estimate-analysis

estimate-analysis is a skill for Claude Code from himself65/finance-skills. It costs 195 tokens per session (2,481 once invoked), scanned A, original, MIT.

A stock-analysis tool that uses Yahoo Finance data to examine what financial analysts expect for a company. It compares earnings-per-share and revenue forecasts, their changes over time, and expected growth.

In plain words
What is it for?
It is for reviewing estimate trends, comparing forecast distributions, and studying projected growth across periods. The data is for research and education, not financial advice.
Why use it?
It helps show whether analyst expectations are rising or falling instead of looking at only the latest forecast.

Skill for Claude Code

Written for Claude Code: dynamic context !`command`. Also seen: positional $N argument.

Part of the finance-market-analysis plugin — 11 skills shipped together

Good fit It is for reviewing estimate trends, comparing forecast distributions, and studying projected growth across periods. The data is for research and education, not financial advice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/himself65/finance-skills/estimate-analysis
About the project

Finance Skills is a collection of agent skills for financial analysis and trading, covering activities such as company valuation, earnings research, market analysis, and options calculations. It is for users who want coding agents to perform structured finance workflows, and the catalogue contains its skills, plugins, instructions, and MCP integration.

himself65/finance-skills · 3,292 stars · on GitHub · skills.himself65.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add himself65/finance-skills --skill estimate-analysis
Clone the repo
git clone --depth 1 https://github.com/himself65/finance-skills

Made for: Claude Code.

Or install finance-market-analysis, the plugin that ships this one along with the rest of its 11 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for estimate-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/himself65/finance-skills/estimate-analysis.svg)](https://agentmods.dev/skills/himself65/finance-skills/estimate-analysis)
Your own site
<a href="https://agentmods.dev/skills/himself65/finance-skills/estimate-analysis"><img src="https://agentmods.dev/badge/skills/himself65/finance-skills/estimate-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 195 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,481 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 1 Apr 2026
  • Snyk warn 1 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00195 $0.02481
Opus 5 $0.00097 $0.01241
Sonnet 5 $0.00039 $0.00496
Haiku 4.5 $0.00019 $0.00248

Measured 8d ago against content hash b1487a45feae, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

estimate-analysis scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])
plugins/market-analysis/skills/estimate-analysis/SKILL.md · 219 lines

How it starts

The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Estimate Analysis Skill

Deep-dives into analyst estimates and revision trends using Yahoo Finance data via yfinance. Covers EPS and revenue estimate distributions, revision momentum, growth projections, and multi-period comparisons — the full picture of where the street thinks a company is heading.

Important: Data is for research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.


Step 1: Ensure yfinance Is Available

Current environment status:

!`python3 -c "exec('try:\n import yfinance\n print(\'yfinance \' + yfinance.__version__ + \' installed\')\nexcept Exception:\n print(\'YFINANCE_NOT_INSTALLED\')')"`

If YFINANCE_NOT_INSTALLED, install it:

import subprocess, sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])

If already installed, skip to the next step.


Step 2: Identify the Ticker and Gather Estimate Data

Extract the ticker from the user's request. Fetch all estimate-related data in one script.

import yfinance as yf
import pandas as pd

ticker = yf.Ticker("AAPL")  # replace with actual ticker

# --- Estimate data ---
earnings_est = ticker.earnings_estimate      # EPS estimates by period
revenue_est = ticker.revenue_estimate        # Revenue estimates by period
eps_trend = ticker.eps_trend                 # EPS estimate changes over time
eps_revisions = ticker.eps_revisions         # Up/down revision counts
growth_est = ticker.growth_estimates         # Growth rate estimates

# --- Historical context ---
earnings_hist = ticker.earnings_history      # Track record
info = ticker.info                           # Company basics
quarterly_income = ticker.quarterly_income_stmt  # Recent actuals

What each data source provides

Data Source What It Shows Why It Matters
earnings_estimate Current EPS consensus by period (0q, +1q, 0y, +1y) The estimate levels — what analysts expect
revenue_estimate Current revenue consensus by period Top-line expectations
eps_trend How the EPS estimate has changed (7d, 30d, 60d, 90d ago) Revision direction — rising or falling expectations
eps_revisions Count of upward vs downward revisions (7d, 30d) Revision breadth — are most analysts raising or cutting?
growth_estimates Growth rate estimates vs peers and sector Relative positioning
earnings_history Actual vs estimated for last 4 quarters Calibration — how good are these estimates historically?

Read the full file on GitHub · 219 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 219 lines · 195 tokens per session scan A b1487a45feae

Subscribe to this mod's changes

estimate-analysis is a skill published in the GitHub repository himself65/finance-skills (3,292 stars, last pushed 11d ago), licensed MIT. It adds 195 tokens to every session and 2,481 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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