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NocturnusAI

NocturnusAI

by Auctalis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Hybrid

merge_scope

Merge facts from a source scope into a target scope (default global) to commit hypothetical reasoning into the main knowledge base. Choose conflict resolution strategy: SOURCE_WINS, TARGET_WINS, KEEP_BOTH, or REJECT.

Instructions

Merge facts from one scope into another (default: global). Use to commit hypothetical reasoning back into the main knowledge base. Strategy controls conflict handling: SOURCE_WINS overwrites, TARGET_WINS keeps existing, KEEP_BOTH retains both, REJECT aborts on conflict. Side effects: mutates the target scope; may overwrite existing facts depending on strategy (potentially destructive under SOURCE_WINS). Auth: requires X-Tenant-ID header; FACT_WRITE permission when auth is enabled. Rate-limited per principal. Errors: VALIDATION_ERROR on unknown strategy; CONFLICT_ERROR when strategy=REJECT and conflicts are found.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sourceScope": "<sourceScope>"
    },
    "name": "merge_scope"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceScopeYesScope to merge facts from
targetScopeNoDestination scope. Omit or pass null for the global partition.
strategyNoConflict resolution: SOURCE_WINS (default) | TARGET_WINS | KEEP_BOTH | REJECT

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.12

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses side effects (mutation, potential overwrite), authentication requirements (X-Tenant-ID, FACT_WRITE permission), rate limiting, and error types (VALIDATION_ERROR, CONFLICT_ERROR). This is comprehensive, especially with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Every sentence is informative: purpose, usage, strategy explanation, side effects, auth, errors. No redundancy, well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all aspects: purpose, parameters (with additional context), behavior, auth, errors, rate limits. No output schema, but description is sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While schema covers parameter descriptions, the description adds value by explaining the default strategy, when to omit targetScope (global partition), and the effect of each strategy beyond enum labels.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action ('merge facts from one scope into another') and the use case ('commit hypothetical reasoning back into the main knowledge base'), distinguishing it from sibling tools like fork_scope or delete_scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('to commit hypothetical reasoning...'), but does not mention when not to use or provide alternatives. Still, the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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