APromptAura

#tool-use

Top prompts tagged tool-use.

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p/agentsAauraNovice4 days agohas example⁂auto-checked

Disambiguate overlapping tools so an agent picks the right one consistently

I have multiple tools that overlap in what they can technically accomplish: overlapping_tools_list. The agent keeps picking the wrong one for a given situation. Help me write disambiguation guidance: 1. For each pair of overlapping tools, state the precise deciding factor (not 'use judgment') that determines which one is correct for a given request: data freshness needs, cost difference, side effects vs read-only, granularity of result. 2. Give a decision table or flowchart in text form the agent can apply mechanically: given attributes of the incoming request, which tool to pick. 3. Identify requests that are genuinely ambiguous even with the deciding factors (both tools would serve about equally well) and state what the agent should do then: pick the cheaper/faster one by default, or ask, your call given the stakes described. 4. Give 3 example requests, one for each tool and one genuinely ambiguous one, with the correct tool choice and one-sentence justification for each. Tools and what they do: overlapping_tools_list Observed mis-selections: observed_mistakes
ClaudeGPT#tool-use#disambiguation#agent-design
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p/agentsAauraNovice4 days agohas example⁂auto-checked

Write a tool description that stops an LLM from misusing the function

I have a function I want to expose to an LLM agent as a tool. Write the tool description (name, parameter docs, and usage notes) that would actually be passed to the model for function-calling. Given the function signature and behavior below, the description must: 1. State precisely what the function does and does NOT do, especially if its name could be misread (e.g. a function called `search` that only searches titles, not full text, must say so). 2. For each parameter, state its exact expected format/type and what happens on invalid input (error vs silent default), so the model doesn't guess. 3. Include one example call with realistic arguments and the shape of the return value, so the model can parse the result correctly without a separate lookup. 4. Add explicit 'do not call this when...' guidance for the situations this tool is commonly misapplied to, based on how a model might plausibly misread its purpose from the name alone. 5. Keep it concise, this goes into every request's context, don't pad it with obvious statements. Function signature and behavior: function_details Common misuse you've observed or anticipate: misuse_notes
ClaudeGPT#tool-use#function-calling#prompt-engineering
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p/agentsAauraNovice4 days agohas example⁂auto-checked

ReAct-style tool-use scaffold with explicit stop conditions

Design a ReAct-style (reason, act, observe) prompt scaffold for an agent that has access to these tools: tool_list_with_descriptions. The scaffold must: 1. Force an explicit reasoning step before every tool call: what question this call answers and why it's needed now, not just 'call tool X'. 2. Include a hard cap on tool calls per task (max_calls) and require the agent to state, once it's used 70% of its budget, whether it can still complete the task or should report partial progress instead of burning the rest of the budget on a long shot. 3. Define what counts as 'done': the agent must produce a final answer that cites which tool observations it's based on, not a final answer that ignores the tool outputs it gathered. 4. Define the failure behavior when a tool call errors: retry once with a modified input if the error suggests a fixable input problem, otherwise stop and report the error rather than looping. 5. Prevent the agent from calling a tool with the same input twice in a row (a common failure mode of building looping agents). Output the scaffold as the actual prompt text I'd use, not a description of it.
ClaudeGPT#tool-use#react#agent-scaffold
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