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Bls

by io.github.pipeworx-io

Bls Get Series

bls_get_series
Read-onlyIdempotent

Fetch historical time series data for employment, inflation, wages, productivity, or housing. Returns dated data points with values. Provide series ID (e.g., "PAYEMS" for total nonfarm employment).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoBLS registration key (optional, increases rate limits)
end_yearNoEnd year (e.g., "2024"). Default: current year.
series_idYesBLS series ID (e.g., "LNS14000000" for unemployment rate). For multiple series, comma-separate them (e.g., "LNS14000000,CES0000000001").
start_yearNoStart year (e.g., "2023"). Default: current year minus 2.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
seriesYesArray of time series data
statusYesAPI response status (e.g., 'REQUEST_PROCESSED')

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by stating that the tool returns 'dated data points with values,' providing useful behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with no filler. It front-loads the core behavior, adds a return-type statement, and provides a concrete example ID, all in an appropriately compact form.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup tool with full schema coverage, an output schema, and strong annotations, the description is nearly complete. It clearly states the data domain, return format, and required input, though it could briefly differentiate itself from sibling BLS tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already documents all four parameters, including defaults and the optional API key. The description's 'Provide series ID' and example add minimal meaning beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource ('Fetch historical time series data') and lists the covered domains, making the tool's purpose clear. It implies a distinction from siblings like bls_latest and bls_search by emphasizing historical series data, though it does not explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clear context is provided: the tool fetches historical time series and requires a series ID, with an example ('PAYEMS'). However, it does not explicitly state when to choose this tool over bls_latest, bls_popular_series, or bls_search.

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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TDQS

A3.6/5.0
Disambiguation2/5

The ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded trio are nearly indistinguishable, with beta currently behaving identically to the stable version. Entity_profile, recent_changes, and compare_entities also overlap heavily as multi-source company research tools, and the six polymarket tools create additional boundary confusion.

Naming Consistency2/5

Most tools use snake_case, but there is no consistent verb_noun pattern: some are imperative phrases (ask_pipeworx, bls_get_series, resolve_entity), while others are noun phrases (entity_profile, pipeworx_feedback, polymarket_edges, recent_alerts). Even within the bls_* family, bls_latest breaks the verb pattern established by bls_get_series and bls_search.

Tool Count2/5

35 tools is well above the 25+ threshold for 'too many', and the server is named Bls yet only four tools actually serve BLS data. Most of the remaining tools cover unrelated domains like Polymarket arbitrage, memory, feedback, and general Pipeworx routing, making the count feel inflated for the apparent purpose.

Completeness3/5

The four BLS-specific tools cover search, browse, historical series fetch, and latest value, but there is no multi-series fetch or series metadata detail, which is a notable gap for a BLS-focused server. The broader Pipeworx toolset is extensive, but the lack of a coherent stated domain makes completeness hard to evaluate as a unified surface.

Resources