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Sotp Valuation

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agentii-ai
sotp-valuation

Sum of the Parts valuation, segment-based valuation, conglomerate valuation, business segment analysis, breakup value, segment sum valuation, parts worth more than whole, hidden asset value

Overview

Publisheragentii-ai
Repositoryagentii-investment-intelligence
Skill namesotp-valuation
Stars
207
Forks
16
Bundled files
7
LicenseApache-2.0
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by agentii-ai on GitHub. Read the source before you install it.

Installation

Install the Sotp Valuation 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/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/sotp-valuation
  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/agentii-ai/agentii-investment-intelligence.git /tmp/agentii-investment-intelligence
mkdir -p .claude/skills
cp -r /tmp/agentii-investment-intelligence/plugins/vertical-plugins/models-and-pitches/skills/agentii/sotp-valuation .claude/skills/sotp-valuation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sotp Valuation 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 Sotp Valuation 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 Sotp Valuation 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.

Sum of the Parts (SOTP) Valuation

Values each business segment independently and sums for total enterprise value. Essential for conglomerates (GE, MMM, HON), multi-segment tech (AMZN: AWS + Retail + Ads, GOOG: Search + Cloud + YouTube), and holding companies. SOTP often reveals "hidden value" when the market undervalues individual segments.

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

  • sum of the parts valuation {ticker}
  • SOTP analysis {ticker}
  • segment-based valuation {ticker}
  • breakup value {ticker}
  • conglomerate valuation {ticker}
  • parts worth more than whole {ticker}
  • segment sum of parts {ticker}
  • business segment valuation {ticker}
  • hidden asset value {ticker}
  • SOTP {ticker}

Defaults

ParameterDefaultNotes
segment_discoverystatement_treeUse get_statement_structure for segment identification
peer_multiplessectorApply sector-appropriate multiples per segment
include_corporatetrueSubtract corporate overhead, net debt

Methodology

Retrieval Scope

unstructured_document_search — SOTP requires segment financials from XBRL (structured) AND segment narrative/business description from MD&A (unstructured) for appropriate multiple selection.

Retrieval Strategy

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

Temporal Scope

Default lookback: 4 fiscal quarter(s); maximum: 12. The default balances recency against the trend window this analysis requires.

Tool Allowlist

Per frontmatter allowed_tools:

  • search_xbrl_facts — primary structured financial facts (is_primary default)
  • search_companies — ticker resolution + company context (entity-alias fuzzy match)
  • get_realtime_quote — latest market price for valuation cross-checks
  • search_documents — Layer 1 document discovery (page-level silver records)
  • read_source_outline — Layer 2 lightweight page map (description + keywords)
  • read_source_deep_outline — Layer 2.5a deep page map (table_titles/drivers/metrics)
  • read_source_pages — Layer 3 deep read of selected pages with table markers
  • get_statement_structure — XBRL presentation tree (concept hierarchy)

Protocol

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

Deliverable Chain

Inputs → Build → Validate → Output → Next

  1. Inputs: resolved ticker + structured facts (search_xbrl_facts, get_company_financials) and any filing pages from the three-layer protocol.
  2. Build: write the .md sum-of-the-parts valuation (segment multiples, conglomerate-discount analysis) per ## Output Structure.
  3. Validate: run the ## Validation Gates below.
  4. Output: write the artifact path per ## Output File.
  5. Next: append to agentii.md; hand off to a downstream pitch/review skill if requested.

Output File

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

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 — inline /v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index.
  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; a bottom Citations section provides a non-duplicative roll-up index; 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.

Validation Gates

  1. Segment coverage: segment revenues must sum to ≥80% of total reported revenue. If failed: flag segments representing <80% of revenue; note "significant unallocated revenue."
  2. Valuation consistency: segment multiples justified by at least one comparable company or sector norm per segment. If failed: flag segments with unsubstantiated multiples.
  3. SOTP bridge integrity: Segment Sum - Corporate + Adjustments = Total Equity within 1%. If failed: refuse delivery; check bridge arithmetic.

Tool Fallbacks

Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.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 a compact Key Citations list (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. See contracts/citation-and-memory.md.

Error Handling

Failure ModeActionUser-Facing Message
No segment dataCompany reports as single segment"{ticker} reports as a single operating segment — SOTP not applicable. Use DCF or comps."
Missing segment financialsProceed with available data; flag gaps"Segment financials incomplete for {segment_names}; SOTP based on partial data."

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sotp Valuation AI skill do?

Sum of the Parts valuation, segment-based valuation, conglomerate valuation, business segment analysis, breakup value, segment sum valuation, parts worth more than whole, hidden asset value

Why use Sotp Valuation on TypingMind?

Because you install it once and use it with any model. Sotp Valuation 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 Sotp Valuation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/sotp-valuation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sotp Valuation?

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 Sotp Valuation?

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

Is the Sotp Valuation AI skill free?

Yes. It is published on GitHub by agentii-ai under the Apache-2.0 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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