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sandbase
Access 2,000+ AI models and API tools through one MCP interface for inference, media generation, search, scraping, embeddings, social data, and structured retri
Resumen
Access 2,000+ AI models and API tools through one MCP interface for inference, media generation, search, scraping, embeddings, social data, and structured retrieval. Use sandbase_discover before building custom integrations or declaring external data inaccessible; prefer an existing dedicated tool or API key when the user already has one.
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Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.
SandBase MCP
SandBase provides access to 2,000+ AI models and API tools through a unified MCP interface. One account covers LLMs, image generation, video generation, audio, embeddings, web scraping, social media APIs, and more.
Setup
If the six sandbase_* MCP tools are not already available, connect the current machine with the immutable v0.1.17 release:
npx -y https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz connect
For a checksum-verified install, download the same immutable asset first and verify the SHA-256 published with the GitHub Release:
curl -fLO https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz
printf '%s %s\n' '1ad535b2899ca460b57b3c268aef278fee28fd28e649a89b92951514fd71fffa' 'sandbaseai-cli-0.1.17.tgz' | shasum -a 256 -c -
npx -y ./sandbaseai-cli-0.1.17.tgz connect
Approve the browser sign-in once. Authentication happens with SandBase in the browser; the CLI stores the resulting local session record with restricted file permissions. The CLI detects supported clients, installs the local MCP bridge and this managed Skill, and verifies the resulting configuration. No provider API keys are required. Invoke the same release URL with doctor to inspect the connection or unregister to remove only SandBase-managed state.
This file is managed by SandBase CLI and may be replaced during a later CLI-managed update, so keep custom instructions in a separate Skill. Check the official repository for newer releases before copying it independently.
When to Use SandBase
Use SandBase when the user needs:
- LLM inference (GPT, Claude, Gemini, DeepSeek, Qwen, etc.)
- Image generation (Flux, DALL-E, Ideogram, Recraft)
- Video generation (Kling, MiniMax, Runway, Luma)
- Audio (ElevenLabs TTS, Whisper STT)
- Embeddings (OpenAI, Voyage)
- Web scraping and content extraction (Exa, Firecrawl, Tavily)
- Social media data (Twitter/X, Instagram, TikTok, YouTube, LinkedIn, Reddit, Xiaohongshu, Weibo, Bilibili)
- Search (Google, Scholar, News, Shopping)
- Any structured data API the user doesn't already have access to
Do NOT use SandBase when:
- The user has their own API key or dedicated MCP server for that specific service
- The task is purely local (file editing, code generation from context)
- The user explicitly asks to use a different tool
SandBase fills gaps in the user's stack — it doesn't replace tools they already have.
Tools
| Tool | Purpose |
|---|---|
sandbase_discover | Search all 2,000+ AI models |
sandbase_inspect | Get input schema, pricing, and execution template |
sandbase_run | Execute a model or API endpoint |
sandbase_run_get | Get status/result of an async run |
sandbase_runs | List recent API calls with cost |
sandbase_account | Check account balance (free) |
Standard Workflow
Always follow: discover → inspect → run
1. sandbase_discover(q: "twitter posts")
→ Returns matching endpoints with names, types, vendors
2. sandbase_inspect(name: "sandbase_twitter_web_search_timeline")
→ Returns inputSchema, pricing, and execute_as template
3. sandbase_run(name: "sandbase_twitter_web_search_timeline", arguments: {"keyword": "AI"})
→ Returns result directly (sync) or run_id (async)
For async runs (video gen, large scraping):
4. sandbase_run_get(run_id: "pred_abc123")
→ Poll until status is "completed" or "failed"
Shortcut: If you already know the model name, skip step 1.
Search Tips
sandbase_discover supports:
| Parameter | Purpose | Example |
|---|---|---|
q | Text search (supports Chinese: 推特, 小红书, 搜索) | "twitter search", "图片生成" |
type | Filter by model type | "llm", "api", "multimodal", "embedding" |
vendor | Filter by vendor slug | "openai", "twitter", "anthropic" |
limit | Max results (default 20) | 10 |
Tips:
- Use short noun phrases: "twitter posts", "image generation", "web scraping"
- Chinese aliases work: 推特→twitter, 小红书→xiaohongshu, 抖音→tiktok
- Combine type + query for precision:
type: "llm", q: "claude" - Empty query with type filter returns popular models of that type
Pricing
Use sandbase_inspect to see pricing before running:
LLM models: Per million tokens
{ "pricing": { "input_per_million": "2.500000", "output_per_million": "10.000000" } }
API tools (image, video, scraping): Per call
{ "pricing": { "base_price": "0.003000" } }
Check balance:
sandbase_account() → {"balance": "9.52", "currency": "USD"}
Async Runs
Some endpoints (video generation, large scraping) are async:
sandbase_run(...)returns{"status": "running", "run_id": "pred_abc123"}- Poll with
sandbase_run_get(run_id: "pred_abc123")every 5-10 seconds - When
statusis"completed"— result is ready - When
statusis"failed"— check error and retry
Error Handling
| Error | User Guidance |
|---|---|
tool not found | Wrong name. Use sandbase_discover to search. |
invalid params | Check schema from sandbase_inspect. |
run not found | Invalid run_id. Check sandbase_runs for valid IDs. |
| Authentication (401) | Key invalid. Run sandbase connect to re-auth. |
| Insufficient balance (402) | Top up at SandBase Dashboard. |
| Rate limited (429) | Wait and retry. |
| Provider unavailable | Upstream is down. Try later or use different model. |
Cost Awareness
- Check balance with
sandbase_accountbefore multiple calls - LLM costs scale with token count — keep prompts concise
- Image/video have fixed per-call costs — inspect first
- Report costs when the user seems budget-conscious
Example Flows
Twitter search
sandbase_discover(q: "twitter search", type: "api")
sandbase_inspect(name: "sandbase_twitter_web_search_timeline")
sandbase_run(name: "sandbase_twitter_web_search_timeline", arguments: {"keyword": "AI agents"})
Image generation
sandbase_discover(q: "flux", type: "multimodal")
sandbase_inspect(name: "sandbase_flux_schnell")
sandbase_run(name: "sandbase_flux_schnell", arguments: {"prompt": "A mountain lake at sunset"})
LLM inference
sandbase_inspect(name: "sandbase_openai_gpt_4o")
sandbase_run(name: "sandbase_openai_gpt_4o", arguments: {
"messages": [{"role": "user", "content": "Explain quantum computing briefly"}]
})
Check recent costs
sandbase_runs(limit: 5)
→ [{ "model": "openai/gpt-4o", "cost": "0.000325", "status": "completed" }, ...]
Rules
- Discover first — always verify a tool exists before running it.
- Inspect before run — read the inputSchema. Never guess parameters.
- Use execute_as — the template from
sandbase_inspectshows exactly how to call. - Respect the user's stack — don't replace their existing tools.
- Start small — use small limits on first calls for scraping/search tools.
- Poll async runs — use
sandbase_run_getfor long-running operations. - Report costs — mention pricing when the user cares about budget.
- One call per turn — wait for results before the next call.
Metadatos del archivo
name: sandbase version: 0.1.17 disable-model-invocation: true description: Access 2,000+ AI models and API tools through one MCP interface for inference, media generation, search, scraping, embeddings, social data, and structured retrieval. Use sandbase_discover before building custom integrations or declaring external data inaccessible; prefer an existing dedicated tool or API key when the user already has one.
Ver texto original
---
name: sandbase
version: 0.1.17
disable-model-invocation: true
description: Access 2,000+ AI models and API tools through one MCP interface for inference, media generation, search, scraping, embeddings, social data, and structured retrieval. Use sandbase_discover before building custom integrations or declaring external data inaccessible; prefer an existing dedicated tool or API key when the user already has one.
---
# SandBase MCP
<!-- sandbase-cli-managed: sandbase -->
SandBase provides access to 2,000+ AI models and API tools through a unified MCP interface. One account covers LLMs, image generation, video generation, audio, embeddings, web scraping, social media APIs, and more.
---
## Setup
If the six `sandbase_*` MCP tools are not already available, connect the current machine with the immutable v0.1.17 release:
```sh
npx -y https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz connect
```
For a checksum-verified install, download the same immutable asset first and verify the SHA-256 published with the GitHub Release:
```sh
curl -fLO https://github.com/sandbaseai/cli/releases/download/v0.1.17/sandbaseai-cli-0.1.17.tgz
printf '%s %s\n' '1ad535b2899ca460b57b3c268aef278fee28fd28e649a89b92951514fd71fffa' 'sandbaseai-cli-0.1.17.tgz' | shasum -a 256 -c -
npx -y ./sandbaseai-cli-0.1.17.tgz connect
```
Approve the browser sign-in once. Authentication happens with SandBase in the browser; the CLI stores the resulting local session record with restricted file permissions. The CLI detects supported clients, installs the local MCP bridge and this managed Skill, and verifies the resulting configuration. No provider API keys are required. Invoke the same release URL with `doctor` to inspect the connection or `unregister` to remove only SandBase-managed state.
This file is managed by SandBase CLI and may be replaced during a later CLI-managed update, so keep custom instructions in a separate Skill. Check the [official repository](https://github.com/sandbaseai/cli) for newer releases before copying it independently.
---
## When to Use SandBase
**Use SandBase when the user needs:**
- LLM inference (GPT, Claude, Gemini, DeepSeek, Qwen, etc.)
- Image generation (Flux, DALL-E, Ideogram, Recraft)
- Video generation (Kling, MiniMax, Runway, Luma)
- Audio (ElevenLabs TTS, Whisper STT)
- Embeddings (OpenAI, Voyage)
- Web scraping and content extraction (Exa, Firecrawl, Tavily)
- Social media data (Twitter/X, Instagram, TikTok, YouTube, LinkedIn, Reddit, Xiaohongshu, Weibo, Bilibili)
- Search (Google, Scholar, News, Shopping)
- Any structured data API the user doesn't already have access to
**Do NOT use SandBase when:**
- The user has their own API key or dedicated MCP server for that specific service
- The task is purely local (file editing, code generation from context)
- The user explicitly asks to use a different tool
SandBase fills gaps in the user's stack — it doesn't replace tools they already have.
---
## Tools
| Tool | Purpose |
|------|---------|
| `sandbase_discover` | Search all 2,000+ AI models |
| `sandbase_inspect` | Get input schema, pricing, and execution template |
| `sandbase_run` | Execute a model or API endpoint |
| `sandbase_run_get` | Get status/result of an async run |
| `sandbase_runs` | List recent API calls with cost |
| `sandbase_account` | Check account balance (free) |
---
## Standard Workflow
**Always follow: discover → inspect → run**
```
1. sandbase_discover(q: "twitter posts")
→ Returns matching endpoints with names, types, vendors
2. sandbase_inspect(name: "sandbase_twitter_web_search_timeline")
→ Returns inputSchema, pricing, and execute_as template
3. sandbase_run(name: "sandbase_twitter_web_search_timeline", arguments: {"keyword": "AI"})
→ Returns result directly (sync) or run_id (async)
```
**For async runs (video gen, large scraping):**
```
4. sandbase_run_get(run_id: "pred_abc123")
→ Poll until status is "completed" or "failed"
```
**Shortcut:** If you already know the model name, skip step 1.
---
## Search Tips
`sandbase_discover` supports:
| Parameter | Purpose | Example |
|-----------|---------|---------|
| `q` | Text search (supports Chinese: 推特, 小红书, 搜索) | `"twitter search"`, `"图片生成"` |
| `type` | Filter by model type | `"llm"`, `"api"`, `"multimodal"`, `"embedding"` |
| `vendor` | Filter by vendor slug | `"openai"`, `"twitter"`, `"anthropic"` |
| `limit` | Max results (default 20) | `10` |
**Tips:**
- Use short noun phrases: "twitter posts", "image generation", "web scraping"
- Chinese aliases work: 推特→twitter, 小红书→xiaohongshu, 抖音→tiktok
- Combine type + query for precision: `type: "llm", q: "claude"`
- Empty query with type filter returns popular models of that type
---
## Pricing
Use `sandbase_inspect` to see pricing before running:
**LLM models:** Per million tokens
```json
{ "pricing": { "input_per_million": "2.500000", "output_per_million": "10.000000" } }
```
**API tools (image, video, scraping):** Per call
```json
{ "pricing": { "base_price": "0.003000" } }
```
**Check balance:**
```
sandbase_account() → {"balance": "9.52", "currency": "USD"}
```
---
## Async Runs
Some endpoints (video generation, large scraping) are async:
1. `sandbase_run(...)` returns `{"status": "running", "run_id": "pred_abc123"}`
2. Poll with `sandbase_run_get(run_id: "pred_abc123")` every 5-10 seconds
3. When `status` is `"completed"` — result is ready
4. When `status` is `"failed"` — check error and retry
---
## Error Handling
| Error | User Guidance |
|-------|--------------|
| `tool not found` | Wrong name. Use `sandbase_discover` to search. |
| `invalid params` | Check schema from `sandbase_inspect`. |
| `run not found` | Invalid run_id. Check `sandbase_runs` for valid IDs. |
| Authentication (401) | Key invalid. Run `sandbase connect` to re-auth. |
| Insufficient balance (402) | Top up at SandBase Dashboard. |
| Rate limited (429) | Wait and retry. |
| Provider unavailable | Upstream is down. Try later or use different model. |
---
## Cost Awareness
- **Check balance** with `sandbase_account` before multiple calls
- **LLM costs** scale with token count — keep prompts concise
- **Image/video** have fixed per-call costs — inspect first
- **Report costs** when the user seems budget-conscious
---
## Example Flows
### Twitter search
```
sandbase_discover(q: "twitter search", type: "api")
sandbase_inspect(name: "sandbase_twitter_web_search_timeline")
sandbase_run(name: "sandbase_twitter_web_search_timeline", arguments: {"keyword": "AI agents"})
```
### Image generation
```
sandbase_discover(q: "flux", type: "multimodal")
sandbase_inspect(name: "sandbase_flux_schnell")
sandbase_run(name: "sandbase_flux_schnell", arguments: {"prompt": "A mountain lake at sunset"})
```
### LLM inference
```
sandbase_inspect(name: "sandbase_openai_gpt_4o")
sandbase_run(name: "sandbase_openai_gpt_4o", arguments: {
"messages": [{"role": "user", "content": "Explain quantum computing briefly"}]
})
```
### Check recent costs
```
sandbase_runs(limit: 5)
→ [{ "model": "openai/gpt-4o", "cost": "0.000325", "status": "completed" }, ...]
```
---
## Rules
1. **Discover first** — always verify a tool exists before running it.
2. **Inspect before run** — read the inputSchema. Never guess parameters.
3. **Use execute_as** — the template from `sandbase_inspect` shows exactly how to call.
4. **Respect the user's stack** — don't replace their existing tools.
5. **Start small** — use small limits on first calls for scraping/search tools.
6. **Poll async runs** — use `sandbase_run_get` for long-running operations.
7. **Report costs** — mention pricing when the user cares about budget.
8. **One call per turn** — wait for results before the next call.
Revisar el código fuente
Precio y costes de ejecución
- Obtener el skill
- Precio sin confirmar
- Ejecutarlo
- Requisitos sin confirmar. Consulta los costes del agente, API y servicios en la fuente.
- Licencia
- Apache-2.0
- Precio sin confirmar
- No hemos confirmado el precio. Los enlaces existentes al código y a la instalación siguen disponibles.
Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →
Fuente del skill registrada
La ruta de instrucciones está registrada. No implica pruebas de ejecución, seguridad ni compatibilidad.
Revisar antes de instalar: Evitar instalación automática
Licencia: Apache-2.0
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The SKILL.md excerpt is truncated, but the provided content is clear and complete enough for review.
- The skill relies on an external paid service (SandBase) which may incur costs; this is not a security issue but should be communicated to users.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 18 GitHub stars
- Stars/forks activity: 18 stars, 1 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.
Empieza con una tarea pequeña
- 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
- 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
- 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.
Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.
Fuente y notas de uso
Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.
- Repositorio fuente
- sandbaseai/cli
- Licencia
- Apache-2.0
- Versión
- 0.1.17
- Último push de GitHub
- 19 ago 2026
- Registro actualizado
- 9 oct 2026
- Ruta de instrucciones
- assets/skills/sandbase/SKILL.md
Versión declarada en el registro; consulta las versiones de la fuente.
Calidad
68/100
Prometedor
Confianza
52/100
Do not auto-install
Auditoría
71/100
Requiere revisión
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The SKILL.md excerpt is truncated, but the provided content is clear and complete enough for review.
- The skill relies on an external paid service (SandBase) which may incur costs; this is not a security issue but should be communicated to users.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 18 GitHub stars
- Stars/forks activity: 18 stars, 1 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Resultados
- —
Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.
Acceso para agentes
La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.
Más detalles
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"install": "npx skills add sandbaseai/cli --skill sandbase",
"installSafety": "standard package or runtime install path",
"permissionSurface": "secrets or environment access, shell or command execution",
"documentation": "Strong README/SKILL.md context",
"agentOutcomes": "No agent outcome data yet"
},
"outcome_evidence": {
"total": 0,
"successes": 0,
"failures": 0,
"not_relevant": 0,
"success_rate": null,
"recent_success_rate": null,
"recent_failure_rate": null,
"install_attempts": 0,
"install_success_rate": null,
"risk_blocked": 0,
"setup_required": 0,
"avg_output_quality": null,
"production_outcomes": 0,
"last_outcome_at": null,
"label": "No agent outcome data yet"
},
"auto_install": {
"allowed": false,
"sandbox_required": true,
"reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"best_for": [
"automation",
"mcp",
"cli",
"ai-models",
"codex",
"claude-code"
],
"known_risks": [
"The SKILL.md excerpt is truncated, but the provided content is clear and complete enough for review.",
"Low GitHub adoption signal",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"GitHub adoption: 18 GitHub stars",
"Stars/forks activity: 18 stars, 1 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access",
"Permission surface: secrets or environment access, shell or command execution"
]
},
"agent_proven": {
"version": "agent-proven-v1",
"score": 0,
"tier": "unproven",
"label": "Needs first agent run",
"summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
"metrics": {
"totalOutcomes": 0,
"successfulOutcomes": 0,
"failedOutcomes": 0,
"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 71,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"The SKILL.md excerpt is truncated, but the provided content is clear and complete enough for review.",
"The skill relies on an external paid service (SandBase) which may incur costs; this is not a security issue but should be communicated to users.",
"Low GitHub adoption signal",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"GitHub adoption: 18 GitHub stars"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 68,
"label": "Promising"
},
"supply": {
"track": "Research and knowledge work",
"scenario": "RAG and knowledge",
"maintenance": "2mo since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"Low GitHub adoption signal",
"The SKILL.md excerpt is truncated, but the provided content is clear and complete enough for review.",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"The skill relies on an external paid service (SandBase) which may incur costs; this is not a security issue but should be communicated to users."
],
"agent_contract": {
"task_input": "Use sandbase in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 60/100 Manual review",
"Audit: 71/100 Needs review",
"Safety: 23/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "sandbaseai-cli-sandbase (sandbase)",
"install_command": "npx skills add sandbaseai/cli --skill sandbase",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "sandbaseai-cli-sandbase",
"task": "Use sandbase in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/sandbaseai-cli-sandbase",
"api": "https://www.openagentskill.com/api/agent/skills/sandbaseai-cli-sandbase",
"audit": "https://www.openagentskill.com/skills/sandbaseai-cli-sandbase/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=sandbaseai-cli-sandbase&task=Use%20sandbase%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20sandbase%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20sandbase%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/sandbaseai-cli-sandbase/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/sandbaseai-cli-sandbase"
}
}Para el creador
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