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Kelly financial services intel

Skill mr-kelly/skills/skills/kelly-financial-services-intel

Agent Skills by mr-kelly

Install
npx -y skills add mr-kelly/skills --skill kelly-financial-services-intel

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Kelly Financial Services Intel: App-in-Skill daily industry intelligence cockpit for financial services, investment advisory, and family offices. Use when the user asks about financial services, investment advisory, market explainers, client memos, family office,投顾,金融服务, or family-office scenes. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.

SKILL.md

7.5 KB, ~1.5k tokens by cl100k_base, as published. Nobody here has run it

Kelly Financial Services Intel

Overview

Use this skill as Kelly's daily industry-intelligence operator for financial services, investment advisory, and family offices.

It turns current news sources, trend signals, competitor movement, customer questions, and buyer-intent clues into a small reviewable batch:

  • source-backed signals;
  • why each signal matters to the buyer;
  • sales or operating actions for today;
  • draft messages/content for client memo, internal brief, advisor script;
  • blocked claims that need human, legal, compliance, or domain review.

Default interaction mode: App UI. Unless the user explicitly asks for chat-only handling, check onboarding/config, prepare or refresh the local batch, start/reuse the local app with app/start.sh, and give the actual local URL. Use chat-only mode only when the user says "纯聊天", "chat only", "不要打开 UI", or similar.

Product Package

  • Buyer: financial-service founders, family office operators, analysts, and client advisors.
  • Pain: financial teams need fast, sourced explainers and client talking points without overclaiming or giving uncontrolled advice.
  • Offer: daily financial-services intelligence that becomes sourced internal briefs and review-first client drafts.
  • Demo source mix: market news, regulatory updates, macro data, company announcements, portfolio themes, and client questions.

Sales framing:

Every morning, AI watches the sources that affect your business, turns them into today's sales actions, and puts the drafts in a review queue before anything becomes official.

Do not lead with "AI platform", "agent workspace", "database", or model names. Lead with the daily business scene.

Scene Logic

Use this skill to turn financial-market, regulatory, and client-question signals into reviewable relationship-management actions. A signal is valuable when it changes client concern, advisor preparation, risk disclosure, product education, or internal briefing priorities.

Prioritize signals in this order:

  1. regulator, exchange, central-bank, tax, product, or disclosure changes with client-facing implications;
  2. macro, market, company, and portfolio-theme movement that may trigger client questions;
  3. competitor commentary or campaign movement that changes expectations around service, tools, or education;
  4. recurring client objections that can become an evidence-backed memo or meeting agenda.

Actions should become internal briefs, client education memos, advisor talking points, risk reminders, meeting agendas, or Busabase approval batches. Block personalized investment advice, suitability conclusions, performance promises, tax/legal advice, and any trade or money movement.

Boundary

  • The skill may browse public/current sources, reason over buyer intent, draft actions/content, validate schemas, and write local handoff files.
  • The app reads and writes local files only. It must never post content, send WhatsApp/email, mutate CRMs, scrape private systems, spend money, or perform external side effects.
  • Customer-visible drafts, regulated claims, pricing promises, medical/financial/legal advice, and outbound messages are approval-required.
  • Store only the minimal source excerpts needed for review. Do not commit config.local.json, env files, app/.data/, exports, screenshots of private sources, or raw customer data.

First Run And Onboarding

On invocation, check app/.data/onboarding.json and private config readiness. If onboarding is absent/incomplete, guide setup before doing real monitoring.

Ask for non-secret setup details only:

  • company/brand name, geography, language, and customer segment;
  • 3-10 public source URLs or source categories to monitor;
  • competitor names/URLs;
  • approved offer, CTA, and forbidden claims;
  • preferred channels among client memo, internal brief, advisor script;
  • whether Busabase should be the review provider later.

Never ask for API keys or platform tokens in chat. Secrets belong in env files only.

When setup is complete and the user confirms, write app/.data/onboarding.json:

{
  "completed": true,
  "completed_at": "ISO timestamp",
  "config_version": "1"
}

Local App

Start the cockpit with:

skills/kelly-financial-services-intel/app/start.sh

The app uses local HTTP on 127.0.0.1, preferring port 3000 through 4000, or KELLY_FINANCIAL_SERVICES_INTEL_UI_PORT when set.

Required views:

  • #/overview: human-attention panel, today's top signals, ready actions, blocked items, and source coverage.
  • #/signals and #/signals/<id>: source-backed signals with evidence links, buyer-intent interpretation, confidence, risk badges, and suggested next action.
  • #/actions and #/actions/<id>: approved/blocked/reviewable operating or sales actions.
  • #/drafts and #/drafts/<id>: editable client memo, internal brief, advisor script drafts with approve/request-changes/block decisions.
  • #/sources: configured source categories, freshness, and gaps.
  • #/settings: sanitized config summary, onboarding state, provider, language, and accent color.

Demo mode:

  • ?demo=1, ?demo=overview, ?demo=signals, ?demo=actions, ?demo=drafts, and ?demo=detail load deterministic demo data.
  • lang=en or lang=zh forces UI chrome language.
  • Demo API responses never read/write app/.data/ or private config.

File Contract

Read references/ui-schema.md before changing the app, scripts, or generated JSON.

  • app/.data/current_batch.json: current intelligence batch.
  • app/.data/decisions.json: user verdicts and edits keyed by item id.
  • app/.data/agent_tasks.json: queued agent work for requested changes or missing evidence.
  • app/.data/execution_report.json: dry-run/apply handoff report.
  • app/.data/onboarding.json: setup marker.
  • app/.data/agent.lock: temporary lock while the skill writes files.

Validate with:

node skills/kelly-financial-services-intel/scripts/validate_ui_schema.ts skills/kelly-financial-services-intel/app/.data/current_batch.json

Normal Workflow

  1. Detect mode. Default to App UI.
  2. Browse or otherwise collect current public evidence. For news/trends, use exact dates and source URLs.
  3. Build one narrow buyer scene, not a generic AI report.
  4. Write a batch with signals, actions, drafts, and source coverage. Keep every item tied to evidence or mark it blocked.
  5. Validate the batch.
  6. Launch the UI for review.
  7. Poll agent_tasks.json for requested changes and revise only those items.
  8. On "execute/export approved", re-read decisions and run scripts/execute_decisions.ts first as a dry run. Apply only after explicit confirmation.

Safety Defaults

  • Treat outbound messages, regulated claims, medical/financial/legal advice, pricing promises, and publishing as approval-required.
  • If source evidence is weak, mark the item blocked or lower confidence instead of pretending.
  • Preserve source language unless the workflow asks for translation.
  • Use Busabase as the later shared review provider when the workflow needs team approvals; local files remain the reference implementation.

Keep looking

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