CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

yfinance-data

Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.

72

Quality

91%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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 skill body: environment setup with a conditional install checkpoint, a request-to-method mapping table, terse key rules with concrete limits, and clean deferral to a single real reference file. The main gaps are the duplicated intro sentence, a skeleton general-pattern example that never shows the mandated try/except wrapper, and no explicit error-recovery loop for rate-limited or empty responses.

Suggestions

Delete the duplicated intro sentence under the title (the frontmatter description already covers it) and trim the host-specific shell-probe preamble to one short line.

Show one complete worked example (e.g., a try/except around ticker.history with an empty-DataFrame check) so the 'always wrap in try/except' rule is executable rather than aspirational.

Add a brief error-recovery step in Step 3 for rate limits or empty data (e.g., retry with a delay, then report the failure) to close the feedback loop.

DimensionReasoningScore

Conciseness

The body is dense and table-driven with little padding, but has minor trim opportunities: the intro sentence 'Fetches financial and market data from Yahoo Finance using the yfinance Python library' duplicates the frontmatter description, and the Codex/shell-probe preamble adds meta-explanation. This fits the 'efficient; minor instances of over-explanation' anchor, not the lean 5.

4 / 5

Actionability

Concrete executable pieces abound (install probe, install snippet, request-to-method mapping table, period/interval tables, specific intraday limits), but the general pattern is a skeleton ('# ... use the appropriate method from the reference') and rule 1 mandates 'Always wrap in try/except' without ever showing such an example. Mostly executable with minor gaps — anchor 4, not the fully copy-paste-ready 5.

4 / 5

Workflow Clarity

A clear four-step sequence (ensure availability, identify need, write/execute code, present data) with a conditional checkpoint in Step 1 (install if YFINANCE_NOT_INSTALLED). There is no explicit error-recovery loop for rate limits or empty data beyond the try/except mandate. This is read-only fetching, so the destructive/batch cap does not apply; it fits 'clear sequence with most checkpoints present; minor validation gaps' rather than the feedback-loop anchor at 5.

4 / 5

Progressive Disclosure

The body is a lean overview (mapping table, key rules, valid parameters) with the bulk API detail split into a verified one-level-deep reference, clearly signaled in a 'Reference Files' section with purpose and a usage cue ('Read the reference file when you need exact method signatures or edge case handling'). This matches the top anchor for clear overview with well-signaled references.

5 / 5

Total

17

/

20

Passed

Description

100%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.

An exemplary description: it states what the skill does, when to use it with natural trigger phrasing including bare-ticker inference, comprehensively lists concrete data capabilities, and explicitly delegates overlapping analysis tasks to a dedicated skill. Third-person voice is used throughout with no fluff or over-claims.

DimensionReasoningScore

Specificity

The description enumerates many concrete capabilities ('current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data'), matching the anchor for comprehensive specific coverage rather than the 'minor gaps' anchor below it.

5 / 5

Completeness

Both 'what' ('Fetch financial and market data with the yfinance Python library (Yahoo Finance)') and 'when' ('Use this skill whenever the user wants stock data: ...') are explicit with concrete trigger phrases, matching the top anchor rather than the 'when could be more explicit' anchor at 4.

5 / 5

Trigger Term Quality

It uses natural user-facing phrases ('stock data', 'price history', 'options chains', 'dividends', 'earnings', 'analyst estimates') and even concrete ticker examples '(AAPL, MSFT, TSLA)' plus an inference trigger ('Use it even when the user gives only a ticker symbol'), giving comprehensive natural-term coverage.

5 / 5

Distinctiveness Conflict Risk

It carves a clear niche (Yahoo Finance data via yfinance) and adds explicit boundary guidance ('For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill'), minimizing conflict with sibling skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

himself65/finance-skills

Path

plugins/market-analysis/skills/yfinance-data/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.