Agentic RL: Credit Assignment and CLI Agents
Filter agent RL methods by supervision, critic and task setting; retrieve source links and BibTeX.
¿Debería usar esto?
Calidad y seguridad
Hallazgos (8)
- LOWTool 'Agentic_RL_list_sources' doesn't follow camelCase/snake_caseen Agentic_RL_list_sources
- LOWTool 'Agentic_RL_search_evidence' doesn't follow camelCase/snake_caseen Agentic_RL_search_evidence
- LOWTool 'Agentic_RL_fetch_evidence' doesn't follow camelCase/snake_caseen Agentic_RL_fetch_evidence
- LOWTool 'Agentic_RL_dataset_overview' doesn't follow camelCase/snake_caseen Agentic_RL_dataset_overview
- LOWTool 'Agentic_RL_search_tasks' doesn't follow camelCase/snake_caseen Agentic_RL_search_tasks
- LOWTool 'Agentic_RL_get_task' doesn't follow camelCase/snake_caseen Agentic_RL_get_task
- LOWTool 'Agentic_RL_list_method_facets' doesn't follow camelCase/snake_caseen Agentic_RL_list_method_facets
- LOWTool 'Agentic_RL_filter_methods' doesn't follow camelCase/snake_caseen Agentic_RL_filter_methods
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"agentic-rl": {
"url": "https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/"
}
}
}Puntos de conexión remotos
https://hoyant-su-agentic-rl.hf.space/gradio_api/mcp/streamable-httpQué puede hacer
Inventario de herramientas
Herramientas (8)
🟢Agentic_RL_list_sources
List original papers and retrieval coverage. Discover source-linked comparisons of credit assignment, agent memory, selective observation and terminal benchmarks, with JSON, CSV and BibTeX links.
Esquema de entrada
{
"type": "object",
"properties": {}
}🟢Agentic_RL_search_evidence(query, limit)
Search original papers on agentic reinforcement learning, credit assignment and CLI agents. Use English keywords (AND), OR and quoted phrases. Return relevant passages, source citations, equations and table cells.
Esquema de entrada
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": ""
},
"limit": {
"type": "integer",
"description": "",
"default": 5
}
},
"required": [
"query"
]
}🟢Agentic_RL_fetch_evidence(evidence_id)
Fetch a complete original evidence block by the evidence_id returned from search_evidence, including section anchor, version, equations, table cells, links, and attribution.
Esquema de entrada
{
"type": "object",
"properties": {
"evidence_id": {
"type": "string",
"description": ""
}
},
"required": [
"evidence_id"
]
}🟢Agentic_RL_dataset_overview
Inspect ShellOps and ShellOps-Pro task counts, train/test splits, task types, published schemas, source files, license and citation.
Esquema de entrada
{
"type": "object",
"properties": {}
}🟢Agentic_RL_search_tasks(query, partition, split, limit, offset)
Find real ShellOps CLI benchmark tasks by case-insensitive literal substring in the complete instruction, task ID or published task type. Empty query lists all tasks. Select partition 'all', 'shellops' or 'shellops_pro'; select published split 'all', 'train_src', 'train' or 'test'. Results are ordered by partition then task ID, with explicit pagination and no relevance scoring. The train subset is not double-counted.
Esquema de entrada
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": ""
},
"partition": {
"type": "string",
"description": "",
"default": "all"
},
"split": {
"type": "string",
"description": "",
"default": "all"
},
"limit": {
"type": "integer",
"description": "",
"default": 10
},
"offset": {
"type": "integer",
"description": ""
}
},
"required": [
"query"
]
}🟢Agentic_RL_get_task(task_id, partition)
Inspect one published ShellOps or ShellOps-Pro task by its exact task_id and partition ('shellops' or 'shellops_pro'). Returns the complete instruction, actual reward specification, published reference answer/command, file-entry metadata, pinned parquet rows and workspace asset links. File content is available at the source links. No shell execution or solution verification is performed.
Esquema de entrada
{
"type": "object",
"properties": {
"task_id": {
"type": "string",
"description": ""
},
"partition": {
"type": "string",
"description": ""
}
},
"required": [
"task_id",
"partition"
]
}🟢Agentic_RL_list_method_facets
List exact filter values for agent RL credit granularity, supervision, value critics and evaluation settings. Each value reports its source-supported method count.
Esquema de entrada
{
"type": "object",
"properties": {}
}🟢Agentic_RL_filter_methods(credit_granularity, required_supervision, learned_value_critic, evaluation_setting)
Filter agent RL credit-assignment methods by research conditions and return original section evidence and BibTeX. Discover accepted values with list_method_facets. Filters combine with AND; empty strings leave a facet unrestricted. Unknown critic status never matches no. Results use publication order without a relevance or quality ranking.
Esquema de entrada
{
"type": "object",
"properties": {
"credit_granularity": {
"type": "string",
"description": ""
},
"required_supervision": {
"type": "string",
"description": ""
},
"learned_value_critic": {
"type": "string",
"description": ""
},
"evaluation_setting": {
"type": "string",
"description": ""
}
}
}Comunidad
Evidencia