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financial-intel

financial-intel is a skill for Claude Code, Codex from SELAT-AI/selat-skills. It costs 130 tokens per session (2,412 once invoked), scanned A, original, Apache-2.0.

A workflow for creating a verified cold-email list. Cold email is unsolicited business outreach, while verification checks whether an email address is likely deliverable.

In plain words
What is it for?
Finding target companies, collecting domain emails, locating a specific person's address, checking deliverability, enriching leads, and gathering brand context.
Why use it?
It brings company discovery, contact lookup, email finding, verification, and personalization data into one ordered process.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

not rated 2repo changed 22d ago A scan 130 tokens original Apache-2.0

Good fit Finding target companies, collecting domain emails, locating a specific person's address, checking deliverability, enriching leads, and gathering brand context.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/selat-ai/selat-skills/financial-intel
View source ↗ SELAT-AI/selat-skills
Install

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.

Any agent
npx skills add SELAT-AI/selat-skills --skill financial-intel
Clone the repo
git clone --depth 1 https://github.com/SELAT-AI/selat-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for financial-intel

README.md
[![agentmods](https://agentmods.dev/badge/skills/selat-ai/selat-skills/financial-intel/github.svg)](https://agentmods.dev/skills/selat-ai/selat-skills/financial-intel)
Your own site
<a href="https://agentmods.dev/skills/selat-ai/selat-skills/financial-intel"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/financial-intel/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for financial-intel

Your own site · 80×15
<a href="https://agentmods.dev/skills/selat-ai/selat-skills/financial-intel"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/financial-intel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,412 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00130 $0.02412
Opus 5.5 $0.00052 $0.00965
Sonnet 5.5 $0.00026 $0.00482
Haiku 4.5 $0.00013 $0.00241

Measured 22d ago against content hash ef7e2a9360c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

financial-intel 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 22d 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.

skills/financial-intel/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

financial-intel

When To Use

Use this skill for a fixed five-call crypto market-research bundle when the user wants several independent signals in one brief:

  • current token spot price;
  • token market, volume, supply, and price-change metrics;
  • one user-selected US equity or ETF benchmark quote;
  • chain-wide aggregated smart-money holdings; and
  • current news and market context with source URLs.

The user must identify one coherent crypto asset across symbol, coin, assetChain, and query, and explicitly select the ticker benchmark. For example, ETH / ethereum / ethereum / QQQ / an Ethereum-specific current news query is coherent. Do not silently combine an asset with unrelated manifest defaults.

This is a research workflow, not personalized financial advice. It does not place trades, predict returns, or decide whether the user should buy, hold, or sell. For an equity-only study or a single price/news lookup, choose a smaller skill or free endpoint discovery instead of paying for all five calls.

Workflow

  1. Install the vetted recipe:

    selat skill install financial-intel

  2. Collect and validate all five required inputs:

    • symbol: token symbol, such as ETH;
    • coin: matching CoinGecko ID, such as ethereum;
    • ticker: the explicit US equity or ETF benchmark, such as QQQ;
    • assetChain: Nansen data chain, such as ethereum; and
    • query: current, asset-specific search wording.

    Confirm the symbol and CoinGecko ID refer to the same asset. Explain that the Nansen step describes the whole selected chain, not that asset alone.

  3. Probe all five payment challenges for free:

    selat skill verify ~/.config/selat/skills/financial-intel \
  --symbol ETH \
  --coin ethereum \
  --ticker QQQ \
  --assetChain ethereum \
  --query "Ethereum ETH ETF flows regulation latest news" \
  --live-probe

  4. Show every live quote, the expected cumulative total, and the sum of all per-step caps. Obtain explicit approval for the exact workload and a proposed cumulative session budget. Verification without --pay is free.

Read the full file on GitHub · 203 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 22d ago Changed · +76 lines · -27 tokens per session ef7e2a9360c0
  2. 1mo ago First seen · 127 lines · 157 tokens per session scan A 629f172f3ce5

Subscribe to this mod's changes

financial-intel is a skill published in the GitHub repository SELAT-AI/selat-skills (2 stars, last pushed today), licensed Apache-2.0. It adds 130 tokens to every session and 2,412 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-31.

Claude CodeFinance and fintechagent-paymentsagent-skillsagentic-commerceai-agentscircle
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