valta-mcp

valta_set_policy

Set spending limits for AI agents by creating policies that define daily and per-transaction caps on USDC spend.

Instructions

Create a new spending policy — a named limit configuration (daily cap, per-transaction cap) that can be applied to an agent's spend.

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": {
      "name": "<name>"
    },
    "name": "valta_set_policy"
  }
}

Input Schema

Name	Required	Description
`name`	Yes	A name for this policy
`agentId`	No	Optional — the agent this policy applies to
`maxSpendPerDay`	No	Maximum USDC spend per day
`maxSpendPerTransaction`	No	Maximum USDC per single transaction

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 14, 2026

TDQS

B3.1/5.0

Behavior2/5

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

With no annotations, the description carries full burden but does not disclose important behavioral traits: whether creation is idempotent, what happens on duplicate name, required permissions, side effects, or return value. The description only says 'create', omitting safety and confirmation details.

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

Conciseness5/5

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

A single, well-structured sentence that front-loads the core purpose. Every word contributes meaning; no redundancy or filler.

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?

The description covers the essential purpose but lacks context around post-creation behavior (e.g., returns policy object or ID), error conditions, prerequisites (e.g., agent existence for optional agentId), and interaction with sibling tools like 'valta_apply_policy' if it exists. It is adequate but not comprehensive.

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

Parameters3/5

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

Schema descriptions cover all 4 parameters (100% coverage), so baseline is 3. The description adds value by explaining that the policy is a 'named limit configuration' and that 'daily cap, per-transaction cap' map to the spend parameters, but does not add critical new info beyond what the schema provides.

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?

The description clearly states the tool creates a new spending policy with daily and per-transaction caps, and mentions it applies to an agent's spend. It distinguishes from siblings like 'valta_list_policies' and 'valta_request_spend' implicitly, but does not explicitly differentiate.

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?

No guidance on when to use this tool versus alternatives. For example, it does not mention checking existing policies with 'valta_list_policies' before creating, or prerequisites like having an agent if 'agentId' is provided.

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

Deploy Server