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fmp-api

Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading. Use when fetching financial statements, ratios, DCF valuations, insider/institutional ownership, or screening stocks.

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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.

A highly actionable API reference with excellent executable code and appropriate handling of the legacy-endpoint migration, but it underuses its own bundle: the endpoint tables inline what references/ENDPOINTS.md already provides, the production-ready scripts/fmp_client.py wrapper is never referenced, and free/paid information is repeated across three sections.

Suggestions

Replace the inline 'API Endpoints Reference' tables with a short index (or a handful of key endpoints) and point to references/ENDPOINTS.md for the complete reference — the detail already exists in the bundle.

Reference scripts/fmp_client.py from the body (e.g., a 'Ready-made client' section) instead of only showing raw requests code, so readers discover the rate-limited wrapper that ships with the skill.

Deduplicate the free/paid and base-URL information: consolidate 'Free vs Paid Features', the endpoint-table 'Free' column, and the repeated BASE_URL/new-format reminders into one place.

DimensionReasoningScore

Conciseness

The API specifics (endpoints, params, rate limits) are high-value, but there is repeated material: BASE_URL is stated three times (Quick Start code, 'Important: New Endpoint Format', Best Practices #1), the 'Free vs Paid Features' section restates the ⚠️ Paid flags from the endpoint tables and the Rate Limits section, and the 'Unique FMP Features' bullets add little ('Standardized Financials - Normalized line items'). This fits 'mostly efficient but includes some unnecessary explanation or could be tightened'; the time-sensitive /api/v3/ → /stable/ migration is properly isolated in a new-vs-old-format section, avoiding that penalty, but keeps it below 4.

3 / 5

Actionability

Every task ships complete, copy-paste-ready Python with real endpoints, parameters, and runnable examples with expected output ('quote = get_quote("AAPL")', 'filings = get_sec_filings("AAPL", "10-K")'), plus a reusable safe_api_call error handler. Authentication, base URL, and per-task code cover the common cases exactly as the 5 anchor requires; nothing is pseudocode or hand-wavy.

5 / 5

Workflow Clarity

Each task is a clear, unambiguous single-call pattern with usage examples, and the Error Handling section provides an explicit error/empty-response feedback loop, which suits this read-only API skill (no destructive or batch operations, so no validation cap applies). It sits at 4 rather than 5 because there is no guidance on sequencing across tasks or checking remaining daily quota before batch fetching — 'most checkpoints present; minor validation gaps'.

4 / 5

Progressive Disclosure

Section structure is good (Quick Start, tasks, error handling), but the ~65-line inline 'API Endpoints Reference' tables duplicate content that already lives in the bundled references/ENDPOINTS.md, and neither bundle file — references/ENDPOINTS.md nor scripts/fmp_client.py — is ever mentioned or linked from the body, so the references are effectively invisible to a reader. That matches the 3 anchor ('content that should be separate is inline; references present but not clearly signaled'); it stays above 2 because sections are well-organized and the skill is navigable on its own.

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 with explicit what-and-when structure, a named provider, and good natural-language trigger terms including synonyms like 13F. Its only gaps are minor: a few missing common terms (quotes/prices, earnings, financial data) that create slight overlap risk with sibling finance-API skills.

DimensionReasoningScore

Specificity

The description names concrete capabilities — 'fetching financial statements, ratios, DCF valuations, insider/institutional ownership, or screening stocks' plus 'SEC filings, institutional holdings (13F), and congressional trading' — which matches the 'several specific actions' anchor. It falls short of 5 because notable capabilities like real-time quotes/prices and earnings calendars are absent, and 'Financial Modeling Prep API for stocks, fundamentals...' leans on domain nouns rather than verbs for the first half.

4 / 5

Completeness

Both parts are explicit: 'what' is 'Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading' and 'when' is the concrete 'Use when fetching financial statements, ratios, DCF valuations, insider/institutional ownership, or screening stocks'. This mirrors the 5-anchor example structure ('X for A, B, C. Use when ...') exactly; 4 would require the when-clause to be weaker or implicit, which it is not.

5 / 5

Trigger Term Quality

Natural user phrases like 'financial statements', 'DCF valuations', 'SEC filings', 'screening stocks', '13F', and 'congressional trading' are present, with some synonym coverage (13F ↔ institutional holdings, insider/institutional ownership). A few common terms are missing — 'stock quotes', 'prices', 'financial data', 'earnings' — so it fits the 'good keyword coverage, a few natural terms missing' anchor rather than the comprehensive 5.

4 / 5

Distinctiveness Conflict Risk

Naming the specific provider ('Financial Modeling Prep API') and distinctive data like 13F filings and congressional trading gives it a clear niche, but generic triggers like 'fetching financial statements' or 'screening stocks' overlap with the closely related finance-API skills this bundle itself lists (finnhub-api, twelvedata-api, alphavantage-api). That is 'mostly distinct; minor overlap risk with closely related skills' (4), not the minimal-conflict 5.

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/fmp-api/SKILL.md

Reviewed

Table of Contents

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