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

82%

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Securityby

Passed

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Quality

Content

72%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.

Highly actionable and well-structured with accurate progressive disclosure to real bundle files, but it is verbose for an overview and lacks explicit validation checkpoints integrated into its workflows.

Suggestions

Trim the four full "Common Patterns" function definitions to brief illustrative snippets or move them to scripts/fred_examples.py, keeping the SKILL.md body lean as an overview.

Integrate the error-handling check (e.g., "if 'error' in result: ... before processing observations") as an explicit validation checkpoint inside the observation-fetching workflows rather than presenting it only in a standalone section.

Consider condensing the Popular Economic Series table and the transformations/frequency tables, since detailed parameter reference is already covered in references/series.md.

Dimension	Reasoning	Score
Conciseness	Tone is efficient and avoids explaining known concepts, but the body (~430 lines) inlines four full "Common Patterns" function definitions plus long series/transformations/frequency tables that largely duplicate the reference files and could be tightened.	3 / 5
Actionability	Fully executable, copy-paste-ready Python throughout with real series IDs (GDP, UNRATE, CPIAUCSL), real parameters (units="pch", frequency="q"), a runnable Quick Start, and a concrete script invocation ("uv run python scripts/fred_examples.py") covering the common cases.	5 / 5
Workflow Clarity	A clear Quick Start sequence and per-endpoint mini-workflows exist, but validation checkpoints are not woven into the workflows; the Error Handling pattern is shown in isolation rather than as explicit validate-before-proceed steps within each workflow.	3 / 5
Progressive Disclosure	Clear overview structure with well-signaled, one-level-deep references to 7 reference files (all verified to exist) and 2 scripts; endpoint-count claims match the reference files exactly, and content is appropriately split with a consolidated Reference Documentation section.	5 / 5
	Total	16 / 20 Passed

Description

92%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 that clearly states capabilities and explicit use-conditions with natural trigger terms. Minor room to add a few more synonymous trigger phrases, but it already answers what and when comprehensively.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions and domains ("Query FRED ... API", "GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data") with quantified scale ("800,000+ economic time series from 100+ sources"), giving comprehensive coverage.	5 / 5
Completeness	Explicitly answers both what ("Query FRED ... API for 800,000+ economic time series") and when ("Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research") with concrete trigger phrases.	5 / 5
Trigger Term Quality	Strong natural keyword coverage ("GDP", "unemployment", "inflation", "interest rates", "macroeconomic analysis", "economic forecasting", "academic research"), but a few natural synonyms/extensions a user might say are absent, sitting just below the comprehensive 5 anchor.	4 / 5
Distinctiveness Conflict Risk	Targets a named, specific system ("FRED (Federal Reserve Economic Data)") with tightly scoped economic-indicator triggers, giving a clear niche with minimal conflict risk against unrelated skills.	5 / 5
	Total	19 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning

	Total	15 / 16 Passed

Repository: foryourhealth111-pixel/Vibe-Skills
Path: bundled/skills/fred-economic-data/SKILL.md
Commit: d5ae560

Reviewed: 1 day ago

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