Get a calculator's inputs (labels, units, defaults, min/max) and formula before running it. requiresPositive marks a field whose documented minimum of 0 is really exclusive. Use the tool slug from search_calculators. Try: {"tool":"oee"}
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | Calculator slug, e.g. 'oee' or 'unit-cost' |
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 a useful quirk: 'requiresPositive marks a field whose documented minimum of 0 is really exclusive,' which helps interpret the output. However, it does not mention whether the operation is read-only, any side effects, or error conditions. The description adds some behavioral context but is not comprehensive given the lack of annotations.
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?
The description is concise (~50 words) and well-structured. It opens with the primary purpose, then clarifies a behavioral nuance, and ends with a concrete example. Every sentence adds value with no fluff. The structure front-loads the key information.
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 simple one-parameter tool with no output schema, the description adequately explains what is returned (inputs and formula) and includes the requiresPositive detail that aids interpretation. It also provides a try example. It does not explicitly state that it is read-only, but that is implicitly clear from the wording. Overall, enough for an agent to call it correctly.
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 schema already provides full documentation for the 'tool' parameter (100% coverage), including an example. The description reinforces that the slug comes from search_calculators and shows a try example, but this is mostly redundant. The baseline of 3 is appropriate since the schema handles the parameter explanation.
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?
The description clearly states the tool retrieves a calculator's inputs and formula, distinguishing it from running or searching. It uses a specific verb 'Get' and resource 'calculator's inputs' and explicitly mentions 'before running it,' which contrasts with run_calculator. This makes its purpose unambiguous.
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?
The description gives clear context: use this tool before running a calculator, and obtain the slug from search_calculators. It even provides a try example. It does not explicitly say 'use run_calculator for execution,' but the 'before running it' phrasing implies that. This is adequate usage guidance without being overly explicit about alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but several clusters overlap: ask/brief/get_index all answer questions, get_revisions/get_vintages both cover historical data, and get_provenance/get_receipts/get_citation all support verification. Descriptions clarify some boundaries, but an agent could easily misselect between ask and get_index for tariff or cost questions.
The naming pattern is largely consistent verb_noun with a strong get_ prefix (get_freshness, get_vintages, run_calculator, search_calculators). However, ask and brief break the convention as bare verbs, and lookup_tariff/optimize_sourcing use different verbs, creating minor but noticeable deviations.
17 tools is at the high end of reasonable for a broad domain covering calculators, live data series, tariffs, sourcing optimization, and verification. It feels slightly heavy but each tool has a real function, and the count is justifiable given the breadth.
The tool surface covers the full research workflow: search, lookup, calculate, optimize, verify, cite, and monitor data freshness/revisions. Minor gaps include the lack of a direct series browser (search_site covers it) and the index family being collapsed into a single get_index tool rather than exposed individually.
