Project Tango

Reset Demo State

reset_demo_state

Discard every simulated order and inventory change to restore the original seed catalog. Use it to undo exploratory ordering before reporting results from the real dataset.

Instructions

Write-action tool: discards every simulated order and inventory change made during this or any earlier session, restoring the original seed catalog. Use it to undo exploratory ordering before reporting results, so the numbers you hand back reflect the real dataset rather than your own test orders.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "reset_demo_state"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`reset`	Yes
`orders`	Yes
`products`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.2.0Nov 10, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it explicitly labels this a write-action tool and discloses the exceptionally wide destructive scope (all simulated changes from this or any earlier session). It stops short of stating irreversibility/confirmation requirements, but the safety profile is otherwise well covered.

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?

Front-loads the 'Write-action tool' warning, then the effect, then the rationale. The final clause about reporting real numbers is slightly redundant with 'before reporting results,' but it reinforces intent rather than padding.

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

Completeness5/5

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

Output schema exists so return values need no explanation, and there are no parameters or annotations to compensate for. Scope, intent, and destructive warning are all present for a zero-arg tool.

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

Parameters4/5

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

The tool takes zero parameters, so per the baseline there is no parameter semantics to explain and no gap in the description. No misleading parameter claims are made.

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

Purpose5/5

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

Names a specific action (discards/restores) on a specific resource (simulated orders and inventory changes, seed catalog). An agent can immediately distinguish this reset tool from simulate_order_placement or find_orders in the sibling set.

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

Usage Guidelines4/5

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

Gives a clear when-to-use context: undo exploratory ordering before reporting results. It does not name an explicit alternative tool or a when-not-to-use condition, but the trigger condition is unambiguous.

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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