sadd

Plugin sadd from marketplace context-engineering-kit in NeoLabHQ/context-engineering-kit. Commands read from the repo's manifest — 1 month ago.

Skills (10)

• do-and-judge

  Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop

• do-competitively

  Execute tasks through competitive multi-agent generation, meta-judge evaluation specification, multi-judge evaluation, and evidence-based synthesis

• do-in-parallel

  Run independent tasks concurrently across multiple files or targets using parallel sub-agents, with per-task model selection and LLM-as-a-judge verification. Use when tasks do not depend on each other and can run side by side.

• do-in-steps

  Execute one complex task as ordered, dependent steps run sequentially, passing context from each step to the next, with per-step LLM-as-a-judge verification. Use when later steps depend on the results of earlier ones.

• judge-with-debate

  Evaluate solutions through multi-round debate between independent judges until consensus

• judge

  Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation

• launch-sub-agent

  Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification

• multi-agent-patterns

  Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

• subagent-driven-development

  Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates

• tree-of-thoughts

  Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation

Subagents (2)

• judge

  Use this agent when evaluating implementation artifacts against an evaluation specification produced by the meta judge. Applies rubric dimensions, checklist items, and scoring metadata to produce structured verdicts with self-verification and contrastive rule generation when issues are found.

• meta-judge

  Use this agent when generating evaluation rubrics, checklists, criteria, metrics, and weights for a user prompt BEFORE implementation begins. Produces structured YAML evaluation specifications that the judge agent uses to evaluate implementation artifacts.

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