Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis…

Apache-2.0Auto-check passedProduct & Project Management

Install Business Model

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill business-model -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence business-model --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/agent-plugins/agentii-equity-agent/skills/agentii/business-model .claude/skills/business-model && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
business-model
GitHub stars
207
Token cost
~2.8k tokens
SKILL.md length
1,088 words
Files
8 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis…

  • Works in 5 steps: Retrieval Scope → Retrieval Strategy → Temporal Scope → …
  • Tasks that involve Product strategy
  • SKILL.md covers Preflight, Triggers, Defaults and Production Grounding, plus 9 more sections
  • Reaches agentii.ai

What it does

Business Model is an agent skill from agentii-ai/agentii-investment-intelligence. Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis, revenue model identification, market sizing TAM SAM SOM, competitive positioning, business unit performance, management team & leadership analysis, what does the company sell, how does the company go to market, business model type platform service product, channel mix direct vs indirect, revenue concentration risk, CEO…

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/knowledge-frameworks.md`, `references/methodology.md` and `references/moat-methodology.md`).

It sits in Product & Project Management, covering Product strategy, Market sizing and Go-to-market strategy. The repository describes itself as: Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Product strategy
  • Tasks that involve Market sizing
  • Tasks that involve Go-to-market strategy

Example prompts

  • “/business-model”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Retrieval Scope
  2. Retrieval Strategy
  3. Temporal Scope
  4. Tool Allowlist
  5. Protocol

What it can do on your machine

Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • agentii.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Business Model loads about 2.8k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 142 tokens; SKILL.md has 1,088 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~142
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 1,088 words, ~2,760 tokens.

Download SKILL.mdSave it as .claude/skills/business-model/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
business-model
description
Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis, revenue model identification, market sizing TAM SAM SOM, competitive positioning, business unit performance, management team & leadership analysis, what does the company sell, how does the company go to market, business model type platform service product, channel mix direct vs indirect, revenue concentration risk, CEO CFO executive backgrounds and changes
multi_ticker_semantics
target_with_optional_peers
essentials_modes
business-model-classification, distribution-channel-analysis, revenue-composition-and-concentration
temporal_scope.default_quarters
4
temporal_scope.max_quarters
8
temporal_scope.description
Structural analysis over a trailing 4 fiscal quarters (latest 10-K + trailing 10-Qs); max 8 for channel-mix or management-evolution windows. A single-quarter…
retrieval_scope
unstructured_document_search
min_tool_diversity
9
<!-- analog: equity-research-core/business-model -->

Preflight

Run canonical pre-flight per contracts/preflight.md.

Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

Triggers

  • analyze the business model of {ticker}
  • run business model analysis on {ticker}
  • decompose the business model of {ticker}
  • what does {ticker} sell and how does it make money
  • classify the business model type of {ticker}
  • analyze {ticker} product offerings and distribution channels
  • assess {ticker} revenue composition and concentration risk
  • evaluate {ticker} TAM SAM SOM and market positioning
  • analyze {ticker} management team and leadership changes
  • review {ticker} go-to-market strategy
  • breakdown {ticker} customer segments and distribution model
  • structural analysis of {ticker}
  • business unit performance analysis for {ticker}
  • competitive positioning of {ticker}

Defaults

ParameterDefaultNotes
lookback_quarters4Trailing 4 fiscal quarters (latest 10-K + trailing 10-Qs); a single-quarter snapshot is INSUFFICIENT for business-model classification
include_management_changestrueWhether to surface leadership-change analysis (mode 1_5)
include_market_sizingtrueWhether to surface TAM/SAM/SOM (mode 1_4)
peer_setnoneBusiness-model analysis is single-issuer by default; peers are added by /agentii:competitive

Production Grounding

Production data-plane grounding (scale, locators) is in references/methodology.md.

Data Source Priority (mandatory order)

  1. XBRL FIRST (grounding truth) — search_xbrl_facts with the detailed/segment view for revenue & margins broken down by product line, segment, geography, and distribution channel (concepts Revenues, GrossProfit, OperatingIncomeLoss, SegmentReportingInformation). Retrieve XBRL BEFORE any document discovery.
  2. SEC filings — search_documents / search_sec_filings for the 10-K (annual, richest business overview), trailing 10-Q, and 20-F for foreign issuers → read_source_pages enrichment.
  3. Web search = LAST RESORT — only when SEC/XBRL coverage is genuinely insufficient (e.g., third-party TAM estimates, very recent unfiled events), and it MUST be flagged in Coverage Gaps. Web search is NOT an MCP tool and is never a substitute for filings.

Methodology

1. Retrieval Scope

This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings and earnings call transcripts). The three-layer agent-use-ready retrieval protocol applies (Layer 1 → Layer 2 → Layer 3). For foreign issuers, use 20-F (annual) and 6-K (material events) instead of 10-K and 8-K respectively.

2. Retrieval Strategy

See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.

Read before you quote. A page's description is platform-generated — it is never the issuer's words and must never be quoted as the filing's. When a description identifies a relevant page, read_source_pages that page and quote its page_content. The description is a pointer, not a source: a citation written from one is the fabricated quote this skill's output standard exists to prevent (contracts/retrieval.md § Three-Layer Document Protocol).

3. Temporal Scope

Default: 4 fiscal quarters (max 8). A single-quarter snapshot is INSUFFICIENT for business-model classification — use the latest 10-K (annual) plus trailing 10-Qs. Extend the window when explicitly tracking channel-mix evolution (mode 1_2 default 12 quarters) or management changes (mode 1_5 default 4 quarters).

4. Tool Allowlist

See frontmatter allowed_tools.

  • search_companies, get_company_profile — issuer resolution and sector classification.
  • search_xbrl_facts, list_xbrl_concepts, get_company_financials — segment-level P&L and revenue concentration metrics.
  • search_documents, search_sec_filings — Layer 1 document discovery (with secondary_labels filter).
  • read_source_outline, read_source_pages, search_keyword_in_source — Layer 2/3 deep read for business-overview pages.
  • get_company_fiscal_calendar, get_ticker_coverage — pre-flight (mandatory first step).
5. Protocol

Step-by-step execution detail is in references/methodology.md.

Moat Assessment: When evaluating competitive advantage durability, apply the Sustainable Value Creation framework in references/moat-methodology.md. Quantify the ROIC−WACC spread magnitude, calibrate sustainability using sector-level ROIC autocorrelation data (Consumer Staples r=0.46 → Energy r=0.15), classify industry structure (Fragmented/Oligopoly/Dominant/Network/Commodity), and apply the 67-item Moat Checklist. High current ROIC in a rapid-mean-reversion industry is not a moat.

Modes (5 — structural equity analysis)

This skill delivers analyst-grade output via 5 addressable mode(s); invoke with --mode=<slug> / --modes=<slug1>,<slug2> / --mode=all (see Mode syntax. The default invocation (no flag) runs the essentials_modes subset declared in this skill's frontmatter.

Analyst Modes

This skill exposes addressable analysis modes (--mode=<slug> / --modes=<s1>,<s2> / --mode=all; see Mode syntax). The full mode definitions and their output templates live in references/modes.md. The default invocation runs the essentials subset.

Tool Fallbacks

Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.

Show full SKILL.md (437 more words)Show less

Output File

Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_business-model_{affix}.md.

Output Directory Rule: write to {ticker}/ (e.g. NVDA/) — NEVER {ticker}-recent-quarter/ or any dimension-suffixed variant. The directory is the bare uppercase ticker; the skill name appears only in the filename, never the directory.

Output Structure

The deliverable is a structured markdown report written to the path in ## Output File. Full section-by-section template (headings, tables, and field definitions) lives in references/output-structure.md. Required elements:

  1. Executive Summary — headline conclusions (≤200 words).
  2. Core analysis sections — per this skill's methodology and analyst modes.
  3. Data classification — tag findings [FACT] / [DEDUCTED] / [VIEW] per contracts/snapshot-synthesis.md.
  4. Coverage Gaps & Citations — coverage gaps are required; inline /v/ citations are the citation surface (immediately after each fact). A bottom roll-up index is optional, and where kept it must not repeat a link the prose already carries.
  5. Output frontmatter — emit the FR-090 structured block per contracts/output-frontmatter-schema.md.

Citations & memory: follow contracts/citation-and-memory.md — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link; citations belong inline, a bottom roll-up index is optional and never a repeat of a link already given; the closing TUI reply includes a compact Key Citations list (headline 5–10 facts) of clickable /v/ URLs; and append the run to agentii.md per contracts/agentii-md-schema.md.

Memory & Snapshot

  • Memory load (pre-flight): load prior workspace context for the ticker before retrieval — see contracts/memory-load.md.
  • Structured output frontmatter: emit the FR-090 block (key_metrics, conclusions, facts_count, deducted_count, views_count, citation_count) per contracts/output-frontmatter-schema.md.
  • Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as [FACT]/[DEDUCTED]/[VIEW] — see contracts/snapshot-synthesis.md.
  • Session archival: record the run under sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.

Final Summary (TUI)

End the closing chat reply with the summary shape in contracts/citation-and-memory.md — Citation Placement Policy item 3: title · key conclusions · key metrics · Executive Summary · Key Citations (the headline 5–10 facts, each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link), so the user can cmd+click straight to the exact SEC page without opening the file.

Error Handling

Failure ModeDetectionActionUser-Facing Message
Missing dataData API returns empty result setWiden date range and retry once"No data available for {ticker} in requested window."
Partial dataData API returns <80% expected recordsProceed with coverage gaps section"Analysis based on partial data; see Coverage Gaps section."
Foreign issuerform_type=["10-K"] emptyRetry with form_type=["20-F"] for annual + form_type=["6-K"] for material events"Foreign issuer; using 20-F + 6-K instead of 10-K + 8-K."
Insufficient historyTicker <3 years on public marketsDowngrade to limited-history profile (skip channel-mix evolution)"Limited historical data; mode 1_2 channel-mix trend skipped."
MCP unreachablePreflight probe failsHalt with actionable error"agentii data plane unreachable; check connection."

© agentii-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in plugins/agent-plugins/agentii-equity-agent/skills/agentii/business-model of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/knowledge-frameworks.md
  • references/methodology.md
  • references/moat-methodology.md
  • references/modes.md
  • references/output-structure.md
  • references/tool-fallbacks.md
  • references/wsp-methodology.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Business Model next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Business Model this skillagentii-ai/agentii-investment-intelligence207—~2.8kAutomated safety check: PassApache-2.0
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Product Strategistnicepkg/auto-company1951 repos~2.4kAutomated safety check: PassNone
Organic Growth Path Advisordeanpeters/Product-Manager-Skills7.2k2 repos~5.2kAutomated safety check: PassCustom licence
PlaidBuildGreatProducts/plaid218—~1.6kAutomated safety check: PassMIT
Management ConsultantDogInfantry/claude-skill-management-consultant-B1136—~14kAutomated safety check: PassCustom licence

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Questions about Business Model

What does Business Model do?

Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis…. Business Model is an agent skill from agentii-ai/agentii-investment-intelligence.

When should I use Business Model?

Business Model fits situations like: tasks that involve Product strategy; tasks that involve Market sizing; tasks that involve Go-to-market strategy.

How do I install Business Model in Claude Code?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill business-model -a claude-code`. Or copy the skill folder (plugins/agent-plugins/agentii-equity-agent/skills/agentii/business-model in agentii-ai/agentii-investment-intelligence) into .claude/skills/business-model in your project. Claude Code loads it when a task matches its description.

How do I install Business Model in Codex?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill business-model -a codex`. Or copy the skill folder (plugins/agent-plugins/agentii-equity-agent/skills/agentii/business-model in agentii-ai/agentii-investment-intelligence) into .agents/skills/business-model in your project. Codex loads it when a task matches its description.

Can I use Business Model in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentii-ai/agentii-investment-intelligence --skill business-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/business-model, .gemini/skills/business-model, .github/skills/business-model and .opencode/skills/business-model in your project.

What does Business Model need to run?

SKILL.md names no scripts, command-line tools or credentials: Business Model is instructions for the agent only.

Does Business Model access the network?

SKILL.md names 1 domain. In commands or code: agentii.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Business Model safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Business Model use?

Business Model is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Business Model use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.9k tokens, read only when the agent opens those files.

What are the alternatives to Business Model?

Skills that share tags, products or a category with Business Model: Startup Design (ferdinandobons/startup-skill, 1.2k stars), Product Strategist (nicepkg/auto-company, 195 stars), Organic Growth Path Advisor (deanpeters/Product-Manager-Skills, 7.2k stars) and Plaid (BuildGreatProducts/plaid, 218 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Business Model?

agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.

Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.