Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation
Install Lbo
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence lbo --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .claude/skills/lbo && rm -rf skills-srcUse ~/.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/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .claude/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lboType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence lbo --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .agents/skills/lbo && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .agents/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence lbo --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .cursor/skills/lbo && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .cursor/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/agentii-ai/agentii-investment-intelligence.git --path plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence lbo --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .gemini/skills/lbo && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .gemini/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install agentii-ai/agentii-investment-intelligence lboInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .github/skills/lbo && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .github/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence lbo --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo .opencode/skills/lbo && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "lbo" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo into .opencode/skills/lbo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lbo", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
lbo- GitHub stars
- 207
- Token cost
- ~1.9k tokens
- SKILL.md length
- 796 words
- Files
- 9 (incl. references)
- Skills in repo
- 79
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation
- Works in 5 steps: Inputs: resolved ticker +… → Build: write a self-contained Python… → Validate: run LibreOffice recalc; audit… → …
- Business, Finance & HR work in your project
- SKILL.md covers Preflight, Triggers, Defaults and Methodology, plus 8 more sections
- Reaches agentii.ai
What it does
Lbo is an agent skill from agentii-ai/agentii-investment-intelligence. LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/formula-sheet.md`, `references/institutional-defaults.md` and `references/methodology.md`).
It sits in Business, Finance & HR. 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
- Business, Finance & HR work in your project
Example prompts
- “/lbo”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Inputs: resolved ticker + search_xbrl_facts (Income Statement, Balance Sheet, Cash Flow) + get_company_financials for historical financials.
- Build: write a self-contained Python script using openpyxl that creates the LBO workbook (sources & uses, debt schedule, pro forma…
- Validate: run LibreOffice recalc; audit per ## Validation Gates.
- Output: write the artifact path per ## Output File.
- Next: append to agentii.md; hand off to a downstream pitch/review skill if requested.
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
Lbo loads about 1.9k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 796 words of instructions outside code blocks.
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). 796 words, ~1,888 tokens.
Download SKILL.mdSave it as
.claude/skills/lbo/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- lbo
- description
- LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation
- multi_ticker_semantics
- target_with_optional_peers
- temporal_scope.default_quarters
- 4
- temporal_scope.max_quarters
- 12
- temporal_scope.description
- Typical lookback: 4 quarters, max: 12
- retrieval_scope
- unstructured_document_search
- min_tool_diversity
- 5
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 lbo model
- run lbo model analysis
- produce lbo model report
- lbo model breakdown
- lbo model deep dive
- build a lbo model
- assess lbo model
- quantify lbo model
- compare lbo model across peers
- review lbo model for
- generate lbo model on
- lbo model for investment decision
Defaults
| Parameter | Default | Notes |
|---|---|---|
| lookback_years | 3 | Historical data window |
| include_peers | false | Whether to surface a peer comparison block |
Methodology
Retrieval Scope
This skill performs unstructured document search at scale across SEC filings and earnings call transcripts (10-K, 10-Q, 8-K). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
Retrieval Strategy
See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.
Temporal Scope
Default: 12 fiscal quarters (max 20). Financial modeling: trailing 12 quarters (3 fiscal years) for long-range projection inputs.
Tool Allowlist
See frontmatter allowed_tools.
Protocol
Step-by-step execution detail is in references/methodology.md.
Deliverable Chain
Inputs → Build → Validate → Output → Next
- Inputs: resolved ticker +
search_xbrl_facts(Income Statement, Balance Sheet, Cash Flow) +get_company_financialsfor historical financials. - Build: write a self-contained Python script using
openpyxlthat creates the LBO workbook (sources & uses, debt schedule, pro forma statements, returns waterfall) per## Output Structure. Execute viaBash: python3 script.py. Verify the.xlsxexists. Ifimport openpyxlfails, fall back to.mdsummary withdata_availability: degraded(seecontracts/office-tooling.md). - Validate: run LibreOffice recalc; audit per
## Validation Gates. - Output: write the artifact path per
## Output File. - Next: append to
agentii.md; hand off to a downstream pitch/review skill if requested.
Validation Gates
sources vs uses: sources = uses within 0.1% tolerance. If failed: If unbalanced: refuse delivery.
sponsor IRR: >= 20% at exit. If failed: If IRR < 20%: flag in assumptions.
debt schedule: mandatory repayments present for each tranche. If failed: If missing: refuse delivery.
**calculation arc cross-validation **: cross-statement balancing verified against
gold.xbrl_calculationsweights — the LBO model's financial projections MUST align with the filer's reported accounting relationships. Callget_statement_structure(accession_number)(resolve the accession_number first). Flag discrepancies ≥1% of parent concept value. If failed: If material discrepancy (≥1%): flag in audit findings.tool diversity: distinct MCP tools used in this invocation >=
min_tool_diversity(5). If failed: flag as depth-insufficient in Coverage Gaps, listing which tool categories were unused (structured data / document retrieval / company metadata / earnings calendar / coverage). This gate does NOT block analysis completion — it is a quality signal for your review.
Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.
Output File
Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_lbo_{affix}.md .
Show full SKILL.md (345 more words)Show less
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:
- Executive Summary — headline conclusions (≤200 words).
- Core analysis sections — per this skill's methodology and analyst modes.
- Data classification — tag findings
[FACT]/[DEDUCTED]/[VIEW]percontracts/snapshot-synthesis.md. - Coverage Gaps & Citations — inline
/v/citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index. - 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.
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) percontracts/output-frontmatter-schema.md. - Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as
[FACT]/[DEDUCTED]/[VIEW]— seecontracts/snapshot-synthesis.md. - Session archival: record the run under
sessions/{YYYY-MM-DD}/and updatesessions/INDEX.mdpercontracts/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 Mode | Detection | Action | User-Facing Message |
|---|---|---|---|
| Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." |
| Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." |
| Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." |
| Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." |
| MCP unreachable | Preflight probe fails | Halt 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 8 other files (references) in plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo of agentii-ai/agentii-investment-intelligence.
- SKILL.md
- references/formula-sheet.md
- references/institutional-defaults.md
- references/methodology.md
- references/modes.md
- references/output-structure.md
- references/tool-fallbacks.md
- references/validation-checklist.md
- references/wsp-methodology.md
Open the folder on GitHubat commit 86980e1
Compare with similar skills
Lbo 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Lbo this skillagentii-ai/agentii-investment-intelligence | 207 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Questions about Lbo
What does Lbo do?
LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation. Lbo is an agent skill from agentii-ai/agentii-investment-intelligence.
When should I use Lbo?
Lbo fits situations like: business, Finance & HR work in your project.
How do I install Lbo in Claude Code?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo in agentii-ai/agentii-investment-intelligence) into .claude/skills/lbo in your project. Claude Code loads it when a task matches its description.
How do I install Lbo in Codex?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill lbo -a codex`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/lbo in agentii-ai/agentii-investment-intelligence) into .agents/skills/lbo in your project. Codex loads it when a task matches its description.
Can I use Lbo 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 lbo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lbo, .gemini/skills/lbo, .github/skills/lbo and .opencode/skills/lbo in your project.
What does Lbo need to run?
SKILL.md names no scripts, command-line tools or credentials: Lbo is instructions for the agent only. Our summary lists: Python 3.
Does Lbo 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 Lbo 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 Lbo use?
Lbo 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 Lbo use?
About 1.9k tokens (SKILL.md is roughly 7.6k 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 10k tokens, read only when the agent opens those files.
What are the alternatives to Lbo?
Skills that share tags, products or a category with Lbo: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Lbo?
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.