A
license-
qualityB
maintenanceProvides reasoning budget estimates for AI tasks, making effort and time trade-offs visible through a compact control interface.
Last updated
MIT
Budgetary: estimate token spend
Server Details
Pre-flight, probabilistic token-spend estimate (range, scenario, confidence) for a coding task.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- thriftell/budgetary-clients
- GitHub Stars
- 0
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Tool Definition Quality
A4.2/5.0
Tool DescriptionsA
Average 3.9/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With a single tool, there is no possibility of confusion or ambiguity. The tool's purpose is clear and distinct simply because it is the only one.
Naming Consistency5/5
With only one tool, there is no pattern to break or inconsistency. The name 'estimate' is a single verb that directly describes its function, which is as consistent as possible.
Tool Count4/5
One tool is minimal, but for a narrow domain like token spend estimation, it is arguably appropriate. The server does exactly what it advertises without unnecessary bloat.
Completeness5/5
The tool fully covers the server's stated purpose of providing probabilistic token spend estimates. No additional operations are needed since actual usage reporting is explicitly excluded from scope.
Available Tools
1 toolestimateAInspect
Return a pre-flight, probabilistic token-spend estimate (range + scenario + confidence) for a coding task before you run it. Estimates only — it never reports your actual token usage.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Optional model identifier, e.g. claude-opus-4-7. | |
| query | Yes | The coding task or prompt you're about to run. |
Tool Definition Quality
A3.9/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the estimate is 'probabilistic' and includes 'range + scenario + confidence', but does not detail any side effects, prerequisites, or limitations (e.g., accuracy based on model or query complexity). The behavioral description is adequate but not comprehensive.
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?
The description consists of two concise sentences with no fluff. The key verb and scope are front-loaded. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not explain the return format (range, scenario, confidence) in detail. It also lacks information on error cases or when the estimate might be unavailable. For a tool returning a complex estimate, more context is needed.
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 coverage is 100%, so both parameters are described in the schema. The description reinforces that the task is a 'coding task' and that it's a pre-flight estimate, but adds little beyond the schema's own descriptions. With full schema coverage, the baseline is 3, and the description only marginally adds value.
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 returns a 'pre-flight, probabilistic token-spend estimate' for a coding task. It specifies the verb 'return' and the resource 'token-spend estimate', and distinguishes it from actual token usage by saying 'it never reports your actual token usage'. This makes the purpose unambiguous.
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 explicitly indicates when to use the tool: 'before you run it' a coding task. It also clarifies what the tool does not do: 'Estimates only — it never reports your actual token usage.' While no siblings are provided, the context is clear. A small deduction for not mentioning conditions where estimation might be inappropriate or alternatives.
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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