youdotcom-finance-research
This skill delegates finance-grade research to a specialized agent that searches financial data sources such as SEC filings, earnings reports, and market data…
Identity proven by GitHub's verified organisation badge (youdotcom-oss)
- Agents
- Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
- License
- MIT (permissive)
- Pin
- b8db22apinned Oct 9, 2026
- Context cost
- about 1,500 tokenswhen the skill loads
- GitHub stars
- 3on youdotcom-oss/langchain-deepagents-finance-research
- Scripts
- None found
What it does
“Use this skill when the workflow needs finance-grade research, source-backed numeric answers, or exact company, market, or macroeconomic evidence with citations.”
Generated summary from the skill's own text
This skill delegates finance-grade research to a specialized agent that searches financial data sources such as SEC filings, earnings reports, and market data to retrieve exact, cited numeric answers. It synthesizes multiple sources into thorough, well-sourced responses with strict citation contracts, making it suitable for workflows that require defensible finance evidence rather than conversational answers.
When to use it
- Public company filings, earnings metrics, and SEC disclosure data with exact period and unit alignment
- Macro and market data questions requiring specific source vintage, currency, or contract terms
- Finance calculations where every input must be retrieved, cited, and verified before computing
- Answer verification when another workflow branch produced an uncited numeric claim
When not to
- Non-finance factual questions or lightweight conversational answers without source requirements
- Real-time trading execution, investment advice, or portfolio recommendations
- Questions where all calculation inputs are already trusted and available
Install
These commands install from the publisher's repository and need no account.
skills CLI
npx skills add youdotcom-oss/langchain-deepagents-finance-research --skill youdotcom-finance-researchInstalls from the repository's default branch, which may have changed since the commit we checked.
GitHub CLI 2.90 or later
gh skill install youdotcom-oss/langchain-deepagents-finance-research youdotcom-finance-research@b8db22a0bda09319a44eda5994b0722e0f0975c8Installs the commit we checked (b8db22a).
Copy by hand
Download the folder at b8db22a and put it in .claude/skills/youdotcom-finance-research for Claude Code and in .agents/skills/youdotcom-finance-research for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.
Claude Code plugin
/plugin install youdotcom-agent-skills@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Copy for your agent
A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.
Prompt
Install the agent skill "youdotcom-finance-research" by You.com. Source, pinned to commit b8db22a0bda09319a44eda5994b0722e0f0975c8: https://github.com/youdotcom-oss/langchain-deepagents-finance-research/tree/b8db22a0bda09319a44eda5994b0722e0f0975c8/reports/20260521_160716/skills/youdotcom-finance-research 1. Download that folder at exactly this commit. Do not use the default branch. 2. Copy every file unchanged, keeping the folder structure, into .claude/skills/youdotcom-finance-research/ for Claude Code and .agents/skills/youdotcom-finance-research/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist. 3. Do not edit the files, and do not run any script in the folder unless I ask you to. 4. When you are done, list the files you copied and where you put them. Listing and checks: https://www.agentnative.dev/skills/you-com/youdotcom-finance-research
SKILL.md at the pin
---
name: youdotcom-finance-research
description: Use this skill when the workflow needs finance-grade research, source-backed numeric answers, or exact company, market, or macroeconomic evidence with citations.
allowed-tools: you-finance
---
# Finance Research Agent Orchestration Skill
Use this skill when a broader agentic workflow needs finance-grade research, source-backed numeric answers, or exact public/company/macroeconomic evidence.
## Purpose
The finance research agent is a specialist evidence engine. It is best used as a delegated branch inside a larger workflow when the main agent needs high-confidence finance answers rather than broad conversational search.
Its retrieval index is optimized for financial data: earnings reports, SEC filings, analyst coverage, market data, and financial news. It runs multiple searches, reads through sources, and synthesizes everything into a thorough, well-cited answer.
## When To Use
Use the finance research agent for:
- Public-company filings, annual reports, investor-relations disclosures, earnings metrics, segment tables, contractual obligations, and note-level values.
- Macro questions that need exact country, period, indicator, unit, vintage, or source-family alignment.
- Financial-market and benchmark questions where contract month, instrument, date, field, currency, or unit matters.
- Derived finance calculations where every source input must be retrieved, aligned, and cited before computing.
- Finance answer verification inside a larger agentic plan, especially when another branch produced a plausible but uncited numeric claim.
- Source-constrained finance research where you need evidence from specific domains.
Prefer the finance research agent over generic web search when the question has any of these properties:
- It asks for a number, ratio, date-specific value, filing value, market value, or official statistic.
- A near miss could be materially wrong, such as adjacent quarter, wrong fiscal year, wrong line item, spot vs futures, stock vs flow, wrong source vintage, wrong unit, or wrong currency.
- The final answer must include citations and be defensible in review.
## When Not To Use
Do not use the finance research agent as the first tool for:
- Non-finance factual questions.
- Lightweight conversational answers that do not require source-backed finance evidence.
- Pure calculation where all inputs are already trusted and available.
- Real-time trading execution, investment advice, or portfolio recommendations.
## How To Invoke
### Via MCP
The `you-finance` tool is served by the You.com MCP server:
- **URL:** `https://api.you.com/mcp?tools=you-finance`
- **Auth:** `Authorization: Bearer <YDC_API_KEY>`
Call the tool with:
```json
{
"input": "What was the latest disclosed value of ...?",
"research_effort": "deep"
}
```
### Via HTTP (direct API call)
**Endpoint:** `POST https://api.you.com/v1/finance_research`
**Auth header:** `X-API-Key: <YDC_API_KEY>`
**Content-Type:** `application/json`
Request body:
```json
{
"input": "What was the latest disclosed value of ...?",
"research_effort": "deep"
}
```
### Response shape
```json
{
"output": {
"content": "The value was $12 million [[1]].",
"content_type": "text",
"sources": [
{
"url": "https://example.com/source",
"title": "Source title"
}
]
}
}
```
The citation contract is strict: `output.content` uses `[[n]]` tags only. `[[1]]` maps to `output.sources[0]`, `[[2]]` maps to `output.sources[1]`, and so on.
## Orchestration Pattern
For a broader agentic workflow:
1. Classify whether the user question has a finance evidence requirement.
2. Extract the exact checklist: entity, geography, metric, fiscal/calendar period, quarter/month/date, source vintage, unit, scale, currency, stock vs flow, contract month, and output format.
3. Decide the research effort level:
- `deep` (default): most financial questions, including multi-company comparisons, earnings analysis, and regulatory research.
- `exhaustive`: complex financial research tasks where highest quality justifies longer latency and higher cost.
4. Run the finance research agent as an evidence branch, not as an unbounded conversational agent.
5. Treat the returned answer as a cited research artifact. Preserve its citations when synthesizing with other branches.
6. If multiple branches disagree, prefer the branch with the most direct primary source and exact period/unit alignment.
## Handling Results
The broader orchestrator should:
- Preserve `output.content` and `output.sources` together.
- Never detach a `[[n]]` citation from its source list.
- Use source titles/URLs for traceability, but do not expose internal tool traces unless the product surface explicitly supports that.
- If the finance answer says evidence is insufficient, do not override it with an uncited guess from another branch.
- If the finance agent times out but completed a supported branch, it may return a best-effort partial final answer. Treat it as supported only to the extent its citations and wording support the claim.
## Reliability Notes
The finance research agent is optimized for correctness over speed. It may be expensive relative to simple search because it runs parallel research branches and multi-source verification.
Use it deliberately:
- Good: "Find the exact figure and cite the filing/report."
- Good: "Verify this macro value against official data."
- Good: "Resolve which of these conflicting finance values is source-correct."
- Bad: "Give me a quick opinion on whether to buy this stock."
- Bad: "Summarize today's market news" unless exact cited finance evidence is required.
## Failure Policy
If the finance research agent fails or returns insufficient evidence:
- Retry only if the workflow can improve the query, source constraints, or effort level.
- Do not blindly increase effort without narrowing the exact evidence target.
- Consider a second branch that searches known official URLs if the first run lacked source specificity.
- Surface insufficiency honestly when no directly supported answer is available.
From youdotcom-oss/langchain-deepagents-finance-research at b8db22a, shown as plain text under its license: MIT (permissive). The license text is in LICENSE.
View SKILL.md on GitHub at b8db22aFiles
- SKILL.md6.2 KB · 2127f160dbbb
- openapi_finance_research.yaml13 KB · fe413eb3384c
2 files, 19 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
Skill folder on GitHub at b8db22aAlso in
The same SKILL.md content appears in these places too. We list it once and credit the oldest public source.
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