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10k Digest

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yennanliu
10k-digest

Deep-read a 10-K annual report and output a structured markdown digest — abstract, section summaries, key metrics, and sourced references. Output in English or Traditional Chinese.

Overview

Publisheryennanliu
RepositoryInvestSkill
Skill name10k-digest
Stars
254
Forks
61
Bundled files
Instructions only
LicenseMIT
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 yennanliu on GitHub. Read the source before you install it.

Installation

Install the 10k Digest 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/yennanliu/InvestSkill/tree/main/plugins/us-stock-analysis/skills/10k-digest
  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/yennanliu/InvestSkill.git /tmp/InvestSkill
mkdir -p .claude/skills
cp -r /tmp/InvestSkill/plugins/us-stock-analysis/skills/10k-digest .claude/skills/10k-digest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 10k Digest 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 10k Digest 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 10k Digest 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.

10-K Report Digest

⚠️ Data Verification — Do This Before Any Analysis

Before running the digest, confirm the filing details:

  1. Identify the filing — confirm ticker, fiscal year-end, and exact 10-K filing date from SEC EDGAR.
  2. State your source — note where the document came from (e.g., "SEC EDGAR, FY2024 10-K filed 2025-02-05") at the top of the output.
  3. Flag incomplete data — if only partial sections are available, list what is missing before proceeding.

⚠️ Source unavailable. If the full 10-K cannot be retrieved, display this warning and proceed only with the sections provided.


📋 Data & Sources Header — Open Every Output With It

The first thing in the output is this provenance block, filled in — never left as placeholders. It is the standard documented on the Data & Accuracy page and the first thing result-validator looks for:

Data & Sources
  As of:      <date the figures represent, e.g. 2026-06-30>
  Source:     <primary docs — SEC EDGAR 10-K/10-Q, company IR, FRED, exchange data …>
  Retrieval:  <pasted by user | web/tool retrieval | model memory>
  Confidence: <HIGH | MEDIUM | LOW>
  • Retrieval: model memory must be paired with Confidence: LOW — memory is a placeholder until confirmed against a primary source.
  • Mixed sources: list each with its own as-of date rather than blending them.
  • Sources disagree on the same figure (a closing price, a deal term): prefer the primary source (SEC filing, company release, exchange data) over an aggregator, then the most recent dated one. Show both values with their sources and dates, say which you used and why, and never average them.
  • Data the user pasted is reported as pasted by user; do not upgrade its confidence beyond what the user's own source supports.

Produce a clean, structured markdown document that distills a company's 10-K annual report into an abstract, per-section summaries, a digest of key metrics, and full source references. Designed for quick comprehension — not trading signals. Output language is selectable: English or Traditional Chinese (繁體中文).

🔎 Retrieving the Filing — the Keyless EDGAR Path

This skill fetches nothing by itself. When the user gives only a ticker, obtain the 10-K in one of three ways and record which one in the Data & Sources header:

A. The host can fetch URLs → Retrieval: web/tool retrieval. Every step is free and needs no API key:

  1. Ticker → CIK — https://www.sec.gov/files/company_tickers.json: find the entry whose ticker matches (write BRK-B for BRK.B) and zero-pad its cik_str to 10 digits.
  2. Filings index — https://data.sec.gov/submissions/CIK##########.json: inside filings.recent the arrays form, filingDate, reportDate, accessionNumber and primaryDocument are aligned by index. Take the newest row whose form is 10-K (foreign private issuers file 20-F instead; a 10-K/A is an amendment). The top-level fiscalYearEnd is MMDD.
  3. The document — https://www.sec.gov/Archives/edgar/data/<CIK without leading zeros>/<accessionNumber without dashes>/<primaryDocument>: the complete filing as HTML (inline XBRL). The filing's index page is the same folder plus <accessionNumber>-index.htm; cite that URL and the accession number in the References.
  4. Structured statement data (optional) — https://data.sec.gov/api/xbrl/companyfacts/CIK##########.json: every US-GAAP fact the company has tagged, by concept and period. Use it to confirm the figures read from Item 8.
  5. Full-text search (optional) — https://www.sec.gov/edgar/search/#/q=%22<phrase>%22&forms=10-K when a filing has to be located by phrase rather than ticker.

Send a User-Agent header that identifies the requester (the SEC requires it, e.g. Name email@example.com) and stay under 10 requests per second. Never substitute a summary site for the filing itself.

B. The host cannot fetch → Retrieval: pasted by user. Ask the user to paste the sections needed — or, if they have the InvestSkill repository, to run

node scripts/fetch-edgar.js <TICKER> --form 10-K        # → data/filings/<TICKER>/*.txt + .json (accession, dates, URL)
node scripts/fetch-fundamentals.js <TICKER>             # → data/fixtures/<TICKER>.md — reconciled statements from the XBRL facts

and paste the result. Both helpers are optional, keyless, and live outside the plugin.

C. Neither → show the ⚠️ Source unavailable warning, set Retrieval: model memory and Confidence: LOW, and digest only what the user provided.


How to Use

# Analyze by ticker (retrieves the latest 10-K via the EDGAR path above, or asks you to paste it)
/10k-digest AAPL

# Paste 10-K text directly
/10k-digest [paste 10-K sections here]

# Specify fiscal year
/10k-digest MSFT FY2024

# Output in Traditional Chinese
/10k-digest NVDA --lang zh-TW

# Save output to file
/10k-digest GOOGL --output googl-10k-digest.md

Output Document Structure

The skill produces a single markdown document with the following sections in order.


1. Cover Block

# [Company Name] ([TICKER]) — 10-K Digest
**Fiscal Year:** [FY20XX ending MM/DD/YYYY]
**Filed:** [Filing date]
**Source:** SEC EDGAR — [Direct URL to filing]
**Prepared:** [Today's date]
**Language:** English | 繁體中文

2. Abstract

A 3–5 sentence executive summary of the entire 10-K. Cover:

  • What the company does (core business in one sentence)
  • Year-over-year financial performance headline (revenue, profit, FCF)
  • The single most important strategic development disclosed in this filing
  • The most material risk disclosed
  • Overall filing tone (transparent / cautious / optimistic)

3. Section Summaries

Summarize each major 10-K section. For each section, write 2–4 sentences capturing the substance — not just restating headings.

3.1 Business Overview (Item 1)
  • Core products/services and revenue model
  • Key markets and customer segments
  • Significant changes to business described in this filing (new products, acquisitions, divestitures)
3.2 Risk Factors (Item 1A)
  • Total number of risk factors disclosed
  • Top 3 risks by disclosure prominence (listed first, given most space, or new this year)
  • Any risks added or removed vs. prior filing (state "N/A if prior not available")
  • One-line assessment: are risks standard boilerplate or specific and material?
3.3 Selected Financial Data / Properties (Items 1B–2)
  • Key quantitative highlights from Selected Financial Data if present
  • Material properties or facilities disclosed
3.4 Management's Discussion & Analysis — MD&A (Item 7)
  • Revenue: total and YoY growth; organic vs. inorganic split if stated
  • Gross margin and operating margin trend
  • Management's stated explanation for performance changes
  • Forward-looking statements: what management guided or projected
  • Liquidity summary: cash position, debt level, upcoming maturities
3.5 Financial Statements (Items 8)
  • Revenue, net income, EPS (GAAP) — current year vs. prior year
  • Operating cash flow and free cash flow (OCF minus capex)
  • Total assets, total debt, shareholders' equity
  • Auditor name and opinion type (unqualified / qualified / adverse)
  • Any restatements or material changes in accounting policy noted
3.6 Quantitative Disclosures about Market Risk (Item 7A)
  • Primary market risks disclosed (interest rate, FX, commodity)
  • Sensitivity disclosures if provided (e.g., "1% rate rise = $X impact")
3.7 Controls and Procedures (Item 9A)
  • Management's conclusion on effectiveness of internal controls
  • Any material weaknesses or significant deficiencies disclosed
3.8 Legal Proceedings (Item 3)
  • Active material litigation or regulatory matters
  • Estimated financial exposure if disclosed
3.9 Executive Compensation & Governance (Items 10–13, from Proxy if incorporated)
  • CEO/CFO compensation summary
  • Board composition notes (independence, tenure)
  • Any significant governance changes

4. Key Metrics Table

Provide a concise metrics table drawn directly from the financial statements. Use exact figures from the filing; do not estimate.

| Metric                    | Current FY      | Prior FY        | YoY Change |
|---------------------------|-----------------|-----------------|------------|
| Revenue                   | $X.XX B         | $X.XX B         | +X.X%      |
| Gross Profit              | $X.XX B         | $X.XX B         | +X.X%      |
| Gross Margin %            | XX.X%           | XX.X%           | +X bps     |
| Operating Income          | $X.XX B         | $X.XX B         |            |
| Operating Margin %        | XX.X%           | XX.X%           |            |
| Net Income (GAAP)         | $X.XX B         | $X.XX B         |            |
| EPS Diluted (GAAP)        | $X.XX           | $X.XX           |            |
| Operating Cash Flow       | $X.XX B         | $X.XX B         |            |
| Capital Expenditures      | $X.XX B         | $X.XX B         |            |
| Free Cash Flow            | $X.XX B         | $X.XX B         |            |
| Cash & Equivalents        | $X.XX B         | $X.XX B         |            |
| Total Debt                | $X.XX B         | $X.XX B         |            |
| Net Debt / (Net Cash)     | $X.XX B         | $X.XX B         |            |
| Shares Outstanding (dil.) | X.XX B          | X.XX B          |            |

Note below the table: data source (filing section and page number if available).


5. Highlights & Concerns

Two short lists that give the reader the "so what" without leaving the digest. Draw every item directly from the filing and cite the source Item.

Highlights — up to 5 of the strongest positives disclosed this year (e.g., record revenue, margin expansion, new products/segments, strong FCF conversion, new buyback authorization, market-share gains). Format: - **[Headline]** — [one sentence] *(Item X)*

Concerns — up to 5 of the most material negatives or warning signs (e.g., decelerating growth, margin compression, rising leverage, customer/supplier concentration, new risk factors, active litigation, going-concern language). Format: - **[Headline]** — [one sentence] *(Item X)*


6. Management Outlook & Forward Guidance

Capture every forward-looking commitment made in the filing. Present as a table.

| Guidance Item              | What Management Said                | Time Horizon | Source     |
|----------------------------|-------------------------------------|--------------|------------|
| Revenue growth             | [target / range / directional]      | [FY / multi] | Item 7     |
| Margin target              | [gross / operating target]          | [horizon]    | Item 7     |
| Capex / capacity           | [planned spend or expansion]        | [horizon]    | Item 7     |
| Capital allocation         | [dividend / buyback / debt / M&A]   | [horizon]    | Item 7/8   |
| Strategic priorities       | [product roadmap, new markets]      | [horizon]    | Item 1/7   |

Only include rows the filing actually addresses. If the 10-K gives no explicit guidance (common — 10-Ks are backward-looking), state that and summarize any qualitative forward statements instead.


7. Prior-Year Promise Tracker

An accountability audit: take the forward-looking statements, targets, and stated priorities from last year's 10-K (Item 7 MD&A) and score whether they materialized in this year's results. This is the single most differentiating part of the digest — it measures management credibility over time.

| Prior-Year Commitment (FY[N-1] 10-K)   | FY[N] Actual Result          | Verdict     | Notes            |
|-----------------------------------------|------------------------------|-------------|------------------|
| [what management said they would do]    | [what actually happened]     | ✅ Delivered | [brief context]  |
| [e.g., "expand operating margin"]       | [e.g., "margin +120 bps"]    | 🟡 Partial  | [brief context]  |
| [e.g., "launch product X in H2"]        | [e.g., "slipped to next FY"] | ❌ Missed    | [brief context]  |

Verdict legend: ✅ Delivered · 🟡 Partial · ❌ Missed · ⏳ Too early to judge.

Close with a one-line Management Credibility read: e.g., "4/5 prior commitments delivered — high follow-through." If the prior-year 10-K is unavailable, state N/A — prior filing not retrieved and skip the table.


8. Bull vs. Bear Synthesis

A lightweight face-off built strictly from evidence in this filing — not a full valuation call (defer to bear-case, stock-eval, and stock-valuation for that).

Bull case — 3–4 strongest points from this filing supporting the stock.

Bear case — 3–4 strongest points from this filing arguing against it.

Net read — one sentence weighing the two, consistent with the Investment Signal below.


9. Notable Disclosures

Bullet list of up to 8 items that are worth investor attention but don't fit neatly into section summaries:

  • New segment or business unit disclosures
  • Changes in accounting estimates or policies
  • Related party transactions
  • Auditor changes
  • Going concern language (if any)
  • New share repurchase authorizations or dividend changes
  • Material acquisitions or divestitures announced
  • Specific named customers or suppliers with concentration risk

10. Source References

List all sources cited in this digest. Format:

## References

1. **SEC EDGAR Filing** — [Company] 10-K, FY[XXXX]
   URL: https://www.sec.gov/cgi-bin/browse-edgar?...
   Filed: [Date] | Accession No.: [XXXXXXXXXX-XX-XXXXXX]

2. **Item 1 — Business** (pp. X–X of filing)
3. **Item 1A — Risk Factors** (pp. X–X of filing)
4. **Item 7 — MD&A** (pp. X–X of filing)
5. **Item 8 — Financial Statements** (pp. X–X of filing)
6. **Item 9A — Controls and Procedures** (pp. X–X of filing)
7. **Exhibit 13 / Annual Report to Shareholders** (if incorporated by reference)
8. [Any additional sources used, e.g. earnings press release, investor presentation]

If page numbers are unavailable (e.g., pasted text), reference by Item number and section heading.


Language Mode

When --lang zh-TW is specified, output the entire document in Traditional Chinese (繁體中文), including:

  • All section headings translated
  • All narrative summaries written in Traditional Chinese
  • All tables with Chinese column headers
  • Cover block language field: 語言:繁體中文
  • Keep ticker symbols, financial figures, and SEC item numbers in their original form

Suggested Traditional Chinese headings for the interpretation sections: 亮點與隱憂 (Highlights & Concerns), 管理層展望 (Management Outlook & Forward Guidance), 上年度承諾兌現 (Prior-Year Promise Tracker), 多空對決 (Bull vs. Bear Synthesis).

English mode is the default when no --lang flag is given.


File Output

When --output <filename> is specified:

  • Save the digest as a markdown file at the specified path
  • If no path separator is present, save in the current directory
  • Confirm the file path after saving: ✓ Digest saved to: <path>
  • Default filename if --output flag is present without a name: <TICKER>-10k-digest.md

Thesis Invalidation

After delivering the digest, note what would make this document stale:

Re-run this digest when:

  • Company files next 10-K or 10-K/A amendment
  • Material 8-K filed disclosing a restatement or auditor change
  • 12 months have elapsed since the filing date
╔══════════════════════════════════════════════╗
║              INVESTMENT SIGNAL               ║
╠══════════════════════════════════════════════╣
║ Signal:      BULLISH / NEUTRAL / BEARISH     ║
║ Confidence:  HIGH / MEDIUM / LOW             ║
║ Horizon:     SHORT / MEDIUM / LONG-TERM      ║
║ Score:       X.X / 10                        ║
╠══════════════════════════════════════════════╣
║ Action:      BUY / HOLD / SELL               ║
║ Conviction:  STRONG / MODERATE / WEAK        ║
╚══════════════════════════════════════════════╝

Score Guide: 8.0–10.0 Strongly Bullish | 6.0–7.9 Moderately Bullish | 4.0–5.9 Neutral | 2.0–3.9 Moderately Bearish | 0.0–1.9 Strongly Bearish Confidence: HIGH (strong data, clear signals) | MEDIUM (mixed signals) | LOW (limited data, conflicting signals) Horizon: SHORT-TERM (1 week–3 months) | MEDIUM-TERM (3 months–1 year) | LONG-TERM (1+ years)

Disclaimer: Educational analysis only. Not financial advice.

Frequently asked questions

What does the 10k Digest AI skill do?

Deep-read a 10-K annual report and output a structured markdown digest — abstract, section summaries, key metrics, and sourced references. Output in English or Traditional Chinese.

Why use 10k Digest on TypingMind?

Because you install it once and use it with any model. 10k Digest 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 10k Digest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yennanliu/InvestSkill/tree/main/plugins/us-stock-analysis/skills/10k-digest. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 10k Digest?

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 10k Digest?

As many as you like. As long as a model supports skills, you can use 10k Digest with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 10k Digest AI skill free?

Yes. It is published on GitHub by yennanliu under the MIT license. 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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