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RyanKramer

SummitFlow MCP

by RyanKramer

volunteer_time_value

Calculate the monetary value of volunteer hours for grant match requirements or annual reports. Use default national rates or specify custom hourly rates for skilled professionals.

Instructions

Value volunteer time for match requirements or an annual report.

Defaults to the published national rate. Skilled volunteers doing professional work (legal, accounting, medical) should be valued at the rate for that work instead, which most funders accept if you document it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursYes
volunteersNo
hourly_rateNo

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 provided, the description carries the full burden. It discloses the default behavior (published national rate) and explains the skilled-volunteer exception, which is critical behavioral context. It does not describe the return format, but the presence of an output schema likely covers that.

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 is two sentences long, front-loaded with the primary purpose, and includes only necessary behavioral guidance. Every phrase earns its place with no redundancy or filler.

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 the tool's simple nature (3 params, no nested objects, output schema present), the description covers the core purpose, default behavior, and a key edge case. It omits details like return currency or total-hours calculation, but these are either inferable or handled by the output schema.

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 0%, so the description must compensate. It adds meaning to the hourly_rate parameter by explaining the default national rate and the skilled-volunteer override, but it does not explicitly map these behaviors to parameter names. The hours and volunteers parameters are self-explanatory from their schema definitions.

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 'Value volunteer time for match requirements or an annual report,' which uses a specific verb ('value') and resource ('volunteer time') while stating the use case. This clearly distinguishes it from sibling tools like in_kind_value, which likely handles broader in-kind donations.

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 explicit contexts ('match requirements or an annual report') and a specific usage scenario for skilled volunteers (legal, accounting, medical). However, it does not mention alternatives or when not to use the tool, so it lacks explicit 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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