Server definition

Hash: sha256:4ac692a859cf67624b30bcded8fb3d0f48240a26fdad56cfa9e4f97abe471e46
What it is: What a remote MCP server returned when asked what it offers: 12 tools

The blob, as servednamed by its sha256

{
  "instructions": null,
  "tools": [
    {
      "description": "Given a natural-language task description (e.g., 'I'm building a tool-using agent that runs shell commands'), return the most relevant patterns grouped by suite. Use this as a starting point for any cross-cutting design question; then follow up with get_requirement on specific pattern_ids. Defaults to verbosity='compact' (cheap triage); pass 'full' to inline snippets and confidence flags.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 8,
            "maximum": 25,
            "minimum": 1,
            "type": "integer"
          },
          "task": {
            "maxLength": 500,
            "minLength": 5,
            "type": "string"
          },
          "verbosity": {
            "default": "compact",
            "enum": [
              "compact",
              "full"
            ],
            "type": "string"
          }
        },
        "required": [
          "task"
        ],
        "type": "object"
      },
      "name": "find_patterns_for_task",
      "outputSchema": null
    },
    {
      "description": "Return outgoing adjacencies for a pattern. `explicit_cross_references` are author-asserted (each pattern's `cross_references` YAML field). `inferred_adjacent` (when include_inferred=true) currently returns *same-suite siblings only* — it does not do semantic similarity. Treat inferred entries as 'neighbours worth scanning,' not as endorsed dependencies.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "id": {
            "maxLength": 500,
            "type": "string"
          },
          "include_inferred": {
            "default": true,
            "type": "boolean"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_cross_references",
      "outputSchema": null
    },
    {
      "description": "Retrieve a single operational heuristic by id (e.g., 'OH::geoffrey-pattern'). Returns the full entry: principle, framework mapping, evidence sources from production deployment, design patterns, anti-patterns, and discovery narrative.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "id": {
            "maxLength": 500,
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_operational_heuristic",
      "outputSchema": null
    },
    {
      "description": "Retrieve one subgoal (framework normative content + Pattern layer guidance) by pattern_id (e.g., 'D3::idx2::sandboxing') or display_id (e.g., 'D3.2'). display_id may resolve to multiple subgoals — underlined variants share display_ids.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "id": {
            "maxLength": 500,
            "type": "string"
          },
          "include_pattern": {
            "default": true,
            "type": "boolean"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_requirement",
      "outputSchema": null
    },
    {
      "description": "Return patterns that reference the given pattern_id in their cross_references. Complement to get_cross_references (outgoing); this shows incoming. Use to find all consumers of a given pattern.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "id": {
            "maxLength": 500,
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_reverse_references",
      "outputSchema": null
    },
    {
      "description": "List operational heuristics distilled from production agentic AI deployment (Claude Code, Rewind). These are cross-cutting safety principles discovered through building and operating AI agents, mapped to framework suites. Optional filters: suite_id (heuristics relevant to a specific suite), query (keyword search across titles and principles). Separate from the normative pattern layer — different category of knowledge.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "query": {
            "description": "Keyword search across titles, principles, narratives",
            "maxLength": 500,
            "type": "string"
          },
          "suite_id": {
            "description": "Filter by framework suite (e.g., 'D3', 'I2')",
            "maxLength": 500,
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_operational_heuristics",
      "outputSchema": null
    },
    {
      "description": "List subgoals matching filters (suite_id, suite_type, content_type, min_confidence, missing_pattern_only). Results capped by limit (default 50, max 100).",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "content_type": {
            "enum": [
              "code-applicable",
              "governance",
              "process",
              "ecosystem"
            ],
            "type": "string"
          },
          "include_pattern": {
            "default": false,
            "type": "boolean"
          },
          "limit": {
            "default": 50,
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "min_confidence": {
            "enum": [
              "low",
              "medium",
              "high"
            ],
            "type": "string"
          },
          "missing_pattern_only": {
            "type": "boolean"
          },
          "suite_id": {
            "maxLength": 500,
            "type": "string"
          },
          "suite_type": {
            "enum": [
              "driver",
              "inhibitor"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_requirements",
      "outputSchema": null
    },
    {
      "description": "List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "list_suites",
      "outputSchema": null
    },
    {
      "description": "Return patterns that have not been human-reviewed yet (no reviewed_by). Sorted low-confidence first, then needs_human_review flagged, then alpha. Use during Phase 3 review to pick the next pattern to examine.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "maximum": 250,
            "minimum": 1,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "list_unreviewed",
      "outputSchema": null
    },
    {
      "description": "Resolve a loose reference (partial id, display_id, slug fragment, or title keyword) to canonical pattern_id(s). Call this when you have a rough reference and need the exact id before calling get_requirement. Always returns candidates — never 'not found'.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 5,
            "maximum": 20,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "maxLength": 500,
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "resolve_id",
      "outputSchema": null
    },
    {
      "description": "Coverage stats: total patterns, reviewed %, per-suite and per-confidence breakdown. Surfaces load-time validation issue count.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "review_stats",
      "outputSchema": null
    },
    {
      "description": "Field-weighted keyword search across the framework. Terms match at word starts on lowercased text and are IDF-weighted, so rare terms outrank ubiquitous ones; field weights: title 10x, summary 4x, SFR text 3x (all of a subgoal's SFRs scored as one field), description 2x, pattern body 1x. `matched_in` reports the highest-weighted field that matched. No semantic / embedding search — known limitation, see /mcp.html. Use verbosity='compact' to drop snippets and confidence flags (~70% smaller payload) when triaging.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 10,
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "maxLength": 500,
            "minLength": 2,
            "type": "string"
          },
          "verbosity": {
            "default": "full",
            "enum": [
              "compact",
              "full"
            ],
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_patterns",
      "outputSchema": null
    }
  ]
}

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