Server definition

Hash: sha256:d5f354198ba11c06d7fa19e5f858498ad3f6353e703ef2bbc41b39c9119f268f
What it is: What a remote MCP server returned when asked what it offers: 8 tools

The blob, as servednamed by its sha256

{
  "instructions": null,
  "tools": [
    {
      "description": "Inspect ShellOps and ShellOps-Pro task counts, train/test splits, task types, published schemas, source files, license and citation.",
      "inputSchema": {
        "properties": {},
        "type": "object"
      },
      "name": "Agentic_RL_dataset_overview",
      "outputSchema": null
    },
    {
      "description": "Fetch a complete original evidence block by the evidence_id returned from search_evidence, including section anchor, version, equations, table cells, links, and attribution.",
      "inputSchema": {
        "properties": {
          "evidence_id": {
            "description": "",
            "type": "string"
          }
        },
        "required": [
          "evidence_id"
        ],
        "type": "object"
      },
      "name": "Agentic_RL_fetch_evidence",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "credit_granularity": {
            "description": "",
            "type": "string"
          },
          "evaluation_setting": {
            "description": "",
            "type": "string"
          },
          "learned_value_critic": {
            "description": "",
            "type": "string"
          },
          "required_supervision": {
            "description": "",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "Agentic_RL_filter_methods",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "partition": {
            "description": "",
            "type": "string"
          },
          "task_id": {
            "description": "",
            "type": "string"
          }
        },
        "required": [
          "task_id",
          "partition"
        ],
        "type": "object"
      },
      "name": "Agentic_RL_get_task",
      "outputSchema": null
    },
    {
      "description": "List exact filter values for agent RL credit granularity, supervision, value critics and evaluation settings. Each value reports its source-supported method count.",
      "inputSchema": {
        "properties": {},
        "type": "object"
      },
      "name": "Agentic_RL_list_method_facets",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {},
        "type": "object"
      },
      "name": "Agentic_RL_list_sources",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "limit": {
            "default": 5,
            "description": "",
            "type": "integer"
          },
          "query": {
            "description": "",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "Agentic_RL_search_evidence",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "limit": {
            "default": 10,
            "description": "",
            "type": "integer"
          },
          "offset": {
            "description": "",
            "type": "integer"
          },
          "partition": {
            "default": "all",
            "description": "",
            "type": "string"
          },
          "query": {
            "description": "",
            "type": "string"
          },
          "split": {
            "default": "all",
            "description": "",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "Agentic_RL_search_tasks",
      "outputSchema": null
    }
  ]
}

Verify it yourself

curl -s https://api.teppi.xyz/v1/evidence/sha256:d5f354198ba11c06d7fa19e5f858498ad3f6353e703ef2bbc41b39c9119f268f | sha256sum