Describe a SITUATION rather than a question and get every fact bearing on it, each answered and cited. ask for one figure, brief for a decision. Names what it could not establish. Try: {"situation":"sourcing bearings from china"}
| Name | Required | Description | Default |
|---|---|---|---|
| situation | Yes | In plain words: 'importing $250,000 of aluminium from vietnam'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does the work of revealing behavior. It discloses that results are cited, that the tool names facts it could not establish, and that it returns comprehensive facts relevant to the situation. It stops short of detailing any access, latency, or limitations, but the core behavior is transparent enough.
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 compact: it states purpose, contrasts with the alternative, explains a behavioral guarantee, acknowledges a limitation, and gives a sample input. Every sentence earns its place and the key guidance is front-loaded.
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 single-parameter, low-complexity lookup with a schema that already documents the parameter, the description is complete. It explains what the tool does, how to phrase the situation, what output to expect (answered and cited facts), and what happens when it cannot establish facts.
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?
Schema coverage is 100% and the schema gives a plain-words example for the `situation` parameter. The description adds further semantic value by reinforcing the situational framing and offering a second, distinct example ('sourcing bearings from china'), which helps agents understand the expected input style.
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 states a specific verb and resource: describing a situation to get every fact bearing on it, with answers and citations. It also explicitly distinguishes itself from the sibling tool `ask` by contrasting a situation-based briefing with a single-figure question.
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 direct when-to-use guidance: 'ask for one figure, brief for a decision.' It also clarifies the input framing by saying to describe a SITUATION rather than a question, and provides a concrete example starting with 'Try:'.
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.
