Spending categories
spending_categoriesThe 19 categories this API scores spending against. Call this first and map the person's statement onto these ids before calling simulate_cards.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
spending_categoriesThe 19 categories this API scores spending against. Call this first and map the person's statement onto these ids before calling simulate_cards.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full load; it discloses the tool's role as the id-authority that simulate_cards consumes, which is the key behavioral fact. It omits whether the 19 categories are a fixed constant and what fields each entry carries, but the workflow relationship is well communicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, nothing wasted: the first defines the resource, the second gives the sequencing instruction. The ordering guidance is front-loaded where an agent will act on it.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-param catalog with no output schema, knowing there are 19 entries and that their ids feed simulate_cards is essentially sufficient to call it correctly. A brief note on the shape of each entry (id plus label) would close the only remaining gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-param tool applies. The description spends its space on how to use the returned ids rather than mis-describing inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Names a specific resource — the 19 spending categories the API scores against — so the agent knows it's a static catalog lookup, not a computation. It's clearly distinct from compare_two, keep_or_cancel and simulate_cards, though it never states outright that it takes no arguments and returns a fixed list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Call this first" gives explicit ordering, and "map the person's statement onto these ids before calling simulate_cards" names the exact downstream dependency and the prerequisite step. No inference is required about when to invoke it or what to do with the result.
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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