agentsop-module-shape-selection
byagentsope· 48 skills
ENHANCE overlay on [[dspy]] — the upfront rubric for choosing a reasoning SHAPE (Predict / ChainOfThought / ReAct / ProgramOfThought) BEFORE you write a prompt or pick an optimizer. The local dspy skill lists the modules but never surfaces the *selection criterion*: reasoning shape is chosen by task structure, not by reflexively defaulting to CoT. Activate every time a new LM-calling node/step is added to a pipeline. Do NOT activate for one-shot prompts, optimizer/teleprompter choice (that is the dspy SOP's job), or non-LM control flow. Search keywords: chain of thought vs ReAct, when to use CoT, reasoning type, ReAct vs CoT vs PoT, which dspy module, predict vs chain of thought.
How to install agentsop-module-shape-selection?
agentsope/skillalchemy/agentsop-module-shape-selection
$npx -y skills add agentsope/skillalchemy --skill agentsop-module-shape-selectionInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/agentsope/skillalchemy" --skill "agentsope/skillalchemy/agentsop-module-shape-selection"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/agentsope/skillalchemy" that are relevant to the current task. Run `npx skills add "https://github.com/agentsope/skillalchemy"` and select the relevant skills, then follow their instructions.
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