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ShotPulled

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OverviewDiscussionsAdmin

Suggest the next step

suggest_next_step
Read-onlyIdempotent

Retrieve the single next experiment step from the reasoning engine.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "bean_id": "<bean_id>"
    },
    "name": "suggest_next_step"
  }
}

Input Schema

NameRequiredDescriptionDefault
bean_idYes

Output Schema

NameRequiredDescriptionDefault
categoryYes
warningsYes
next_stepYes
warning_codesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / warning_codes
      Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / required
      Previous value: -[
-  "next_step",
-  "category",
-  "warnings"
-]New value: +[
+  "next_step",
+  "category",
+  "warnings",
+  "warning_codes"
+]
  2. First observed

TDQS

B3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds only that exactly one step is returned; it says nothing about what happens when no step is available, whether state must exist first, or how fresh the suggestion is.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. It is efficient, though the terseness contributes to the missing context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be described. However, for a tool whose whole purpose is ambiguity-prone ('next step'), the bean_id semantics and the precondition for getting a suggestion are missing, leaving the definition only barely sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

One required parameter with 0% schema description coverage, and the description never explains what bean_id identifies or that it comes from list_beans/register_bean. The description does nothing to compensate for the undocumented parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb ('Retrieve') and resource ('the single next experiment step from the reasoning engine'), which is enough to distinguish it from the CRUD/registration siblings. What an 'experiment step' actually is in this coffee-tooling domain is left implicit, so it stops short of full clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to call this versus diagnose_shot, get_dial_state, get_rule or the other read-oriented siblings. An agent must guess that this is the recommendation/advice endpoint rather than a lookup.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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