Creating Financial Models
Chen-zexi/open-ptc-agent
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
PEG valuation, Price Earnings to Growth ratio, Peter Lynch PEG methodology, growth-adjusted valuation, earnings growth rate, PE ratio valuation, PEG sector comparison, undervalued growth stocks…
Install Peg Valuation
$ npx skills add agentii-ai/agentii-investment-intelligence --skill peg-valuation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence peg-valuation --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/quantitative-analysis/skills/agentii/peg-valuation .claude/skills/peg-valuation && 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 "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .claude/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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/quantitative-analysis/skills/agentii/peg-valuationType 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 peg-valuation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence peg-valuation --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/quantitative-analysis/skills/agentii/peg-valuation .agents/skills/peg-valuation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .agents/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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 peg-valuation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence peg-valuation --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/quantitative-analysis/skills/agentii/peg-valuation .cursor/skills/peg-valuation && 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 "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .cursor/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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/quantitative-analysis/skills/agentii/peg-valuation--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 peg-valuation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence peg-valuation --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/quantitative-analysis/skills/agentii/peg-valuation .gemini/skills/peg-valuation && 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 "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .gemini/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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 peg-valuationInstalls 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 peg-valuation -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/quantitative-analysis/skills/agentii/peg-valuation .github/skills/peg-valuation && 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 "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .github/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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 peg-valuation -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 peg-valuation --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/quantitative-analysis/skills/agentii/peg-valuation .opencode/skills/peg-valuation && 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 "peg-valuation" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation into .opencode/skills/peg-valuation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peg-valuation", 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
peg-valuation- GitHub stars
- 207
- Token cost
- ~1.6k tokens
- SKILL.md length
- 658 words
- Files
- 5 (incl. references)
- Skills in repo
- 79
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
PEG valuation, Price Earnings to Growth ratio, Peter Lynch PEG methodology, growth-adjusted valuation, earnings growth rate, PE ratio valuation, PEG sector comparison, undervalued growth stocks…
- Works in 5 steps: Executive Summary — headline conclusions… → Core analysis sections — per this… → Data classification — tag findings… → …
- Tasks that involve Financial modeling
- SKILL.md covers Preflight, Triggers, Defaults and Methodology, plus 6 more sections
- Reaches agentii.ai
What it does
Peg Valuation is an agent skill from agentii-ai/agentii-investment-intelligence. PEG valuation, Price Earnings to Growth ratio, Peter Lynch PEG methodology, growth-adjusted valuation, earnings growth rate, PE ratio valuation, PEG sector comparison, undervalued growth stocks, fair value PEG
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/methodology.md`, `references/modes.md` and `references/output-structure.md`).
It sits in Business, Finance & HR, covering Financial modeling. 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 Financial modeling
Example prompts
- “/peg-valuation”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Executive Summary — headline conclusions (≤200 words).
- Core analysis sections — per this skill's methodology and analyst modes.
- Data classification — tag findings [FACT] / [DEDUCTED] / [VIEW] per contracts/snapshot-synthesis.md.
- Coverage Gaps & Citations — inline /v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a…
- Output frontmatter — emit the FR-090 structured block per contracts/output-frontmatter-schema.md.
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
Peg Valuation loads about 1.6k tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 56 tokens; SKILL.md has 658 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). 658 words, ~1,623 tokens.
Download SKILL.mdSave it as
.claude/skills/peg-valuation/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- peg-valuation
- description
- PEG valuation, Price Earnings to Growth ratio, Peter Lynch PEG methodology, growth-adjusted valuation, earnings growth rate, PE ratio valuation, PEG sector comparison, undervalued growth stocks, fair value PEG
- multi_ticker_semantics
- target_with_optional_peers
- temporal_scope.default_quarters
- 4
- temporal_scope.max_quarters
- 12
- temporal_scope.description
- Trailing 4 quarters for current PE; up to 12 for historical CAGR
- retrieval_scope
- structured_only
- min_tool_diversity
- 4
PEG Valuation
Peter Lynch PEG (Price/Earnings to Growth) methodology. PEG = P/E Ratio ÷ Earnings Growth Rate (%). Growth-adjusted valuation that answers: "Is this stock's growth justifying its multiple?"
Preflight
Run canonical pre-flight per contracts/preflight.md.
**get_realtime_quote availability **: If get_realtime_quote is not yet deployed, prompt user for current stock price. PE numerator from search_earnings_calendar (NTM consensus EPS × current price = PE) as fallback.
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
- PEG valuation for {ticker}
- compute PEG ratio {ticker}
- Peter Lynch PEG {ticker}
- growth-adjusted valuation {ticker}
- is {ticker} undervalued by PEG
- PEG analysis {ticker}
- price earnings growth {ticker}
- compare PEG across peers
- {ticker} PEG vs sector
- growth at reasonable price {ticker}
Defaults
| Parameter | Default | Notes |
|---|---|---|
| growth_source | consensus | consensus estimates preferred; fallback to historical CAGR |
| include_peers | true | Sector PEG comparison |
| lookback_years | 3 | Historical CAGR computation window |
Methodology
Retrieval Scope
structured_only — PEG uses XBRL earnings data + real-time price + earnings calendar for growth estimates.
Retrieval Strategy
See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.
Temporal Scope
Default: 4 fiscal quarters (max 12). PEG uses trailing 4 quarters for LTM P/E; up to 12 for historical EPS CAGR if consensus unavailable.
Tool Allowlist
See frontmatter allowed_tools — 4 tools. get_realtime_quote for current price + PE (TTM). search_earnings_calendar for consensus EPS and long-term growth estimates. search_xbrl_facts for historical EPS to compute CAGR. search_companies for peer identification.
Protocol
Step-by-step execution detail is in references/methodology.md.
PEG Interpretation (Peter Lynch Framework)
| PEG Range | Rating | Investment Implication |
|---|---|---|
| < 0.5 | Deeply Undervalued | Growth vastly exceeds valuation; investigate for hidden risks |
| 0.5 – 1.0 | Undervalued | Classic Lynch buy zone; growth justifies the multiple |
| 1.0 – 1.5 | Fairly Valued | Growth and valuation in equilibrium |
| 1.5 – 2.0 | Premium | Market paying up for growth; needs above-consensus execution |
| > 2.0 | Overvalued | Growth insufficient to justify current multiple |
| Negative | N/A | Negative earnings — PEG not meaningful; use revenue-based metrics |
Output File
Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_peg-valuation_{affix}.md.
Show full SKILL.md (333 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.
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) 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 | No consensus or historical EPS | Halt; cannot compute growth rate | "Insufficient earnings data to compute growth rate for {ticker}." |
| Negative earnings | PE (TTM) < 0 | Compute only revenue-based metrics; flag PEG as N/A | "PEG not applicable — {ticker} has negative earnings." |
| Zero growth | CAGR ≈ 0% | PEG = ∞; flag as "no growth" case | "Zero historical EPS growth — PEG effectively infinite." |
| MCP unreachable | Preflight probe fails | Halt | "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 4 other files (references) in plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation of agentii-ai/agentii-investment-intelligence.
- SKILL.md
- references/methodology.md
- references/modes.md
- references/output-structure.md
- references/tool-fallbacks.md
Open the folder on GitHubat commit 86980e1
Compare with similar skills
Peg Valuation 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 |
|---|---|---|---|---|---|---|
| Peg Valuation this skillagentii-ai/agentii-investment-intelligence | 207 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Equity ResearchrollingSirius/equity-research-skill | 453 | — | ~1.5k | Automated safety check: Pass | MIT | |
| SaaS Metrics Coachrongxinzy/RongxinAI | 154 | 2 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Startup Financial Modelingnicepkg/auto-company | 194 | 11 repos | ~2.8k | Automated safety check: Pass | None | |
| Stock Value AnalyzerFunnyKun/stock-value-analyzer | 140 | — | ~3.3k | Automated safety check: Pass | None |
Similar skills
Equity Research
rollingSirius/equity-research-skill
撰写机构级个股投资研究报告（二级市场深度研究）。Use whenever the user wants to research, analyze, or value a specific publicly-traded stock — e.g.
SaaS Metrics Coach
rongxinzy/RongxinAI
SaaS financial health advisor. An agent skill from rongxinzy/RongxinAI.
Startup Financial Modeling
nicepkg/auto-company
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or…
Stock Value Analyzer
FunnyKun/stock-value-analyzer
基于邱国鹭《投资中最简单的事》方法论的股票价值分析器（v2.0 双层架构）。通过"三好原则"（好行业、好公司、好价格）系统评估一只股票是否值得投资。v2.0 在原定性框架之上注入一套可量化、可复现的硬模型层——反向 DCF 反解市场隐含增速、情景概率加权估值、EPV 盈利能力价值、分行业估值路由、杜邦三/五因子分解、ROIC vs WACC、Piotroski F-Score、Beneish…
Dcf Valuation
edinetdb/dexter-jp
Performs discounted cash flow (DCF) valuation analysis to estimate intrinsic value per share for Japanese listed companies.
More from agentii-ai/agentii-investment-intelligence
All 79 skills in this repoChallenge
agentii-ai/agentii-investment-intelligence
Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion…
Chart Patterns
agentii-ai/agentii-investment-intelligence
Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step…
Clarify
agentii-ai/agentii-investment-intelligence
The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrongif, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human…
Constitution
agentii-ai/agentii-investment-intelligence
Scaffold and amend the L1 Investment Constitution — [ALLCAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm.
Converge
agentii-ai/agentii-investment-intelligence
Append-only gap closure and the cadence engine for research theses.
Implement
agentii-ai/agentii-investment-intelligence
Execute research tasks — checklist soft gate, phase dispatch with explicit thesisdir, budget enforcement (halt + approval card on overrun), skillpin recording (versionhash content-hashed per skill…
Related
Categories
Questions about Peg Valuation
What does Peg Valuation do?
PEG valuation, Price Earnings to Growth ratio, Peter Lynch PEG methodology, growth-adjusted valuation, earnings growth rate, PE ratio valuation, PEG sector comparison, undervalued growth stocks…. Peg Valuation is an agent skill from agentii-ai/agentii-investment-intelligence.
When should I use Peg Valuation?
Peg Valuation fits situations like: tasks that involve Financial modeling.
How do I install Peg Valuation in Claude Code?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill peg-valuation -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation in agentii-ai/agentii-investment-intelligence) into .claude/skills/peg-valuation in your project. Claude Code loads it when a task matches its description.
How do I install Peg Valuation in Codex?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill peg-valuation -a codex`. Or copy the skill folder (plugins/vertical-plugins/quantitative-analysis/skills/agentii/peg-valuation in agentii-ai/agentii-investment-intelligence) into .agents/skills/peg-valuation in your project. Codex loads it when a task matches its description.
Can I use Peg Valuation 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 peg-valuation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/peg-valuation, .gemini/skills/peg-valuation, .github/skills/peg-valuation and .opencode/skills/peg-valuation in your project.
What does Peg Valuation need to run?
SKILL.md names no scripts, command-line tools or credentials: Peg Valuation is instructions for the agent only.
Does Peg Valuation 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 Peg Valuation 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 Peg Valuation use?
Peg Valuation 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 Peg Valuation use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 1k tokens, read only when the agent opens those files.
What are the alternatives to Peg Valuation?
Skills that share tags, products or a category with Peg Valuation: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Equity Research (rollingSirius/equity-research-skill, 453 stars), SaaS Metrics Coach (rongxinzy/RongxinAI, 154 stars) and Startup Financial Modeling (nicepkg/auto-company, 194 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Peg Valuation?
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.