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
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage.
Install Analyst Estimates
$ npx skills add OctagonAI/skills --skill analyst-estimates -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OctagonAI/skills analyst-estimates --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/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyst-estimates .claude/skills/analyst-estimates && 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 "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .claude/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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/OctagonAI/skills/tree/main/skills/analyst-estimatesType 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 OctagonAI/skills --skill analyst-estimates -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OctagonAI/skills analyst-estimates --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyst-estimates .agents/skills/analyst-estimates && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .agents/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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 OctagonAI/skills --skill analyst-estimates -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OctagonAI/skills analyst-estimates --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyst-estimates .cursor/skills/analyst-estimates && 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 "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .cursor/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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/OctagonAI/skills.git --path skills/analyst-estimates--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 OctagonAI/skills --skill analyst-estimates -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OctagonAI/skills analyst-estimates --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyst-estimates .gemini/skills/analyst-estimates && 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 "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .gemini/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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 OctagonAI/skills analyst-estimatesInstalls 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 OctagonAI/skills --skill analyst-estimates -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyst-estimates .github/skills/analyst-estimates && 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 "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .github/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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 OctagonAI/skills --skill analyst-estimates -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OctagonAI/skills analyst-estimates --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyst-estimates .opencode/skills/analyst-estimates && 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 "analyst-estimates" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/analyst-estimates into .opencode/skills/analyst-estimates/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyst-estimates", 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
analyst-estimates- GitHub stars
- 127
- Token cost
- ~1.1k tokens
- SKILL.md length
- 433 words
- Files
- 5 (incl. references)
- Skills in repo
- 53
- Repo updated
- First seen
- Licence
- MIT
At a glance
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage.
- Works in 5 steps: Growth trajectory: Calculate implied… → Estimate dispersion: Analyze spread… → Analyst coverage: Note number of… → …
- Analyzing forward expectations
- SKILL.md covers Prerequisites, Query Format, Output Format and Key Observations Pattern, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Analyst Estimates is an agent skill from OctagonAI/skills. Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Use when analyzing forward expectations, consensus estimates, valuation inputs, or comparing projections to historical performance.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).
It sits in Business, Finance & HR, covering Financial modeling. It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.
When your agent uses it
- Analyzing forward expectations
- Consensus estimates
- Valuation inputs
- Comparing projections to historical performance
Example prompts
- “/analyst-estimates”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Growth trajectory: Calculate implied revenue and EPS CAGR
- Estimate dispersion: Analyze spread between low and high estimates
- Analyst coverage: Note number of analysts covering each period
- Near vs far-term: Compare confidence in near-term vs long-term estimates
- Historical comparison: Compare estimates to actual historical performance
What it can do on your machine
Read from SKILL.md and the folder at commit 51e938c. 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 (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Analyst Estimates loads about 1.1k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 433 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 OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 433 words, ~1,141 tokens.
Download SKILL.mdSave it as
.claude/skills/analyst-estimates/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- analyst-estimates
- description
- Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Use when analyzing forward expectations, consensus estimates, valuation inputs, or comparing projections to historical performance.
Analyst Estimates
Retrieve analyst financial estimates for public companies using Octagon MCP.
Prerequisites
Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
Query Format
Retrieve analyst financial estimates for <TICKER> for the annual period, limited to <N> records on page 0.MCP Call:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Retrieve analyst financial estimates for AAPL for the annual period, limited to 10 records on page 0"
}
}Output Format
The agent returns a table with analyst estimates across future periods:
| Fiscal Year Ending | Revenue Estimate (Low to High) | Revenue Avg | EPS Estimate (Low to High) | EPS Avg | # Revenue Analysts | # EPS Analysts |
|---|---|---|---|---|---|---|
| 2030-09-27 | $540.64B - $600.88B | $566.24B | $12.01 - $13.78 | $12.77 | 9 | 6 |
| 2029-09-27 | $520.95B - $578.99B | $545.62B | $10.62 - $12.17 | $11.28 | 13 | 6 |
| 2028-09-27 | $515.19B - $520.48B | $517.84B | $8.96 - $11.18 | $10.20 | 18 | 15 |
| 2027-09-27 | $474.27B - $531.94B | $490.97B | $8.41 - $9.77 | $9.23 | 31 | 30 |
| 2026-09-27 | $445.03B - $483.54B | $460.35B | $7.84 - $8.92 | $8.42 | 24 | 29 |
Data Source: octagon-financials-agent
Key Observations Pattern
After receiving data, generate observations:
- Growth trajectory: Calculate implied revenue and EPS CAGR
- Estimate dispersion: Analyze spread between low and high estimates
- Analyst coverage: Note number of analysts covering each period
- Near vs far-term: Compare confidence in near-term vs long-term estimates
- Historical comparison: Compare estimates to actual historical performance
Metrics Reference
| Metric | Definition |
|---|---|
| Revenue Estimate (Low to High) | Range of analyst revenue projections |
| Revenue Avg | Consensus average revenue estimate |
| EPS Estimate (Low to High) | Range of analyst EPS projections |
| EPS Avg | Consensus average EPS estimate |
| # Revenue Analysts | Number of analysts providing revenue estimates |
| # EPS Analysts | Number of analysts providing EPS estimates |
Analysis Tips
Implied Growth Rate
Implied CAGR = (Future Estimate / Current)^(1/Years) - 1Example: ($566B / $416B)^(1/5) - 1 = 6.4% revenue CAGR
Estimate Dispersion
Dispersion = (High - Low) / Average × 100- Narrow dispersion (<10%) = High consensus
- Wide dispersion (>20%) = Significant uncertainty
Show full SKILL.md (182 more words)Show less
Analyst Coverage Quality
- More analysts = more reliable consensus
- Declining coverage = less institutional interest
- <5 analysts = thin coverage, use caution
Forward P/E Calculation
Forward P/E = Current Price / EPS EstimateUse for valuation relative to growth expectations.
Estimate Revisions (with follow-up)
Track changes over time:
- Upward revisions = positive momentum
- Downward revisions = negative momentum
- Frequency of revisions matters
Valuation Applications
DCF Inputs
Use estimates for:
- Revenue projections
- Margin assumptions (with historical data)
- Terminal growth rate guidance
Relative Valuation
Compare:
- Forward P/E to historical average
- Forward P/E to peers
- PEG ratio (P/E / Growth rate)
Earnings Surprise Potential
Compare estimates to:
- Management guidance
- Historical beat/miss rate
- Recent operating trends
Confidence Assessment
High Confidence Estimates
- Near-term (1-2 years out)
- Many analysts covering
- Narrow dispersion
- Stable business model
Low Confidence Estimates
- Long-term (5+ years out)
- Few analysts covering
- Wide dispersion
- Rapidly changing industry
Follow-up Queries
Based on results, suggest deeper analysis:
- "What factors are driving the projected revenue growth from [YEAR1] to [YEAR2]?"
- "How do these estimates compare to [COMPANY]'s historical financial performance?"
- "What are the key risks to achieving the upper end of these revenue estimates?"
- "Retrieve analyst price targets and ratings for [TICKER]"
© OctagonAI, MIT. 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 skills/analyst-estimates of OctagonAI/skills.
- SKILL.md
- README.md
- marketplace.json
- references/interpreting-results.md
- references/mcp-setup.md
Open the folder on GitHubat commit 51e938c
Compare with similar skills
Analyst Estimates 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 |
|---|---|---|---|---|---|---|
| Analyst Estimates this skillOctagonAI/skills | 127 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Dcf ModelWind-Alice/AliceMarket | 134 | 2 repos | ~12k | Automated safety check: Pass | None | |
| Sealeap Amazon New Product Ad Recoveryxjli360/sealeap-amazon-skills | 251 | — | ~518 | Automated safety check: Pass | MIT | |
| Sealeap Baize Amazon Ad Strategy Routerxjli360/sealeap-amazon-skills | 251 | — | ~553 | Automated safety check: Pass | MIT | |
| Sealeap Chiwen Amazon Niche Nine Check Screenxjli360/sealeap-amazon-skills | 251 | — | ~815 | Automated safety check: Pass | MIT |
Similar skills
Dcf Model
Wind-Alice/AliceMarket
Real DCF (Discounted Cash Flow) model creation for equity valuation.
Sealeap Amazon New Product Ad Recovery
xjli360/sealeap-amazon-skills
Recover an underperforming Amazon new-product advertising program by diagnosing traffic concentration, sample sufficiency, placement mix, retail readiness, and unit economics in a fixed order.
Sealeap Baize Amazon Ad Strategy Router
xjli360/sealeap-amazon-skills
Route an Amazon product into precise-attribute, broad-intent, or no-clear-keyword advertising structures based on product truth, search behavior, conversion, and unit economics.
Sealeap Chiwen Amazon Niche Nine Check Screen
xjli360/sealeap-amazon-skills
Run a nine-checkpoint screen on a candidate product niche — long- and short-term demand trend, a competition-density ratio, brand concentration among top listings, fulfillment-method mix, price-band…
Sealeap Fenghuang Amazon Product Research Methods
xjli360/sealeap-amazon-skills
Generate product candidates for the US marketplace through several discovery paths—keyword-gap search, filtered product databases, reverse-ASIN keyword pulls, and own-problem ideas—then push every…
More from OctagonAI/skills
All 53 skills in this repoBalance Sheet
OctagonAI/skills
Retrieve detailed balance sheet statement data including Total Assets, Current Assets, Non-Current Assets, Liabilities, Equity, and Net Debt for public companies.
Balance Sheet Growth
OctagonAI/skills
Retrieve year-over-year growth in balance sheet items including Total Assets, Total Liabilities, Shareholders Equity, Cash, and Inventories.
Batch Market Cap
OctagonAI/skills
Retrieve market capitalization data for multiple companies at once using Octagon MCP.
Cash Flow Growth
OctagonAI/skills
Retrieve year-over-year growth in cash flow metrics including Operating Cash Flow, Free Cash Flow, and Net Cash Flow.
Cash Flow Statement
OctagonAI/skills
Retrieve real-time or historical cash flow statement data including Net Income, Operating Cash Flow, Investing Cash Flow, Financing Cash Flow, Free Cash Flow, and Cash Position for public companies.
Commodities List
OctagonAI/skills
Retrieve the full catalog of tradable commodities across energy, metals, and agriculture using Octagon MCP.
Related
Works with
Categories
Questions about Analyst Estimates
What does Analyst Estimates do?
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Analyst Estimates is an agent skill from OctagonAI/skills. Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage.
When should I use Analyst Estimates?
Analyst Estimates fits situations like: analyzing forward expectations; consensus estimates; valuation inputs; comparing projections to historical performance.
How do I install Analyst Estimates in Claude Code?
Run `npx skills add OctagonAI/skills --skill analyst-estimates -a claude-code`. Or copy the skill folder (skills/analyst-estimates in OctagonAI/skills) into .claude/skills/analyst-estimates in your project. Claude Code loads it when a task matches its description.
How do I install Analyst Estimates in Codex?
Run `npx skills add OctagonAI/skills --skill analyst-estimates -a codex`. Or copy the skill folder (skills/analyst-estimates in OctagonAI/skills) into .agents/skills/analyst-estimates in your project. Codex loads it when a task matches its description.
Can I use Analyst Estimates 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 OctagonAI/skills --skill analyst-estimates -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyst-estimates, .gemini/skills/analyst-estimates, .github/skills/analyst-estimates and .opencode/skills/analyst-estimates in your project.
What does Analyst Estimates need to run?
SKILL.md names no scripts, command-line tools or credentials: Analyst Estimates is instructions for the agent only.
Does Analyst Estimates access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Analyst Estimates 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 Analyst Estimates use?
Analyst Estimates is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Analyst Estimates use?
About 1.1k tokens (SKILL.md is roughly 4.6k 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 1.7k tokens, read only when the agent opens those files.
What are the alternatives to Analyst Estimates?
Skills that share tags, products or a category with Analyst Estimates: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Dcf Model (Wind-Alice/AliceMarket, 134 stars), Sealeap Amazon New Product Ad Recovery (xjli360/sealeap-amazon-skills, 251 stars) and Sealeap Baize Amazon Ad Strategy Router (xjli360/sealeap-amazon-skills, 251 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Analyst Estimates?
OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.
Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.