Classify research tasks into seven primitive categories for model routing.
npx skills add https://github.com/Biajin-PKU/research-harness --skill task-taxonomy
Please help me install this Agent Skill. Skill: task-taxonomy Source: https://github.com/Biajin-PKU/research-harness/tree/main/codex-skills/task-taxonomy Command: npx skills add https://github.com/Biajin-PKU/research-harness --skill task-taxonomy
The Task Taxonomy skill helps researchers and AI agents decide which model path and primitives to apply for a given research task, enabling efficient routing and consistent results.
Provide a research task description and have the system classify it into a primitive category with routing guidance.
High-intent search queries and answers about installing and using this skill.
The seven primitive categories used for task classification are Retrieval, Comprehension, Extraction, Analysis, Synthesis, Generation, and Verification, each mapping to specific research actions and routing paths.
Routing AI agents for literature reviews and experiment planning uses a task taxonomy to map these activities to defined primitives, ensuring predictable model selection and consistent tool sequencing.
Yes, task taxonomy implements MCP-based routing rules to serve as a reference for routing policies in MCP servers, enabling predictable behavior and auditability for model selection.
Yes, you can use this classification system for proposal drafting and evidence synthesis, as it applies these research tasks to decide appropriate primitives and routing paths for consistent results.
A limitation of using a seven-category taxonomy for research task routing is that complex, multi-disciplinary queries may overlap categories, requiring manual disambiguation to ensure accurate model and primitive selection.
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