Stock Deep Dive logo

Stock Deep Dive

Organization
kansoku-trade
stock-deep-dive

Use when the user asks for an end-to-end orientation on a listed company they don't yet understand, especially when the request combines two or more dimensions in one ask. Triggers on "X 是干什么的", "帮我了解 X", "X 主营 + 同行", "盘前为什么涨", "本周趋势 + 阻力支撑", "X 和其他公司的关系", "first time looking at X", "full brief on X". Skip when the user wants only a single lens — use the targeted Longbridge sub-skill instead.

Overview

Publisherkansoku-trade
Repositorykansoku
Skill namestock-deep-dive
Stars
329
Forks
40
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kansoku-trade on GitHub. Read the source before you install it.

Installation

Install the Stock Deep Dive AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kansoku-trade/kansoku/tree/main/.claude/skills/stock-deep-dive
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kansoku-trade/kansoku.git /tmp/kansoku
mkdir -p .claude/skills
cp -r /tmp/kansoku/.claude/skills/stock-deep-dive .claude/skills/stock-deep-dive
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Stock Deep Dive in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Stock Deep Dive on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Stock Deep Dive is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Stock Deep Dive

Overview

A six-lens onboarding workflow for getting up to speed on one listed company in a single pass. Built from a live session where the author repeatedly failed by quoting community-post numbers as if they were company guidance, by trusting GAAP EPS fields when the market quoted non-GAAP, and by reading YoY % deceleration as business slowdown without checking the base.

Core principle: anchor every numeric claim on a primary source. Press release, 8-K, real OHLCV are primary. Community topic titles, truncated news headlines, and aggregated provider fields are leads, not sources. Verify before quoting.

When to use

  • User names a ticker they don't know and asks for orientation
  • Request combines two or more of {business, fundamentals, technicals, catalyst, peers}
  • "盘前 / 今日为什么涨跌" question — runs lenses 1, 4, partially 6
  • Request to "explain how X relates to other listed companies" — emphasizes lens 5

If the user wants only one lens (e.g., just real-time price), do NOT load this skill — go directly to the corresponding longbridge-* sub-skill.

The six lenses

Lenses 1–5 are independent. Dispatch their Longbridge calls in parallel. Lens 6 (audit) runs last, against all collected data.

#LensSub-skillsOutput anchor
1Business identitylongbridge-company-profile + longbridge-business-query1-line "what" + segment revenue mix table
2Fundamentalslongbridge-fundamentalQuarterly revenue series (YoY and QoQ) + OpInc trajectory + reconciled EPS
3Technicalslongbridge-technical + longbridge-klineLast-5-day OHLCV + week summary + pivot S/R + indicator vote + ATR14
4Catalystslongbridge-news + trump-truth-monitor (if policy-exposed)Classified news/filings + community sentiment skew + pre-market range + Trump-policy hits
5Supply chain & peerslongbridge-supply-chain + longbridge-competitive-analysisUpstream → company → downstream flow + peer valuation table + paired-trade logic
6Narrative audit(this skill, see below)Reconciliation: official vs community, GAAP vs non-GAAP, YoY vs QoQ, mix vs aggregate

Mandatory verification — the recurring traps

These six errors occur repeatedly when synthesizing a stock brief. The skill exists primarily to prevent them. Self-audit before sending output:

Trap 1 — Community topic ≠ company guidance

Longbridge news <SYMBOL> returns mixed feeds. Items with URL pattern longbridge.com/topics/* are user-posted community threads, not company-issued. Any "FY guide $X" figure sourced from a community-topic title must be verified against the actual press release (longbridge.com/news/* with reputable source_name, or the SEC 8-K) before quoting. Never restate a community-topic number as guidance.

Trap 2 — Truncated headline ≠ official statement

News titles end in "…" when truncated by the feed. Pull the article body (<url>.md variant on Longbridge) or the 8-K text before quoting a CEO percentage. If you can't pull the body, attribute as "per news headline — unverified".

Trap 3 — Longbridge financial-report --kind IS EPS field = GAAP

US companies report non-GAAP EPS on earnings calls; analyst consensus is also non-GAAP. The Longbridge IS EPS field is GAAP diluted. If the value looks absurd (e.g., 0.04 when consensus was 0.80), it's GAAP, not a beat/miss. Always state which basis you're quoting. For non-GAAP, pull from news / press release excerpt.

Trap 4 — YoY % deceleration ≠ business slowdown

Compute QoQ alongside YoY every time. If the base year was itself accelerating off a low, YoY % naturally compresses even as absolute revenue accelerates. Look at the sequential QoQ trend before claiming "growth is slowing". Show implied forward YoY from next-quarter guidance — it often reveals a V-shape that aggregate YoY hides.

Trap 5 — Mix shift hides under aggregate growth

If the company has one hyper-growth segment and one declining segment (classic: AI silicon + legacy storage), aggregate growth understates the hot segment. Break out by segment when the disclosure allows; if not, estimate from CEO commentary and flag the assumption.

Trap 6 — Pre-market wide range is signal

A pre-market range > 1× ATR14 (e.g., $188 – $211 vs ATR14 $12) means institutions and retail are in heavy disagreement. Note explicitly. The open print and the first-hour hold-of-pivot is the resolution.

Output template

# {Symbol} — {company name} 略览

## 一、Business identity
1-sentence "what" + revenue mix table (segment | % | content | cycle phase)

## 二、Fundamentals
- Quarterly revenue table: period | rev | YoY | QoQ
- OpInc trajectory (sign and direction matter more than absolute)
- EPS: GAAP from provider AND non-GAAP from press release (label both)
- Latest-quarter guidance vs prior guidance — explicit delta

## 三、Technicals
- Last 5 sessions OHLCV table + week summary (open/close/high/low/%)
- 52w range, last close, ATR14
- Pivot S/R from last 5d (P, R1-3, S1-3)
- Indicator vote table (MACD, RSI, KDJ, BB, EMA50/200, ADX, OBV)
- Composite verdict (buy / sell / neutral)

## 四、Catalysts (now)
- Classified news (catalyst / regulatory / strategic / opinion / filing / community)
- Pre-market last + range (flag if > 1× ATR)
- Sentiment skew (coarse %, no individual quotes)

## 五、Supply chain & peers
- Upstream (foundry / IP / EDA / equipment) — who, why dependent
- Downstream (customers / OEMs / end users) — concentration risk
- Horizontal (same-tier competitors / substitutes) — peer valuation table
- Paired-trade logic — which other tickers move together / inversely

## 六、Verdict
- Bull thesis (anchored on numbers)
- Bear / risk (anchored on numbers)
- Valuation anchor (which peer's multiple this should trade against, why)
- Key tell to watch (e.g., does first-hour price hold pivot)

⚠️ For reference only. Not investment advice.

Anti-pattern table

ExcuseReality
"The community post said the FY28 guide is $X"Community ≠ company. Find the press release.
"The CEO said +40% YoY" (from a "…"-truncated headline)Pull the article body. Attribute as unverified if you can't.
"EPS is 0.04, missed badly" (from the IS feed)That's GAAP. Non-GAAP is what consensus measures.
"YoY dropped from 63% to 22%, growth is slowing"Check QoQ. Check the base. Check next quarter's implied YoY.
"Revenue is +28%, no big deal"If 75% of revenue is hyper-growth segment masking 25% in decline, the hot segment is +60%+.
"Pre-market is volatile, ignore"A pre-market range > 1× ATR is institutional disagreement — a signal. Note it.

Red flags — STOP and reverify

  • About to quote a number that came from a topics/* URL
  • About to quote a CEO statement from a title ending in "…"
  • About to call an earnings result "miss / beat" without saying GAAP or non-GAAP
  • About to use YoY % alone to describe momentum
  • About to give a verdict without ATR + S/R for the technical lens
  • About to skip the supply-chain lens because "it's just a chip company"

Concurrency

Lenses 1–5 each call multiple Longbridge endpoints. Within a single user turn, batch every independent CLI call in one parallel tool block. A typical first turn dispatches 8–12 longbridge calls in parallel, then runs the technical Python computation in a follow-up turn.

Related skills

Required (load on demand):

  • longbridge-company-profile, longbridge-business-query
  • longbridge-fundamental
  • longbridge-technical, longbridge-kline
  • longbridge-news
  • longbridge-supply-chain, longbridge-competitive-analysis

Optional (deeper drilldown):

  • longbridge-peer-comparison — pure peer-matrix
  • longbridge-valuation — historical PE/PB percentile
  • longbridge-earnings — earnings-day specific
  • longbridge-capital-flow — intraday capital direction
  • trump-truth-monitor — Trump policy catalyst (run for lens 4 when the symbol has policy exposure: semis / China ADR / auto / energy / defense / bank)

For session-long multi-symbol tracking after the deep dive, route to market-session-tracker.

Frequently asked questions

What does the Stock Deep Dive AI skill do?

Use when the user asks for an end-to-end orientation on a listed company they don't yet understand, especially when the request combines two or more dimensions in one ask. Triggers on "X 是干什么的", "帮我了解 X", "X 主营 + 同行", "盘前为什么涨", "本周趋势 + 阻力支撑", "X 和其他公司的关系", "first time looking at X", "full brief on X". Skip when the user wants only a single lens — use the targeted Longbridge sub-skill instead.

Why use Stock Deep Dive on TypingMind?

Because you install it once and use it with any model. Stock Deep Dive is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Stock Deep Dive in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kansoku-trade/kansoku/tree/main/.claude/skills/stock-deep-dive. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Stock Deep Dive?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Stock Deep Dive?

As many as you like. As long as a model supports skills, you can use Stock Deep Dive with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Stock Deep Dive AI skill free?

It is published on GitHub by kansoku-trade. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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