report-stock — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited report-stock (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Generates professional reports with comprehensive stock analysis including trend analysis, PMCC viability, and fundamental metrics. Supports both PDF and markdown output formats.
Run the report script for each symbol:
uv run python scripts/report.py SYMBOLThe script returns detailed JSON with:
recommendation - Overall recommendation with strengths/riskscompany - Company info (name, sector, industry, market cap)trend_analysis - Bullish scanner results (score, RSI, MACD, ADX, SMAs)pmcc_analysis - PMCC viability (score, LEAPS/short details, metrics)fundamentals - Valuation, profitability, dividend, balance sheet, earnings historypiotroski - F-Score breakdown with all 9 criteriaspread_strategies - Option spread analysis (vertical spreads, straddle, strangle, iron condor)Step 2a — Write markdown
Read templates/markdown-template.md for formatting instructions. Generate a markdown report from the JSON data and save to sandbox/ as:
sandbox/{SYMBOL}_Analysis_Report_{YYYY-MM-DD}_{HHmm}.mdStep 2b — Convert to PDF (if requested)
Invoke the markdown-to-pdf skill on the markdown file just created:
uv run python .claude/skills/markdown-to-pdf/scripts/markdown_to_pdf.py sandbox/{SYMBOL}_Analysis_Report_{YYYY-MM-DD}_{HHmm}.mdThe PDF is written alongside the markdown file with the same basename.
After generating the report, tell the user:
# Single symbol
uv run python scripts/report.py AAPL
# Multiple symbols - run separately
uv run python scripts/report.py AAPL
uv run python scripts/report.py MSFTAll sections defined in templates/markdown-template.md:
This skill aggregates data from:
scanner-bullish for trend analysisscanner-pmcc for PMCC viabilityfundamentals for financial data and Piotroski scoreAll timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.