Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/daloopa/investing/setupnpx skills add daloopa/investing --skill setupgit clone --depth 1 https://github.com/daloopa/investingWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00015 | $0.01077 |
| Opus 5 | $0.00008 | $0.00539 |
| Sonnet 5 | $0.00003 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade A, and why
setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Walk the user through setting up this Daloopa starter kit step by step. Be conversational and helpful.
Step 1: Verify Claude Code
Confirm Claude Code is running (if the user is seeing this, it is — tell them they're good).
Step 2: Install Python Dependencies
Check if required packages are installed. Offer to install them:
pip3 install -r requirements.txt
This installs: requests, beautifulsoup4, html2text, yfinance, openpyxl, python-docx, docxtpl, matplotlib, fredapi.
These are needed for market data, chart generation, Excel model building, and Word document rendering.
Step 3: Daloopa Authentication
Ask the user which authentication method they'd like to use:
Option A: OAuth (Recommended)
- The
.mcp.jsonis already configured for OAuth - On the next MCP tool call, a browser window will open for Daloopa login
- No additional configuration needed
- Just make sure they have a Daloopa account at daloopa.com
Option B: API Key
- Ask the user for their Daloopa API key
- Create/update
.envwith their key:DALOOPA_API_KEY=<their_key> - Update the
daloopaentry in.mcp.jsonto include the API key header (keep thedaloopa-docsentry as-is):
{
"mcpServers": {
"daloopa": {
"type": "http",
"url": "https://mcp.daloopa.com/server/mcp",
"headers": {
"x-api-key": "${DALOOPA_API_KEY}"
}
},
"daloopa-docs": {
"type": "http",
"url": "https://docs.daloopa.com/mcp"
}
}
}
- Tell them they'll need to restart Claude Code for the change to take effect
Step 4: Optional API Keys
Ask if they want to configure optional API keys for enhanced functionality:
FRED API Key (recommended for DCF/valuation work):
- Free at https://fred.stlouisfed.org/docs/api/api_key.html
- Used for risk-free rate in WACC calculations
- Without it, a default rate of 4.5% is used
- Add to
.env:FRED_API_KEY=<their_key>
Step 5: Verify MCP Connection
This project connects to two Daloopa MCP servers:
- daloopa (
mcp.daloopa.com/server/mcp) — Financial data (fundamentals, KPIs, SEC filings) - daloopa-docs (
docs.daloopa.com/mcp) — Daloopa knowledgebase (API docs, how-tos, usage help)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 103 lines · 15 tokens per session scan A 6d3ad4f96a64
setup is a skill published in the GitHub repository daloopa/investing (486 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 1,077 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…