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alphavantage-api

Alpha Vantage financial API for stocks, forex, crypto, and 50+ technical indicators. Use when fetching time series data, technical analysis, fundamentals, economic indicators, or news sentiment.

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 content with excellent executable code and clear per-task coverage, undermined by duplication between the body and references/ENDPOINTS.md and by a progressive-disclosure failure: neither the ENDPOINTS.md reference nor the bundled alphavantage_client.py script is ever referenced from SKILL.md, leaving a 16KB ready-made client undiscoverable. Tightening the endpoint tables into pointers and adding a short 'see references/ENDPOINTS.md for full params' and 'use scripts/alphavantage_client.py for a rate-limited client' would lift both conciseness and structure.

Suggestions

Replace the inlined per-category endpoint tables with one compact summary table and point to references/ENDPOINTS.md for full parameter details, removing the body/reference duplication that costs tokens.

Add a section pointing to scripts/alphavantage_client.py as a production-ready, rate-limited alternative to the hand-rolled requests examples — it is currently bundled but completely undiscoverable from SKILL.md.

De-duplicate the rate-limit information (stated in the table, the 'Free Tier Includes' list, and Best Practices item 3) into a single place, and extend the error-handling example with a retry/backoff step so the rate-limit feedback loop is complete.

DimensionReasoningScore

Conciseness

Line-by-line the body is lean — no conceptual padding or explanations of things Claude already knows — but the endpoint tables (Stock Time Series, Fundamental Data, Forex, Crypto, Economic Indicators, Alpha Intelligence) substantially duplicate what references/ENDPOINTS.md already provides in more detail, and the rate-limit facts are stated three times (table, 'Free Tier Includes' list, and Best Practices item 3). This duplication could be tightened by deferring to the reference file, so it sits at 'mostly efficient but could be tightened' rather than clearly verbose.

3 / 5

Actionability

Every task section provides complete, copy-paste-ready Python functions with real request parameters, response-key parsing ('Time Series (Daily)', 'Technical Analysis: RSI', 'Realtime Currency Exchange Rate'), and runnable usage examples — covering quotes, daily data, RSI, overview, forex, crypto, news sentiment, economic indicators, the CSV-format earnings calendar, and error handling. The examples cover the common cases comprehensively.

5 / 5

Workflow Clarity

The skill is a read-only API reference, so no destructive/batch validation cap applies. The sequence is clear: auth setup, basic usage, per-task recipes, then an error-handling pattern ('safe_api_call') that checks 'Note', 'Error Message', and 'Information' response keys as checkpoints. It does not reach a 5 because there is no explicit feedback loop (e.g. what to do after a rate-limit hit beyond printing) and the bundle's ready-made rate-limited client is never wired into the guidance.

4 / 5

Progressive Disclosure

The body is well-sectioned, but neither bundle file is ever mentioned: references/ENDPOINTS.md is never cited (its endpoint detail is instead re-inlined as condensed tables), and scripts/alphavantage_client.py — a full production-ready client with built-in rate limiting — is completely unsignaled. This matches 'some structure; references present but not clearly signaled; content that should be separate is inline' — the section structure is good, not minimal, which rules out a 2, but the absent navigation to real bundle files rules out a 4.

3 / 5

Total

15

/

20

Passed

Description

83%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 description: explicit what-and-when structure, third-person voice, vendor-named niche, and a solid set of natural trigger terms covering all the API's data domains. Its only weaknesses are limited action-verb variety and a handful of missing synonyms that would overlap with sibling financial-data skills.

DimensionReasoningScore

Specificity

The description names the domain ('Alpha Vantage financial API for stocks, forex, crypto, and 50+ technical indicators') and lists several concrete capability areas ('fetching time series data, technical analysis, fundamentals, economic indicators, or news sentiment'). It falls short of a 5 because the action vocabulary is thin — nearly everything is data-category enumeration with only one action verb ('fetching') rather than multiple distinct concrete actions.

4 / 5

Completeness

It explicitly answers 'what' ('Alpha Vantage financial API for stocks, forex, crypto, and 50+ technical indicators') and 'when' ('Use when fetching time series data, technical analysis, fundamentals, economic indicators, or news sentiment') with concrete trigger phrases, matching the top anchor. The 'Use when...' clause is present and enumerates specific triggering activities.

5 / 5

Trigger Term Quality

Natural user phrases like 'time series data', 'technical analysis', 'fundamentals', 'economic indicators', 'news sentiment', 'stocks', 'forex', and 'crypto' are all present — terms a user would realistically say. A few common variations are missing (e.g. 'stock quotes', 'price data', 'company overview', 'financial data'), so it does not reach the comprehensive synonym coverage of a 5.

4 / 5

Distinctiveness Conflict Risk

Naming the specific vendor 'Alpha Vantage' gives a clear niche with distinct triggers, but the skill itself lists sibling financial-API skills ('twelvedata-api', 'fmp-api', 'finnhub-api') whose trigger domains (technical analysis, fundamentals) overlap with generic phrasing like 'fetching fundamentals' when the user does not name the vendor. Minor overlap risk, so mostly distinct rather than minimal-conflict.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

fernandezbaptiste/Skrillz

Path

skills/alphavantage-api/SKILL.md

Reviewed

Table of Contents

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