EUCompliance Tools - Invoice Guard & Agent Evidence

Choose and prepare AgentLLM tier (free)

prepare_agentllm

Read-onlyIdempotent

FREE deterministic validation and exact-price routing for all AgentLLM tiers. Choose Micro for classification, extraction and short summaries, Basic for general chat, or Plus for stronger drafting, analysis and longer summaries. It validates the exact arguments without calling a model or charging; continue only when ready_to_buy is true.

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": {
      "prompt": "<prompt>"
    },
    "name": "prepare_agentllm"
  }
}

Input Schema

Name	Required	Default
`tier`	No	micro
`prompt`	Yes
`system`	No
`max_tokens`	No

Output Schema

Name	Required	Description
`ok`	No
`tier`	No
`tool`	No
`error`	No
`model`	No
`price`	No	No payment is required for this tool.
`limits`	No
`charged`	No
`message`	No
`missing`	No
`payment`	No
`settled`	No	When present on an error, false means no settlement occurred.
`unknown`	No
`accepted`	No
`contract`	No
`paid_tool`	No
`retryable`	No
`error_code`	No
`input_bytes`	No
`status_code`	No
`did_you_mean`	No
`ready_to_buy`	No
`message_count`	No
`missing_checks`	No
`paid_arguments`	No
`upstream_called`	No
`fixed_price_usdc`	No
`partial_evidence`	No
`accepted_max_output_tokens`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 6, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses deterministic behavior, exact-price routing, absence of model invocation or charging, and a ready_to_buy continuation gate. This materially changes how an agent would use the tool and adds information the annotations do not convey.

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?

Three sentences deliver the value proposition, tier guidance, and critical behavioral caveat with no filler. Key constraints are front-loaded so an agent can decide without reading deeply.

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

Completeness4/5

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

The output schema exists, so not describing return values is acceptable, and the description covers cost, determinism, tier choice, and the ready_to_buy gate. It could be more explicit about the subsequent step (calling agentllm_* after ready_to_buy), but that is inferable from context.

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?

Description explains the tier enum well (Micro for classification/extraction/short summaries, Basic for general chat, Plus for drafting/analysis/longer summaries). With 0% schema coverage, however, it leaves prompt, system, and max_tokens to be inferred from names and defaults, so it only partially compensates.

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?

The first sentence names a specific action (validates arguments, routes exact price) and resource (all AgentLLM tiers), and the tier list maps use cases. This clearly differentiates it from actual model-calling siblings like agentllm_basic and from prepare_agentllm_micro.

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?

It states this is a free pre-flight that doesn't call a model and that the caller should continue only when ready_to_buy is true, making the intended use obvious. It does not explicitly name sibling tools as the 'when not' alternative, but the no-call/no-charge framing implies the boundary.

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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