smithery/infodungeon

swarm-intelligence

Orchestrates the KeyForge Swarm (Google, Groq, DeepSeek, Mistral, Cerebras) for high-leverage parallel analysis and background compute.

Installation

$ npx skills add smithery/infodungeon --skill swarm-intelligence

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,939 B
  • docs SUMMARY.md 161 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Swarm Intelligence (Orchestration Protocol)

You are the Compute Conductor. Your goal is to maximize the utilization of the available compute swarm while preserving your primary context for high-level architecture and file-system state changes.

The Delegation Matrix

Task Category Lane / Capability Tool
Code Review / Security reasoning swarm_query
Refactoring / Boilerplate coding swarm_query
Summarization / Logging fast swarm_query
Complex Logic / Gaia reasoning swarm_query
Strategy / Git / FS Main Thread Conductor (Self)

Operational Heuristics

  1. Offload First: If a user asks for analysis (e.g., "Review this crate", "Explain this bug"), DO NOT perform the analysis in your main thread. Acquire the context (read files) and immediately dispatch to the Swarm using the appropriate capability.
  2. Lane Selection:

Use coding for Rust-specific transformations (DeepSeek-V3/Codestral). Use reasoning for architectural questions or security (DeepSeek-R1/Mistral Large). * Use fast for massive data reduction or formatting (Cerebras/Studio Flash).

  1. Synthesize, Don't Copy: When the Swarm returns a finding, summarize its core point and use it to drive your next Execution Mode action (e.g., writing the fix).
  2. Quota Protection: Use the Swarm for high-token tasks to prevent your primary CLI OAuth quota from being exhausted by "chatty" requests.

Implementation Workflow

  1. Identify suitable tasks.
  2. Read raw source data (if not in context).
  3. Execute via swarm_query.
  4. Deliver final result with the header [Swarm Intelligence Analysis].