get_econ_seriesDownload an economic time series as rows (long format: date, value) with its citation and license. REQUIRES the free ElkassabgiData API key. Use date_from/date_to to window long series.
| Name | Required | Description | Default |
|---|---|---|---|
| date_to | No | ||
| max_rows | No | ||
| date_from | No | ||
| series_id | Yes | Exact catalog id from search_econ_series, e.g. 'worldbank:NY.GDP.MKTP.CD:DEU' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds valuable context about API key requirement and output format (long format rows with citation/license). This goes beyond the annotation, though rate limits or error handling are omitted.
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 two sentences, front-loads the core purpose, and includes key usage guidance without any unnecessary words.
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?
Given no output schema and 25% schema coverage, the description provides essential purpose, usage, and output format. It lacks details on default max_rows behavior and error handling, but is fairly complete for a data download tool.
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 description coverage is only 25% (only series_id described). The description adds meaning for date_from/date_to (window long series) but does not explain max_rows or date_to beyond the schema. It partially compensates for low coverage.
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 downloads an economic time series in long format with date, value, citation, and license. It distinguishes from siblings like search_econ_series and get_econ_series_metadata by focusing on data retrieval.
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 explicitly mentions the required API key and guides windowing with date_from/date_to. However, it does not provide explicit when-not-to-use or alternative tool references.
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.
Each tool targets a distinct resource/action: auth status, freshness, econ series, metadata, family status, HF/IP download links, dictionaries, source listings, and search. No overlapping functionality.
All tool names follow a consistent verb_noun pattern: get_* for retrieving specific items, list_* for enumerations, search_* for queries. Naming is uniform and predictable.
11 tools is well-scoped for a data library server covering multiple domains (econ, HF, IP) with retrieval, metadata, listings, and status checks. No redundancy or excessive granularity.
The toolset covers the full lifecycle for a read-only data service: status/auth, search, retrieval (via download links), metadata, variable dictionaries, and source listings. No obvious gaps for the stated purpose.