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SKILL verified MIT Self-run

Funda Data

skill-himself65-finance-skills-funda-data · by himself65

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Install

$ agentstack add skill-himself65-finance-skills-funda-data

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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How agent discovery & health will work →
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About

Funda AI Skill

Funda AI exposes two complementary surfaces backed by the same data:

| Surface | Best for | Auth | Output | |---|---|---|---| | MCP agent_chat at https://funda.ai/api/mcp | Research, analysis, synthesis | OAuth (auto via claude mcp add) | Synthesized text with disclaimer | | REST /v1/* at https://api.funda.ai | Raw structured data | FUNDA_API_KEY Bearer | JSON |

Both require an active Funda AI subscription.


Step 1: Decide Which Surface

| User wants | Surface | |---|---| | DCF / comps walkthrough, sector view, transcript synthesis, company primer | MCP | | Earnings preview/recap with judgment, beat-miss decomposition, narrative framing | MCP | | Real-time or intraday quote, EOD price history | REST | | Raw options chain snapshot, greeks, GEX time series | REST | | Specific line item from a financial statement (single number, JSON) | REST | | 13F filings, insider trades, congressional trades as rows | REST | | News with structured sentiment / event timeline (JSON) | REST | | Bulk dataset downloads | REST | | AI-company hiring signals (OpenAI, Anthropic, Google, xAI) | REST |

Default to MCP for ambiguous research-style questions. Use REST when the user wants machine-readable structured data — or when the MCP refuses (real-time prices, raw quotes).

The MCP also refuses buy/sell calls, price targets, personalized portfolio advice, tax/legal advice, and trade execution. Those are out of scope for both surfaces — decline politely and don't fall through to REST hoping for a different answer.


Step 2: MCP Flow (Research)

2a. Verify the MCP is connected

!`claude mcp list 2>/dev/null | grep -iE "^funda:" || echo "FUNDA_MCP_NOT_CONNECTED"`
  • A line starting with funda: → registered. The tool is callable as mcp__funda__agent_chat. Continue.
  • FUNDA_MCP_NOT_CONNECTED → ask the user to install:

``bash claude mcp add --transport http funda https://funda.ai/api/mcp `` A browser tab opens for OAuth approval (1-hour token + 30-day refresh, auto-managed). The Claude Code session may need to be restarted before the tool registers.

2b. Frame the question

agent_chat is a fresh research turn with no cross-call memory — bake the ticker, time horizon, and assumptions into the question text itself.

| User wants | Question shape | |---|---| | Earnings preview | "Preview MSFT's Q3 print Thursday — segment trends, where consensus is aggressive/conservative, beat/miss pattern." | | Earnings recap | "Walk through NVDA Q2: beat/miss by segment, guide vs consensus, transcript Q&A on data-center demand." | | Sector deep-dive | "Summarize the 2026 hyperscaler capex cycle — spending tiers by name, supplier exposure, gross-margin implications." | | Supply chain | "Map TSMC's customer concentration and N2 ramp risks — top three exposures by revenue." | | Filing summary | "Diff the new risk factors in PLTR's latest 10-K versus the prior year." | | DCF | "Walk through a DCF for NVDA assuming 25% data-center growth, 10% terminal margin, 9% WACC — surface the sensitivity table." | | Macro | "Where in the Dalio long-term debt cycle is the US, and what does that imply for duration positioning?" | | Ownership | "Has institutional ownership of CRWD shifted in the latest 13F filings — net buyers vs sellers?" |

If the user gave only a ticker, ask one clarifying question to scope the turn (preview? recap? primer? DCF?) before calling — vague questions burn a turn and return vague answers.

If the user is following up on a prior Funda response, quote the relevant paragraph back inside the new question; the agent has no memory of prior calls.

For more example questions per topic, see references/research-topics.md.

2c. Call the tool

mcp__funda__agent_chat(question: "")

Typical run is 15–60 seconds; the server streams progress notifications throughout, so the client doesn't time out.

Response shape:

  • content[0].text — answer prefixed with [Funda research output — fundamental analysis, informational only…]. Keep the prefix.
  • _meta["funda.io/conversation_id"] — UUID. The in-app history page is https://funda.ai/agent-chat?c= (the /agent-chat route redirects to /agent-chat-v2?c=).
  • _meta["funda.io/timed_out"]true if the agent hit its run budget. Answer is partial; offer to retry with a tighter scope.

If the call returns 403 subscription_required, the MCP is registered but the account isn't subscribed — direct the user to https://funda.ai to activate.

Each call costs a research turn. Don't speculatively re-call with a rephrased question if the first answer was reasonable.


Step 3: REST Flow (Raw Data)

3a. Resolve FUNDAAPIKEY

The skill resolves FUNDA_API_KEY in this order:

  1. FUNDA_API_KEY environment variable
  2. FUNDA_API_KEY in .env in the current directory
  3. FUNDA_API_KEY in .env at the git repo root (so a worktree inherits the key from the main checkout)
!`if [ -n "$FUNDA_API_KEY" ]; then echo "KEY_FROM_ENV_VAR"; elif [ -f .env ] && grep -qE "^FUNDA_API_KEY=" .env; then echo "KEY_FROM_LOCAL_DOTENV:$(pwd)/.env"; else GIT_COMMON=$(git rev-parse --path-format=absolute --git-common-dir 2>/dev/null); if [ -n "$GIT_COMMON" ]; then ROOT=$(dirname "$GIT_COMMON"); if [ -f "$ROOT/.env" ] && grep -qE "^FUNDA_API_KEY=" "$ROOT/.env"; then echo "KEY_FROM_ROOT_DOTENV:$ROOT/.env"; else echo "KEY_NOT_SET"; fi; else echo "KEY_NOT_SET"; fi; fi`

Then act on the result:

  • KEY_FROM_ENV_VAR — use $FUNDA_API_KEY directly in curl calls.
  • KEY_FROM_LOCAL_DOTENV: / KEY_FROM_ROOT_DOTENV: — load once before calling:

``bash export FUNDA_API_KEY=$(grep -E "^FUNDA_API_KEY=" | head -1 | cut -d= -f2- | sed 's/^["'\'']//;s/["'\'']$//') ``

  • KEY_NOT_SET — ask the user for their key. They can either export FUNDA_API_KEY="..." or add FUNDA_API_KEY=... to .env at the repo root (preferred for worktrees).

3b. Find the right endpoint

Match the user's request to a category and read the corresponding reference file for full parameters and response schemas.

| Category | Endpoint family | Reference | |---|---|---| | Real-time / batch / aftermarket quotes | /v1/quotes?type=... | references/market-data.md | | Historical EOD, intraday candles, technical indicators | /v1/stock-price, /v1/charts | references/market-data.md | | Commodity / forex / crypto quotes | /v1/quotes?type=commodity-quotes | references/market-data.md | | Income / balance / cash flow / metrics / ratios | /v1/financial-statements | references/fundamentals.md | | Company profile, peers, shares float, search, screener, list | /v1/company-profile, /v1/company-details, /v1/search, /v1/companies | references/fundamentals.md | | Analyst estimates, price targets, grades, DCF, ratings | /v1/analyst?type=... | references/fundamentals.md | | Options chain, greeks, GEX, IV, max pain, flow, screener | /v1/options/... | references/options.md | | Supply-chain KG: suppliers, customers, competitors, partners | /v1/supply-chain/... | references/supply-chain.md | | Twitter, Reddit, Polymarket, government trading, ownership | /v1/twitter-posts, /v1/reddit-posts, /v1/polymarket/..., /v1/government-trading, /v1/ownership | references/alternative-data.md | | AI-enriched news + aggregated sentiment + event timeline | /v1/news/ticker, /v1/news/timeline, /v1/news/sentiment | references/news-enriched.md | | SEC filings, earnings/podcast transcripts, research reports | /v1/sec-filings, /v1/transcripts, /v1/investment-research-reports | references/filings-transcripts.md | | Earnings / dividend / IPO / splits / economic calendar | /v1/calendar?type=... | references/calendar-economics.md | | Treasury rates, GDP/CPI indicators, FRED, risk premium | /v1/economics, /v1/fred | references/calendar-economics.md | | Stock news, gainers/losers, ETF holdings, ESG, COT, bulk, market hours | /v1/news, /v1/market-performance, /v1/funds, /v1/esg, /v1/cot-report, /v1/bulk, /v1/market-hours | references/other-data.md | | AI-company hiring signals (OpenAI, Anthropic, Google, xAI, Mercor, SurgeAI) | /v1/recruit-... | references/recruit.md | | Claude API proxy via Bedrock | /v1/claude/v1/messages | references/claude-proxy.md |

3c. Call the endpoint

curl -s -H "Authorization: Bearer $FUNDA_API_KEY" \
  "https://api.funda.ai/v1/?" | python3 -m json.tool

All responses are {"code": "0", "message": "", "data": ...}. A non-zero code is an error — read message.

List endpoints paginate: {"items": [...], "page": 0, "page_size": 20, "next_page": 1, "total_count": N}. Pages are 0-based; next_page is -1 when exhausted.

For broad ticker overviews ("tell me about AAPL"), combine a few REST calls: /v1/company-profile for sector/CEO/mcap/price + /v1/financial-statements?type=key-metrics-ttm + /v1/analyst?type=price-target-summary.


Step 4: Respond to the User

  • For MCP synthesis: surface with structure (tables, bullets, headings) — don't dump the raw blob. Preserve the Funda disclaimer; never repackage analysis as a recommendation, price target, or trade signal.
  • For MCP responses, cite https://funda.ai/agent-chat?c={conversation_id} so the user can inspect the agent's full timeline.
  • For REST responses, format numbers cleanly (prices to 2 decimals, ratios to 2-4, large numbers with commas or abbreviations like $2.8T). Use tables for comparative data; summarize trends rather than dumping time series.
  • For DCF / valuation work, surface the assumptions Funda used so the user can adjust them.
  • Note the source: "Funda AI" (whether MCP or REST).
  • Never provide trading recommendations — present the data and let the user draw conclusions.

Reference Files

MCP path:

  • references/research-topics.md — categorized example questions and tips for framing agent_chat queries.

REST path:

  • references/market-data.md — quotes, historical prices, charts, technical indicators
  • references/fundamentals.md — financial statements, company profile/details, search/screener, analyst, companies list
  • references/options.md — chains, greeks, GEX, flow, IV, screener, contract-level data
  • references/supply-chain.md — supply-chain KG, relationships, graph traversal
  • references/alternative-data.md — Twitter, Reddit, Polymarket, government trading, ownership
  • references/news-enriched.md — AI-enriched news, event timeline, aggregated sentiment
  • references/filings-transcripts.md — SEC filings, earnings/podcast transcripts, research reports
  • references/calendar-economics.md — calendars, economics, treasury, FRED
  • references/other-data.md — news, market performance, funds, ESG, COT, bulk, market hours
  • references/recruit.md — AI-company hiring signals, JD classifications, product clusters, launch probabilities
  • references/claude-proxy.md — Claude API proxy via Bedrock

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.