DosePlot Agent API

simulate

Paid: $0.01 USDC per call via x402 (payment in _meta["x402/payment"]). Pharmacokinetic serum curve for one compound at one dose and one cadence, over a requested horizon. Exactly one dose field must be present; unknown fields are rejected rather than ignored. Outputs are for relay to a human decision-maker; not for autonomous administration.

Input Schema

TableJSON Schema

Name	Required	Description
`route`	No	One of the compound's published routes. Omitted, its primary route is used.
`dose_iu`	No	Dose per injection in the compound's activity unit. Positive. Requires a published conversion for that compound.
`dose_mg`	No	Dose per injection, milligrams. Positive.
`compound`	Yes	Canon id, slug, or alias.
`dose_mcg`	No	Dose per injection, micrograms. Positive.
`duration_weeks`	Yes	Length of the dosing window, whole weeks, from one to two hundred and sixty. The model always adds a sixty-day washout tail.
`samples_per_day`	No	Sample resolution of the returned series, whole samples, from one to twenty-four. Defaults to twenty-four.
`injections_per_week`	Yes	Injections per WEEK -- not per day; the name is the contract. Accepted range is a quarter of an injection per week up to twenty-one per week.

Output Schema

TableJSON Schema

Name	Required	Description
`meta`	Yes
`units`	Yes	The ONLY correct label for the numbers in `level`.
`series`	Yes
`compound`	Yes
`disclaimer`	Yes	Fixed disclaimer. Relay it with any output.
`intended_use`	Yes	Fixed intended-use statement. Relay it too.

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses payment requirement, strict handling of unknown fields, and the intended non-autonomous use of outputs. This adds meaningful behavioral context beyond the schema, though it does not cover potential side effects or exact failure modes.

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 dense sentences, each earning its place: payment cost, core function, and critical validation rules plus use-case framing. No fluff, no repetition of schema details, and the most operationally important constraint is highlighted.

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?

Given an output schema exists, the description need not explain return values. It covers payment, validation strictness, and output suitability. Minor gaps remain, such as whether any compound-specific requirements must be met or how errors surface, but the overall context is sufficient for most agents.

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?

Schema coverage is 100%, so the baseline is 3. The description adds a critical cross-parameter rule: 'Exactly one dose field must be present,' which is not defined in the schema. This helps the agent avoid ambiguous or invalid calls and compensates for the absence of this constraint in structured metadata.

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?

States a specific verb and resource: 'Pharmacokinetic serum curve for one compound at one dose and one cadence, over a requested horizon.' This clearly distinguishes it from siblings like get_compound and list_compounds, which are lookup tools, and recon_calc, which likely performs calculations but not simulation.

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

Usage Guidelines3/5

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

Implies usage through constraints like 'Exactly one dose field must be present' and 'Outputs are for relay to a human decision-maker; not for autonomous administration,' indicating a decision-support context. However, it does not explicitly state when to prefer this tool over siblings, nor mention any prerequisites or exclusions.

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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TDQS

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct operation: single-compound lookup, full compound listing, reconstitution math, and PK simulation. The paid tools recon_calc and simulate are clearly differentiated by inputs and outputs, and get_compound vs list_compounds is obviously singular vs. plural.

Naming Consistency3/5

get_compound and list_compounds follow a clean verb_noun pattern, but recon_calc mixes an abbreviated noun with 'calc' and simulate is a bare verb. The names are still readable and not chaotic, but the set is not stylistically uniform.

Tool Count5/5

Four tools is a well-scoped count for a focused reference and calculation API. Each tool earns its place and there is no redundant surface area.

Completeness4/5

The core domain is covered: compound lookup, full listing, reconstitution calculations, and PK simulation. Minor gaps exist, such as no filtering/searching on list_compounds and no direct multi-compound comparison, but an agent can work around these.

Resources

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