Get U.S. economic indicators from BLS — CPI (inflation), PPI (producer prices), Non-farm Payrolls (employment), Unemployment Rate, JOLTS. Filter by category.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Number of days of history (default 365) | |
| category | No | Category (case-insensitive): cpi/inflation, ppi, nfp/payrolls, unemployment, jolts, or all | all |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It does not disclose any behavioral traits such as data freshness, rate limits, or authentication requirements. It only names the data source (BLS) which is insufficient.
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 a single, front-loaded sentence that conveys the main purpose and lists example indicators. No superfluous 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 only 2 simple parameters and no output schema, the description is mostly complete. It could hint at the output format (e.g., historical data vs latest) but is adequate for most agents.
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%, so both parameters are already described in the schema. The description's 'Filter by category' adds minimal new meaning beyond the schema. Baseline of 3 is appropriate.
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 it retrieves U.S. economic indicators from BLS and lists specific data points (CPI, PPI, etc.). It distinguishes this tool from siblings like get_fed_rates or stock-oriented tools.
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 implies usage via 'Filter by category' and listing categories, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The context is clear enough given sibling tool names.
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 and action, and descriptions explicitly disambiguate similar pairs (e.g., get_congress_member vs get_congress_trades, get_crypto_holder vs get_crypto_holders). No two tools appear to do the same thing.
The dominant pattern is get_<noun>, with list_<noun> for enumerations. Minor deviations exist: a bare 'search' tool and the 'sec_' prefix on SEC filing tools break the uniform verb_noun style, but the pattern remains predictable.
At 24 tools, this is on the heavier side, but the server spans multiple financial data domains (SEC filings, stocks, insider trading, crypto, rates, economics), so each tool has a clear purpose. It is just below the 'too many' threshold.
The tool surface is remarkably complete for financial data retrieval: SEC filing lifecycle is covered (list -> index -> document), institutional ownership is available from both stock and institution perspectives, and insider/congress/crypto/economic data are all present. No obvious gaps or dead ends.