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
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns.
Install Pead Screener
$ npx skills add tradermonty/claude-trading-skills --skill pead-screener -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tradermonty/claude-trading-skills pead-screener --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/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/pead-screener .claude/skills/pead-screener && 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 "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .claude/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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/tradermonty/claude-trading-skills/tree/main/skills/pead-screenerType 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 tradermonty/claude-trading-skills --skill pead-screener -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tradermonty/claude-trading-skills pead-screener --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/pead-screener .agents/skills/pead-screener && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .agents/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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 tradermonty/claude-trading-skills --skill pead-screener -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tradermonty/claude-trading-skills pead-screener --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/pead-screener .cursor/skills/pead-screener && 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 "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .cursor/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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/tradermonty/claude-trading-skills.git --path skills/pead-screener--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 tradermonty/claude-trading-skills --skill pead-screener -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tradermonty/claude-trading-skills pead-screener --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/pead-screener .gemini/skills/pead-screener && 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 "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .gemini/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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 tradermonty/claude-trading-skills pead-screenerInstalls 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 tradermonty/claude-trading-skills --skill pead-screener -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/pead-screener .github/skills/pead-screener && 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 "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .github/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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 tradermonty/claude-trading-skills --skill pead-screener -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tradermonty/claude-trading-skills pead-screener --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/pead-screener .opencode/skills/pead-screener && 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 "pead-screener" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/pead-screener into .opencode/skills/pead-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pead-screener", 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
pead-screener- GitHub stars
- 3k
- Used in
- 1 other repo
- Token cost
- ~1.1k tokens
- SKILL.md length
- 431 words
- Files
- 16 (incl. scripts, references)
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- MIT
At a glance
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns.
- Works in 4 steps: Prepare and Execute Screening → Review Results → Present Analysis → …
- User asks about PEAD screening
- SKILL.md covers When to Use, Prerequisites, Workflow and Output, plus 1 more section
- Runs Python scripts from its folder; calls python3; needs FMP_API_KEY
What it does
Pead Screener is an agent skill from tradermonty/claude-trading-skills. Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including scripts and reference files (for example `references/entry_exit_rules.md`, `references/pead_strategy.md` and `scripts/_fmp_compat.py`).
It sits in Business, Finance & HR. The repository describes itself as: Claude Code skills for equity investors and traders — market analysis, technical charting, economic calendars, screeners, and trading strategy development. The licence is MIT.
When your agent uses it
- User asks about PEAD screening
- Post-earnings drift
- Earnings gap follow-through
- Red candle breakout patterns
Example prompts
- “/pead-screener”
Requirements
- Python 3
- A credential in FMP_API_KEY
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c8d58f0. 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
Ships 12 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
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 these keys or tokens, usually read from environment variables:
FMP_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Pead Screener loads about 1.1k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 431 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); the scripts in this folder are not scanned.
SKILL.md
The full file from tradermonty/claude-trading-skills at commit c8d58f0, republished under its MIT licence (© tradermonty). 431 words, ~1,118 tokens.
Download SKILL.mdSave it as
.claude/skills/pead-screener/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.- name
- pead-screener
- description
- Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
PEAD Screener - Post-Earnings Announcement Drift
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns using weekly candle analysis to detect red candle pullbacks and breakout signals.
When to Use
- User asks for PEAD screening or post-earnings drift analysis
- User wants to find earnings gap-up stocks with follow-through potential
- User requests red candle breakout patterns after earnings
- User asks for weekly earnings momentum setups
- User provides earnings-trade-analyzer JSON output for further screening
Prerequisites
- FMP API key (set
FMP_API_KEYenvironment variable or pass--api-key)bash export FMP_API_KEY=your_api_key_here - Free tier (250 calls/day) is sufficient for default screening
- For Mode B: earnings-trade-analyzer JSON output file with schema_version "1.0"
Workflow
Step 1: Prepare and Execute Screening
Run the PEAD screener script in one of two modes:
Mode A (FMP earnings calendar):
# Default: last 14 days of earnings, 5-week monitoring window
python3 skills/pead-screener/scripts/screen_pead.py --output-dir reports/
# Custom parameters
python3 skills/pead-screener/scripts/screen_pead.py \
--lookback-days 21 \
--watch-weeks 6 \
--min-gap 5.0 \
--min-market-cap 1000000000 \
--output-dir reports/Mode B (earnings-trade-analyzer JSON input):
# From earnings-trade-analyzer output
python3 skills/pead-screener/scripts/screen_pead.py \
--candidates-json reports/earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json \
--min-grade B \
--output-dir reports/Scheduled US-equity routine pitfall: Prefer Mode B for pre-market / US-equity cron briefs after running earnings-trade-analyzer. Mode A can pull the global FMP earnings calendar, spend the API budget on non-US symbols, and return weak/non-actionable foreign listings before reaching the intended US watchlist. If Mode A is used anyway and the script reports budget trimming or non-US symbols, mark PEAD output as degraded and treat it as manual-review only rather than a clean candidate source.
Step 2: Review Results
- Read the generated JSON and Markdown reports
- Load
references/pead_strategy.mdfor PEAD theory and pattern context - Load
references/entry_exit_rules.mdfor trade management rules
Step 3: Present Analysis
For each candidate, present:
- Stage classification (MONITORING, SIGNAL_READY, BREAKOUT, EXPIRED)
- Weekly candle pattern details (red candle location, breakout status)
- Composite score and rating
- Trade setup: entry, stop-loss, target, risk/reward ratio
- Liquidity metrics (ADV20, average volume)
Show full SKILL.md (161 more words)Show less
Step 4: Provide Actionable Guidance
Based on stages and ratings:
- BREAKOUT + Strong Setup (85+): High-conviction PEAD trade, full position size
- BREAKOUT + Good Setup (70-84): Solid PEAD setup, standard position size
- SIGNAL_READY: Red candle formed, set alert for breakout above red candle high
- MONITORING: Post-earnings, no red candle yet, add to watchlist
- EXPIRED: Beyond monitoring window, remove from watchlist
Output
pead_screener_YYYY-MM-DD_HHMMSS.json- Structured results with stage classificationpead_screener_YYYY-MM-DD_HHMMSS.md- Human-readable report grouped by stage
Unknown earnings timing
FMP does not confirm a bmo/amc session for every earnings row; unconfirmed
rows carry earnings_timing: "unknown" in Mode A and the price gap
calculation assumes the AMC window as a fallback. The Mode A report shows
timing_unknown_count out of timing_candidates_total so this assumption
stays visible (Mode B reports n/a since timing is inherited from the input
JSON). timing_candidates_total is the post-budget-trim population that was
actually analyzed, not the raw earnings-calendar row count.
Resources
references/pead_strategy.md- PEAD theory and weekly candle approachreferences/entry_exit_rules.md- Entry, exit, and position sizing rules
© tradermonty, 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 15 other files (scripts, references) in skills/pead-screener of tradermonty/claude-trading-skills.
- SKILL.md
- references/entry_exit_rules.md
- references/pead_strategy.md
- requirements.txt
- scripts/_fmp_compat.py
- scripts/calculators/__init__.py
- scripts/calculators/breakout_calculator.py
- scripts/calculators/liquidity_calculator.py
- scripts/calculators/risk_reward_calculator.py
- scripts/calculators/weekly_candle_calculator.py
- scripts/fmp_client.py
- scripts/report_generator.py
- scripts/scorer.py
- scripts/screen_pead.py
- scripts/tests/conftest.py
- scripts/tests/test_pead_screener.py
Open the folder on GitHubat commit c8d58f0
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in tradermonty/claude-trading-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Pead Screener 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 |
|---|---|---|---|---|---|---|
| Pead Screener this skilltradermonty/claude-trading-skills | 3k | 1 repos | ~1.1k | 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 | |
| Tushare Datazillionare/zillionare | 322 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Cc Sdd New Agentgotalab/cc-sdd | 3.7k | — | ~1.1k | Automated safety check: Pass | MIT |
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Categories
Questions about Pead Screener
What does Pead Screener do?
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Pead Screener is an agent skill from tradermonty/claude-trading-skills. Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns.
When should I use Pead Screener?
Pead Screener fits situations like: user asks about PEAD screening; post-earnings drift; earnings gap follow-through; red candle breakout patterns.
How do I install Pead Screener in Claude Code?
Run `npx skills add tradermonty/claude-trading-skills --skill pead-screener -a claude-code`. Or copy the skill folder (skills/pead-screener in tradermonty/claude-trading-skills) into .claude/skills/pead-screener in your project. Claude Code loads it when a task matches its description.
How do I install Pead Screener in Codex?
Run `npx skills add tradermonty/claude-trading-skills --skill pead-screener -a codex`. Or copy the skill folder (skills/pead-screener in tradermonty/claude-trading-skills) into .agents/skills/pead-screener in your project. Codex loads it when a task matches its description.
Can I use Pead Screener 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 tradermonty/claude-trading-skills --skill pead-screener -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pead-screener, .gemini/skills/pead-screener, .github/skills/pead-screener and .opencode/skills/pead-screener in your project.
What does Pead Screener need to run?
Going by SKILL.md and its folder, Pead Screener needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named FMP_API_KEY. Our summary lists: Python 3; A credential in FMP_API_KEY.
Does Pead Screener 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 Pead Screener 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Pead Screener use?
Pead Screener 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 Pead Screener use?
About 1.1k tokens (SKILL.md is roughly 4.5k 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 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Pead Screener?
Skills that share tags, products or a category with Pead Screener: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Stock API (zhangxiangliang/stock-api, 2k stars), Itr Wala (karanb192/itr-wala, 871 stars) and Tushare Data (zillionare/zillionare, 322 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Pead Screener?
tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,982 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 11, 2026.
Source: tradermonty/claude-trading-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.