A curated collection of Claude Code skills for Indian stock market research and analysis.

These skills work as plug-and-play modules for Claude Code — give it domain expertise for equity research, concall analysis, financial data collection, and more.

Install directly and get all skills + automatic updates:

claude plugin add github:samyakjain0606/awesome-stock-skills

Copy individual skills into your project's .claude/skills/ directory:

# Clone the repo
git clone https://github.com/samyakjain0606/awesome-stock-skills.git

# Copy a skill to your project
cp -r awesome-stock-skills/skills/fetch-concalls /path/to/your-project/.claude/skills/

Once installed, Claude Code automatically picks up the skill. Just ask naturally:

> fetch concalls for YATHARTH
> get concall links for GRSE
> download concall transcripts for TCS
> growth triggers for SAILIFE
> VP analysis for HDFCBANK
> variant perception scorecard for TATAELXSI
> create a notebook for HDFCBANK concalls
> add this URL as source to my notebook
> generate a podcast for my notebook
> query my notebook about growth triggers
> /stock-research-pipeline GRAVITA
> deep dive on TCS
> equity report for RELIANCE
> run the stock research pipeline on HDFCBANK
> /stock-research-publish GRAVITA
> publish the TCS report
> deploy the RELIANCE report to netlify
> I want an html version of the HDFCBANK report

• screener.in — Primary source for aggregated BSE concall links
• BSE India — Official regulatory filings
• NSE India — Official regulatory filings

The nlm-skill requires the notebooklm-mcp-cli CLI tool:

uv tool install notebooklm-mcp-cli
nlm login  # authenticate with Google

GitHub: nicholasgriffintn/notebooklm-mcp-cli

Requires both the nlm CLI (see above) and Python with reportlab for PDF generation:

pip install reportlab

For HTML deploys to Netlify, the skill installs the CLI for you on first run (with confirmation). To install manually:

npm install -g netlify-cli
netlify login

PDF output uses the same reportlab setup as stock-research-pipeline.

These skills are young and the best ones come from real-world stress-testing on dozens of companies — different sectors, different reporting styles, different sources of edge. Your PRs make these skills better for everyone.

1. Create a folder under skills/your-skill-name/
2. Add a SKILL.md with YAML frontmatter (name and description)
3. Add a README.md with a quick "what it does / setup / usage" section
4. Make it self-contained — no external dependencies beyond Claude Code's built-in tools and commonly available CLIs (Python, nlm, netlify, etc.)
5. Open a PR — include a short example of the skill running on a real company

Even small contributions help:

• More sectors covered — most skills lean industrial/manufacturing today; banks, NBFCs, insurance, FMCG, IT services, pharma, and SaaS each need sector-specific tweaks (NIM/CASA for banks, SSG for retail, ARR/NRR for SaaS, etc.).
• Better data sources — fallbacks for when screener.in is down, BSE/NSE direct scrapers, alternative financial data providers.
• Tighter design rules — particularly for the HTML/PDF outputs in stock-research-publish. Fonts, color palettes, mobile breakpoints, dark-mode polish.
• More analysis frameworks — DCF helpers, peer-comparison automation, technical analysis layers, ownership/insider tracking.
• Bug reports with reproduction steps — even if you can't fix it, a clear bug report on a named company is a real contribution.

• No fabricated outputs — skills must fail loud when inputs are missing, never invent data.
• No private data leakage — be careful with example outputs; mock or anonymize anything proprietary.
• Forbidden in HTML/visual outputs — no Inter/Roboto fonts as primary, no indigo/violet gradient text, no emoji section headers, no glowing-shadow animations. These signal "AI template" and undermine trust. See stock-research-publish/SKILL.md for the full list.

If you have an idea but aren't sure how to scope it, open an issue first — happy to discuss.

MIT