[HN Gopher] Ask HN: How do you know if AI agents will choose you...
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       Ask HN: How do you know if AI agents will choose your tool?
        
       YC recently put out a video about the agent economy - the idea that
       agents are becoming autonomous economic actors, choosing tools and
       services without human input.  It got me thinking: how do you
       actually optimize for agent discovery? With humans you can do SEO,
       copywriting, word of mouth. But an agent just looks at available
       tools in context and picks one based on the description, schema,
       examples.  Has anyone experimented with this? Does better
       documentation measurably increase how often agents call your tool?
       Does the wording of your tool description matter across different
       models (ZLM vs Claude vs Gemini)?
        
       Author : dmpyatyi
       Score  : 13 points
       Date   : 2026-02-23 19:32 UTC (3 hours ago)
        
       | jackfranklyn wrote:
       | We've been exposing tools via MCP and the biggest lesson so far:
       | the tool description is basically a meta tag. It's the only thing
       | the model reads before deciding whether to call your tool.
       | 
       | Two things that surprised us: (1) being explicit about what the
       | tool doesn't do matters as much as what it does - vague
       | descriptions get hallucinated calls constantly, and (2) inline
       | examples in the description beat external documentation every
       | time. The agent won't browse to your docs page.
       | 
       | The schema side matters too - clean parameter names, sensible
       | defaults, clear required vs optional. It's basically UX design
       | for machines rather than humans. Different models do have
       | different calling patterns (Claude is more conservative, will ask
       | before guessing; others just fire and hope) so your descriptions
       | need to work for both styles.
        
         | zahlman wrote:
         | > inline examples in the description beat external
         | documentation every time. The agent won't browse to your docs
         | page.
         | 
         | That seems... surprising, and if necessary something that could
         | easily be corrected on the harness side.
         | 
         | > The schema side matters too - clean parameter names, sensible
         | defaults, clear required vs optional. It's basically UX design
         | for machines rather than humans.
         | 
         | I don't follow. Wouldn't you do all those things to design for
         | humans anyway?
        
       | JacobArthurs wrote:
       | Tool description quality matters way more than people expect. In
       | my experience with MCP servers, the biggest win is specificity
       | about when not to use the tool. Agents pick confidently when
       | there's a clear boundary, not a vague capability statement.
        
       | LetsAutomate wrote:
       | The AI agent chooses your tool based on how well your tool's
       | description matches the user's intent -- clear, specific
       | descriptions win.
        
         | sincerely wrote:
         | You'd know, huh?
        
       | snowhale wrote:
       | tool description wording does matter, at least in my testing.
       | models seem to use the description to reason about whether a tool
       | "should" apply, not just whether it can. two things that helped:
       | (1) explicit input format with an example, (2) a one-sentence
       | note about what the tool does NOT handle. the negative case helps
       | models avoid calling it on edge cases and then failing, which
       | trains them (in context) to prefer it when it's actually the
       | right fit.
        
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       (page generated 2026-02-23 23:01 UTC)