fred-economic-data

Query FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring U.S. and international economic indicators.

Quality

90%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

The canonical home for this skill is fred-economic-data in foryourhealth111-pixel/Vibe-Skills

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable API skill that uses progressive disclosure effectively and provides executable examples throughout; main improvement is deduplicating the reference listings to tighten token use.

Suggestions

Remove the standalone 'Reference Documentation' section (or the per-section 'Reference:' lines) — the links are already stated inline in each endpoint section, so one copy suffices.

Trim the Overview 'Key capabilities' bullet list, which restates the description and the endpoint sections that follow.

Add a brief validate-then-proceed note for the API-key setup (e.g., confirm the key works with a trivial get_series call before larger workflows) to strengthen workflow clarity.

Dimension	Reasoning	Score
Conciseness	Code and reference tables dominate with little concept over-explanation, but the per-section 'Reference:' links are duplicated by a separate 'Reference Documentation' section and the Overview capabilities list echoes the description — minor trim opportunities.	4 / 5
Actionability	Copy-paste-ready examples for both the FREDQuery class and direct requests calls, plus transformation/frequency parameters and four complete pattern functions covering the common cases.	5 / 5
Workflow Clarity	A numbered API-key setup sequence, an error-handling feedback pattern, and ready-made pattern functions give a clear sequence; being a non-destructive query skill the destructive cap does not apply, but explicit validate-then-proceed checkpoints are absent.	4 / 5
Progressive Disclosure	SKILL.md is an overview with each endpoint section clearly signaling a one-level-deep references/*.md file, the scripts/ bundle is described, and bulk endpoint detail is appropriately split into the existing reference files.	5 / 5
	Total	18 / 20 Passed

Description

95%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description with an explicit 'Use for' trigger clause and rich natural keywords; its only minor weakness is a narrow verb set (query/access) slightly limiting action specificity.

Dimension	Reasoning	Score
Specificity	Lists concrete actions ('Query FRED... API', 'Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data') with comprehensive data-type coverage, but only two verbs (query/access) so a couple of distinct actions are absent.	4 / 5
Completeness	Explicitly answers both 'what' (query/access 800,000+ series from 100+ sources) and 'when' via a concrete 'Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research...' trigger clause.	5 / 5
Trigger Term Quality	Comprehensive natural terms users would actually say — GDP, unemployment, inflation, interest rates, exchange rates, housing, plus macroeconomic analysis, financial research, economic forecasting — covering synonyms and domain phrasings.	5 / 5
Distinctiveness Conflict Risk	FRED (Federal Reserve Economic Data) is a clearly named, distinct niche with FRED-specific trigger phrases, giving minimal conflict risk with other skills.	5 / 5
	Total	19 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/databases/fred-economic-data/SKILL.md
Commit: fcd2e11

Reviewed: 1 day ago

Table of Contents

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