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Glama

FRED Economic Data

get_release_dates

Get release dates for a specific FRED data release.

Returns the dates when a particular data release was published. Useful
for tracking when economic indicators are updated. Common release IDs:
- 10: Consumer Price Index
- 46: Producer Price Index
- 50: Employment Situation (jobs report)
- 53: Gross Domestic Product
- 17: Federal Reserve H.15 (interest rates)
- 21: Federal Reserve H.6 (money stock)

Args:
    release_id: FRED release identifier (integer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
release_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It explains the output (dates of publication) but does not explicitly state non-destructive behavior or authentication needs. It is adequate but not rich.

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 brief (about 5 lines), front-loaded with purpose, and every sentence adds value. No fluff.

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

Completeness5/5

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

With only 1 parameter and an output schema (so return values are documented), the description covers the parameter well, provides usage examples, and explains the output. It is complete for the tool's complexity.

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

Parameters5/5

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

The schema has 0% description coverage, but the description fully explains the parameter 'release_id' as a FRED release identifier with integer type and provides a list of common IDs with meanings.

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

Purpose5/5

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

The description clearly states the verb 'Get' and the resource 'release dates for a specific FRED data release'. It differentiates from siblings (get_category_series, get_series_info, etc.) by focusing on release dates.

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?

The description provides context (useful for tracking economic indicator updates) and lists common release IDs. While it doesn't explicitly contrast with siblings, the distinct purpose makes usage clear.

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

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: get_category_series browses series by category, get_release_dates tracks publication dates, get_series_info provides metadata, get_series_observations retrieves data points, and search_series finds series by keyword. The descriptions reinforce these unique roles, eliminating any ambiguity.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with 'get_' or 'search_' prefixes and descriptive nouns (e.g., get_category_series, search_series). The naming is uniform and predictable, making it easy for agents to understand the action and target resource.

Tool Count5/5

With 5 tools, this server is well-scoped for accessing FRED economic data. It covers essential operations like searching, retrieving metadata, and fetching observations, without being overly sparse or bloated. Each tool serves a clear purpose in the data exploration workflow.

Completeness4/5

The tool set provides strong coverage for browsing and retrieving economic data, including search, metadata, and observations. However, it lacks direct update or manipulation tools (e.g., for user favorites or annotations), which are minor gaps but not critical for the core domain of data access.

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