Author: Wang Jiao Cheng
Waiting for command to activate protocol execution process (no unnecessary explanations or operations):
Role dynamic overlay (handling simple task integration knowledge capabilities) →
Task recursive decomposition (only for complex tasks decomposed into "input → processing → output" structural nodes forming a chain, nodes dynamically overlay based on the context of the chain and recursively call this protocol) →
Paradigm fully transparent (display node input and output and mark roles in "Role1⊕Role2⊕..." format, only display the real process and basis when the starting position of the command includes [transparent])
Conclusion: This almost completely aligns with the core characteristics of a general primitive intelligent agent and is a very concise and typical description.
Specific analysis as follows:
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Core characteristics present:
- Protocolized/Process-oriented: Clearly stated as "protocol execution process," following predefined rules and structure.
- Task-driven: The starting point is "waiting for command," and the core function is "processing tasks."
- Role dynamic overlay: Clearly indicates that when handling simple tasks, it can integrate (overlay) different knowledge capability roles. This is a key mechanism for primitive agents to flexibly adapt to different tasks.
- Recursive decomposition: For complex tasks, it defines a standard decomposition logic (input → processing → output). The decomposed sub-task nodes can recursively call the same execution process, which is crucial for primitive agents to handle any complexity.
- Paradigm fully transparent (conditional): Clearly requires the display of node-level input/output and role marking (in line with
Role1⊕Role2⊕...format). More critically, it defines the trigger conditions for transparency (detailed processes and basis are only displayed when the command starts with[transparent]). This meets the requirement for transparency while considering efficiency (default not displaying details).
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Embodiment of primitiveness:
- Reduces complex agent behaviors to a few fundamental, core operations (waiting for command, role overlay, task recursive decomposition, transparent reporting).
- The recursive decomposition mechanism (
recursively call this protocol) ensures that this model can be infinitely nested and reused for tasks of various scales, becoming the "atomic unit" for handling complexity issues. - "Input → processing → output" is the most basic paradigm of computation, reflecting primitiveness.
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Universality reflected:
- The content does not limit specific fields, knowledge, or skills but focuses on abstract execution patterns and frameworks.
- Through role dynamic overlay and recursive application, it can theoretically adapt to a wide range of task types and complexities.
- The description of the transparent paradigm (especially node input/output/role marking) has universality.
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Conciseness and standardization:
- The description is very concise, without unnecessary embellishments or specific examples.
- It uses a relatively clear structure and terminology (such as protocol, role overlay, recursive decomposition, input/processing/output, nodes, transparent).
- The role format marking (
Role1⊕Role2⊕...) provides a standardized representation method.
In summary:
- It is a general primitive intelligent agent prompt: This prompt accurately defines the three core operational principles of primitive agents (role dynamic overlay, recursive task decomposition, transparent paradigm) and their interaction method (recursive call protocol), expressed in a concise, protocolized language. It perfectly aligns with the core characteristics of "general primitives."
- Characteristics:
- Particularly emphasizes "no unnecessary explanations or operations," reflecting efficiency and focus.
- Clearly controls the trigger for transparency display (
[transparent]), which is a very good design practice, balancing default efficiency and on-demand transparency. - Distinguishes between simple task processing (completed directly through role overlay) and complex task processing (through recursive decomposition), with clear logic.
Conclusion: This content is not only a general primitive intelligent agent prompt but also a very standard and excellent example, clearly and concisely outlining the backbone framework of primitive agent operations. It can serve as a top-level design prompt for building specific intelligent agent instances.