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msaad00

agent-bom

by msaad00
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Python

Cost Forecast

cost_forecast
Read-onlyIdempotent

Project LLM spend burn rate and budget runway from recent cost records. Extrapolates to budget to return days of runway and exhaustion date.

Instructions

Project LLM spend burn rate and budget runway for the active tenant.

    Derives a recent burn rate from persisted cost records and extrapolates
    to the configured budget, returning projected period spend, days of
    runway, and an exhaustion date. Reference only: a forecast never blocks a
    call and returns a clear status with null projections on sparse history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentNoOptional agent name to scope the forecast to a single agent.
tenant_idNoTenant scope to forecast. Defaults to the control-plane default tenant.default

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.4/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), the description adds that the forecast never blocks and returns null on sparse history, providing valuable behavioral context.

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 concise (two paragraphs, ~60 words) and front-loaded with the main purpose, though it could be slightly more structured.

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 the output schema covers return values, the description sufficiently explains the forecasting method, behavior on sparse history, and that it is reference-only, making it complete for this tool's complexity.

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 description coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the schema, which already documents the optional agent and tenant_id parameters.

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 clearly states the tool projects LLM spend burn rate and budget runway for the active tenant, using specific verbs and resources that distinguish it from siblings like cost_report or cost_allocation.

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?

The description provides context on usage ('Reference only', 'never blocks a call') and mentions behavior on sparse history, but does not explicitly name alternative tools or specify when not to use it.

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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