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Agent Decision & Evidence Tools (MCP + x402)

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNomicro
promptYes
systemNo
max_tokensNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
tierNo
toolNo
errorNo
modelNo
priceNoNo payment is required for this tool.
limitsNo
chargedNo
messageNo
missingNo
paymentNo
settledNoWhen present on an error, false means no settlement occurred.
unknownNo
acceptedNo
contractNo
paid_toolNo
retryableNo
error_codeNo
input_bytesNo
status_codeNo
did_you_meanNo
ready_to_buyNo
message_countNo
missing_checksNo
paid_argumentsNo
upstream_calledNo
fixed_price_usdcNo
partial_evidenceNo
accepted_max_output_tokensNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

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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