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minimax_status

Check MiniMax Token Plan remaining quota and reset countdown, pausing work automatically to prevent rate limit errors.

Instructions

Return current Token Plan status (the same numbers shown on the page).

Reads the 5h fixed-window remaining/used percent, time until reset, and weekly window. Use this before any substantial work that will call MiniMax models. If should_pause is true, the agent should sleep until the 5h window resets (see minimax_wait_for_quota).

The web console actually fires two distinct requests; we mirror both so the response matches what the user sees on screen:

  1. /v1/api/openplatform/coding_plan/remains?GroupId={gid} powers the "5h 限额 / X% 已用 / 2h56m 后重置" panel.

  2. /backend/account/token_plan_credit powers the "套餐用量" panel (total / used / remaining credits).

Auth for both uses the persisted web-session cookies (Camoufox capture). When cookies are missing or stale, the failure body is saved to <data_dir>/last_coding_plan_failure.json so the cause can be diagnosed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses that the tool fires two distinct HTTP requests, uses persisted web-session cookies for auth, and saves a failure body to a file on missing/stale cookies. It stops short of explicitly stating whether the operation is read-only, though the purpose implies it, so a 4 is appropriate.

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?

The description is organized and front-loads the purpose and usage, then provides a numbered list of the two requests. It is slightly long but each sentence adds value—the request details and auth handling are necessary for correct use. Minor redundancy exists ('same numbers shown on the page' vs 'matches what the user sees'), but overall it is efficient.

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?

Given zero parameters, an existing output schema, and moderate complexity (multiple requests, auth, failure handling), the description covers all essential context: when to use, what the tool mirrors, auth requirements, and failure handling. It even references the sibling tool for the wait action. Nothing needed for correct invocation is missing.

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, and the schema has 100% coverage (empty object). The baseline for no parameters is 4; the description correctly avoids padding and simply documents the requested behavior. No further parameter explanation is needed.

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 description opens with a specific verb ('Return') and a clear resource ('current Token Plan status'), then details the exact metrics (5h window remaining/used percent, time to reset, weekly window). It also names the two backend requests it mirrors, making it unambiguous what the tool does and grounding it in observable behavior.

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

Usage Guidelines5/5

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

It explicitly states when to use it: 'Use this before any substantial work that will call MiniMax models.' It also gives conditional behavior ('If should_pause is true...') and points to a specific alternative (minimax_wait_for_quota), providing both a when and a corresponding alternative action.

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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