
},
})要点:
parameters 是 JSON Schema 格式,LLM 据此生成参数execute(args, ctx) 返回 { success: true, data: ... } 或 { success: false, error: '...' }stello_create_session / activate_skill)需要在 ToolRegistryImpl([...]) 构造时显式 opt-in(参考 createSessionTool() / activateSkillTool(skills) factory)skills — Skill 注册表Skill 是两级渐进式加载的 prompt 片段:LLM 始终看到 name + description,主动调用 activate_skill 后注入完整 content。
import { SkillRouterImpl, loadSkillsFromDirectory } from '@stello-ai/core'
const skillRouter = new SkillRouterImpl()
// 方式一:代码注册
skillRouter.register({
name: 'code-review',
description: '代码审查专家,激活后按标准流程审查代码质量',
content: `你现在是代码审查专家。...`,
})
// 方式二:从目录批量加载(标准 agent skills 格式)
const fileSkills = await loadSkillsFromDirectory('./skills')
for (const skill of fileSkills) {
skillRouter.register(skill)
}activate_skill 是否对 LLM 可见取决于 skills.getAll().length > 0,以及该 session 的 SessionConfig.skills 白名单(详见 fork-design 的 skills 三态语义)。
profiles — Fork Profile 注册表(可选)ForkProfile 是预定义的 fork 配置模板,extends SessionConfig。LLM 调用 stello_create_session 时可通过 profile 参数引用。
import { ForkProfileRegistryImpl } from '@stello-ai/core'
const forkProfiles = new ForkProfileRegistryImpl()
forkProfiles.register('poet', {
systemPrompt: '你是一位诗人。所有回复必须用诗歌形式。',
systemPromptMode: 'preset',
})
forkProfiles.register('region-expert', {
systemPromptFn: (vars) => `你是${vars.region}地区的留学专家。`,
systemPromptMode: 'preset',
llm: cheaperLlmAdapter,
skills: ['search', 'summarize'],
consolidateFn: researchConsolidateFn,
})
forkProfiles.register('researcher', {
systemPrompt: '你是研究助手,善于深入分析。',
systemPromptMode: 'prepend',
context: 'inherit',
})完整字段、合成规则、systemPromptMode 三种模式见 skill fork-design。
lifecycle — 生命周期适配器const lifecycle: EngineLifecycleAdapter = {
bootstrap: async (sessionId) => ({
context: await memory.assembleContext(sessionId),
session: await sessions.get(sessionId),
}),
afterTurn: async (sessionId, userMsg, assistantMsg) => {
await memory.appendRecord(sessionId, userMsg)
await memory.appendRecord(sessionId, assistantMsg)
return { coreUpdated: false, memoryUpdated: false, recordAppended: true }
},
}confirm — 确认协议const confirm: ConfirmProtocol = {
async confirmSplit(proposal) {
return agent.forkSession(proposal.parentId, {
label: proposal.suggestedLabel,
})
},
async dismissSplit() {},
async confirmUpdate() {},
async dismissUpdate() {},
}session — Session 层接入StelloAgentSessionConfig 是纯 I/O 数据加载,按 ID 加载 Session 实例与其固化配置。
session: {
sessionLoader: async (sessionId) => {
const session = await loadSession(sessionId, {
storage: sessionStorage,
llm: currentLlm,
})
if (!session) throw new Error(`Session not found: ${sessionId}`)
return {
session, // SessionCompatible 实例
config: null, // SerializableSessionConfig | null
}
},
// 可选:自定义 send() 结果序列化(默认 JSON)
serializeSendResult: (result) => JSON.stringify(result),
// 可选:自定义 tool call 解析器(默认 sessionSendResultParser)
toolCallParser: customParser,
}所有 Session(含 root)由同一个 sessionLoader 按 id 加载。Root 与子 session 的差异只在拓扑 (TopologyNode.parentId === null),loader 无需区分。
两种 session 接入方式:
| 方式 | 配置 | 适用场景 |
|---|---|---|
| Session 适配 | session.sessionLoader | 使用 @stello-ai/session 包(推荐) |
| 直接提供 runtime | runtime.resolver | 自定义 session 实现 |
orchestration — 编排策略(可选)consolidateEveryNTurnsorchestration: {
consolidateEveryNTurns: 5,
}每 5 轮自动 consolidate(fire-and-forget)。
splitGuardimport { SplitGuard } from '@stello-ai/core'
orchestration: {
splitGuard: new SplitGuard(sessions, {
minTurns: 3,
cooldownTurns: 5,
}),
}hooksorchestration: {
hooks: {
onRoundStart({ sessionId, input }) {},
onRoundEnd({ sessionId, turn }) {},
onSessionFork({ parentId, child }) {},
onToolCall({ sessionId, toolCall }) {},
onError({ source, error }) {},
},
}所有 hooks fire-and-forget:抛错时 emit error 事件,不中断对话。
import {
createStelloAgent,
ToolRegistryImpl,
SkillRouterImpl,
ForkProfileRegistryImpl,
SplitGuard,
SessionTreeImpl,
NodeFileSystemAdapter,
InMemorySharedMemoryStore,
createSessionTool,
activateSkillTool,
memoryRecallTool,
memoryRememberTool,
memoryForgetTool,
} from '@stello-ai/core'
import {
loadSession,
InMemoryStorageAdapter,
createOpenAICompatibleAdapter,
} from '@stello-ai/session'
// ─── 基础设施 ───
const fs = new NodeFileSystemAdapter('./data')
const sessions = new SessionTreeImpl(fs)
const sessionStorage = new InMemoryStorageAdapter()
const sharedMemory = new InMemorySharedMemoryStore()
const llm = createOpenAICompatibleAdapter({
apiKey: process.env.OPENAI_API_KEY!,
model: 'gpt-4o',
})
// ─── 自定义 Tools(含 opt-in 内置 tool) ───
const skills = new SkillRouterImpl()
skills.register({
name: 'data-analysis',
description: '数据分析模式:激活后按结构化流程分析数据',
content: '你是数据分析专家...',
})
const toolRegistry = new ToolRegistryImpl([
createSessionTool(), // 内置 fork tool(opt-in)
activateSkillTool(skills), // 内置 skill 激活 tool(opt-in)
memoryRecallTool(), // 共享 memory 读取 tool(opt-in)
memoryRememberTool(), // 共享 memory 写入 tool(opt-in)
memoryForgetTool(), // 共享 memory 删除 tool(opt-in)
])
toolRegistry.register({
name: 'search_knowledge',
description: '搜索知识库',
parameters: {
type: 'object',
properties: { query: { type: 'string' } },
required: ['query'],
},
execute: async (args, _ctx) => ({
success: true,
data: await knowledgeBase.search(String(args.query)),
}),
})
// ─── Fork Profiles ───
const profiles = new ForkProfileRegistryImpl()
profiles.register('researcher', {
systemPrompt: '你是研究助手,善于深入分析。',
systemPromptMode: 'prepend',
context: 'inherit',
skills: ['search', 'data-analysis'],
})
// ─── 创建 Agent ───
let agent: ReturnType<typeof createStelloAgent>
agent = createStelloAgent({
sessions,
storage: sessionStorage, // 注入内容存储,启用 orchestrator-facing SDK
sharedMemory, // 注入共享 memory,启用 4 个 SDK 方法 + 索引自动注入
sessionDefaults: {
llm,
systemPrompt: '你是一个助手。',
// consolidateFn / compressFn 由应用层闭包注入
},
session: {
sessionLoader: async (sessionId) => {
const session = await loadSession(sessionId, { storage: sessionStorage, llm })
if (!session) throw new Error(`Session not found: ${sessionId}`)
return { session, config: null }
},
},
capabilities: {
lifecycle: {
bootstrap: async (sessionId) => ({
context: { core: {}, memories: [], currentMemory: null, scope: null },
session: await sessions.get(sessionId),
}),
afterTurn: async () => ({ coreUpdated: false, memoryUpdated: false, recordAppended: true }),
},
tools: toolRegistry,
skills,
profiles,
confirm: {
confirmSplit: async (p) => agent.forkSession(p.parentId, { label: p.suggestedLabel }),
dismissSplit: async () => {},
confirmUpdate: async () => {},
dismissUpdate: async () => {},
},
},
orchestration: {
consolidateEveryNTurns: 5,
splitGuard: new SplitGuard(sessions, { minTurns: 3, cooldownTurns: 5 }),
hooks: {
onSessionFork({ parentId, child }) {
console.log(`Fork: ${parentId} → ${child.id} (${child.label})`)
},
},
},
})
// ─── 创建 root session ───
const root = await agent.createSession({ label: 'Main' })
// ─── 开始对话 ───
await agent.enterSession(root.id)
const result = await agent.turn(root.id, '帮我分析一下市场趋势')
console.log(result.turn.finalContent)"全 memory → 反思 → 定向 insight" 的循环由应用层实现:
import { collectLLMStream } from '@stello-ai/session'
async function reflect(agent: StelloAgent, llm: LLMAdapter): Promise<void> {
const digests = await agent.listSessionDigests({ status: 'active' })
const reflection = await collectLLMStream(llm.stream([
{ role: 'system', content: '你是 orchestrator,请综合各 session 的 memory,对需要纠偏/补充信息的 session 写出 insight。' },
{ role: 'user', content: JSON.stringify(digests) },
]))
// 解析 reflection 输出(自定义 schema),调用 putInsight 定向回写
const { insights } = JSON.parse(reflection.content ?? '{}') as { insights: Record<string, string> }
await Promise.all(
Object.entries(insights).map(([sessionId, content]) =>
agent.putInsight(sessionId, content),
),
)
}Agent 创建后的运行时操作(createSession / turn / stream / fork / attach / detach / 数据 SDK 等)见 skill stello-agent-usage。
© stello-agent, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/stello-agent-creation of stello-agent/stello.
Open the folder on GitHubat commit 3bc9493
Stello Agent Creation 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 |
|---|---|---|---|---|---|---|
| Stello Agent Creation this skillstello-agent/stello | 112 | — | ~3.2k | Automated safety check: Pass | Apache-2.0 | |
| Object Storagesickn33/agentic-awesome-skills | 47k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Neon Object Storagesickn33/agentic-awesome-skills | 47k | 1 repos | ~2.9k | Automated safety check: Notes | Apache-2.0 | |
| Remotion Video Creationaffaan-m/ECC | 276k | 2 repos | ~910 | Automated safety check: Pass | MIT | |
| Web Storagethedaviddias/Front-End-Checklist | 74k | — | ~506 | Automated safety check: Pass | MIT | |
| Token Storage Securitythedaviddias/Front-End-Checklist | 74k | — | ~604 | Automated safety check: Pass | MIT |
sickn33/agentic-awesome-skills
Configure object storage with S3, GCS, and MinIO. An agent skill from sickn33/agentic-awesome-skills.
sickn33/agentic-awesome-skills
S3-compatible object storage that branches with your Neon project, so files and the database stay in sync across every branch.
affaan-m/ECC
Best practices for Remotion - Video creation in React. An agent skill from affaan-m/ECC.
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing scripts, client components, bundles, or runtime behavior related to Use Web Storage API safely.
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing authentication implementation, setting up a new auth system, or evaluating whether the current token storage approach exposes the application to XSS-based…
Jeffallan/claude-skills
Sets up Django 4.2+ to keep static and media files on AWS S3 through django-storages, with public and private backends, presigned URLs and CloudFront.
stello-agent/stello
Fork 机制完整说明。覆盖 ForkProfile 与 EngineForkOptions 的字段对齐、四层 fallback 合成链(sessionDefaults → parent → profile → forkOptions)、systemPrompt 合成三种模式、skills 三态语义、持久化边界(SerializableSessionConfig 只固化…
stello-agent/stello
Stello 框架内所有 LLM 调用位置的消息结构速查。覆盖 Session 对话、compress、consolidate;应用层 reflection 调用由 orchestrator 自行决定。
stello-agent/stello
Session 对话单元的设计理念、上下文组装规则、memory / insight 槽位语义、单一 Session 模型与跨 Session 通信模型。
stello-agent/stello
StelloAgent 运行时使用教程。覆盖 Session 生命周期、createSession、turn/stream 对话、fork 配置合成链、orchestrator-facing 数据 SDK、runtime 管理、热更新等运行时 API。
stello-agent/stello
Stello 仓库总览入口。快速理解各包的关系、推荐入口、编排模型、单一 Session 模型. An agent skill from stello-agent/stello.
stello-agent/stello
存储接口的设计原则、SessionMeta 与 TopologyNode 解耦、上下文槽位、单一 SessionStorage 接口。触发条件:理解或实现 SessionStorage / SessionTree。
StelloAgent 创建配置教程。完整说明 createStelloAgent 的每个配置项,包含 sessionDefaults、storage、tools、skills、forkProfiles、session 层接入、orchestration 等。. Stello Agent Creation is an agent skill from stello-agent/stello.
Run `npx skills add stello-agent/stello --skill stello-agent-creation -a claude-code`. Or copy the skill folder (.agents/skills/stello-agent-creation in stello-agent/stello) into .claude/skills/stello-agent-creation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add stello-agent/stello --skill stello-agent-creation -a codex`. Or copy the skill folder (.agents/skills/stello-agent-creation in stello-agent/stello) into .agents/skills/stello-agent-creation 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 stello-agent/stello --skill stello-agent-creation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/stello-agent-creation, .gemini/skills/stello-agent-creation, .github/skills/stello-agent-creation and .opencode/skills/stello-agent-creation in your project.
Going by SKILL.md and its folder, Stello Agent Creation needs credentials named OPENAI_API_KEY. Our summary lists: A credential in OPENAI_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.
Stello Agent Creation is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.2k tokens (SKILL.md is roughly 13k 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 Stello Agent Creation: Object Storage (sickn33/agentic-awesome-skills, 47k stars), Neon Object Storage (sickn33/agentic-awesome-skills, 47k stars), Remotion Video Creation (affaan-m/ECC, 276k stars) and Web Storage (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
stello-agent (a GitHub organization) maintains it in stello-agent/stello, which has 112 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on July 24, 2026.
Source: stello-agent/stello on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.