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Hive Coordinator

mcp_m7_hive_coordinator

Orchestrate multiagent collaboration for complex tasks by forming expert teams, decomposing work, and validating results.

Instructions

Orchestrate multiagent collaboration for complex tasks using M7 Hive system.

v3.8.0 Features:

  • DYNAMIC MODE (default): AI creates optimal expert team for each task

  • PLANNED MODE (new): CNP auction-based coordination with task decomposition

  • MODEL SELECTION: Best model chosen per agent based on LiveBench benchmarks

  • SELF-LEARNING: System improves over time based on results

  • GATEKEEPERS: Style, Architecture, Security validation

Use mode="dynamic" for quick expert analysis (default). Use mode="planned" for complex tasks requiring decomposition and validation. Use mode="fixed" for legacy behavior with predefined agents.

Input Schema

NameRequiredDescriptionDefault
modeNoExecution mode: "dynamic" (AI team, default), "planned" (CNP auction-based, v3.8.0+), or "fixed" (legacy)dynamic
taskYesTask description for multiagent analysis
agentsNoWhich agents to involve (only used in "fixed" mode, auto-selected if not specified)
priorityNoOptimization priorityquality
max_roundsNoMaximum debate rounds before fallback
debate_modeNoEnable agent debates for consensus
plannerOptionsNoOptions for planned mode (v3.8.0+)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.18.1

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose meaningful behavior: mode-dependent coordination strategies, model selection via LiveBench, self-learning across invocations, gatekeeper validation, and debate rounds with a fallback (max_rounds). What it omits is equally important for an orchestration tool: latency/cost profile of a multi-agent run, whether it persists state or emits side effects, and what the result looks like. Adequate but with clear gaps.

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

Conciseness3/5

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

The purpose statement is front-loaded, which is good, but the 'v3.8.0 Features' bullet list is promotional filler ('SELF-LEARNING: System improves over time') and the three 'Use mode=...' lines largely restate the mode enum descriptions. Roughly half the text is redundant with structured fields.

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

Completeness3/5

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

For a 7-parameter tool with a nested plannerOptions object, no output schema, and no annotations, the description should carry more weight. It explains the modes well but leaves the caller uninformed about return shape, run duration expectation, state persistence, and interaction between priority/debate_mode/max_rounds.

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

Parameters3/5

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

Schema description coverage is 100% and every parameter including the nested plannerOptions carries its own description, so baseline is 3. The description adds mode semantics that align with the enum descriptions but adds nothing beyond the schema for priority, max_rounds, debate_mode, or the agents list interaction with modes.

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

Purpose4/5

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

States a specific verb and resource: 'Orchestrate multiagent collaboration for complex tasks using M7 Hive system.' The agent can tell this is the top-level orchestration entry point. However, it never distinguishes itself from plausible siblings such as mcp_m7_analyze_task, mcp_m7_mesh, or mcp_m7_dcce, which a 4 on this dimension would require.

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?

Gives explicit selection criteria between the tool's own modes: dynamic for 'quick expert analysis', planned for 'complex tasks requiring decomposition and validation', fixed for legacy. This is genuinely actionable. It stops short of 5 because it offers no guidance on when to use this tool instead of the many sibling tools, nor any prerequisites or exclusions.

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