Borrowing it
Nothing to install: this file belongs to tusharagg1/aifolimizer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tusharagg1/aifolimizer/master/.claude/skills/momentum-scanner/SKILL.mdgit clone --depth 1 https://github.com/tusharagg1/aifolimizerWrote 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.
[](https://agentmods.dev/skills/tusharagg1/aifolimizer/momentum-scanner)<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/momentum-scanner"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/momentum-scanner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/momentum-scanner"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/momentum-scanner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.01787 |
| Opus 5 | $0.00036 | $0.00894 |
| Sonnet 5 | $0.00014 | $0.00357 |
| Haiku 4.5 | $0.00007 | $0.00179 |
Grade A, and why
momentum-scanner scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Momentum Scanner (12-Month Momentum + 52-Week High Effect)
Research basis
Jegadeesh & Titman (1993): Past 12-month winners outperform losers by 12.01% annually. Effect persists independently of beta, size, or industry. Strongest version: skip most-recent month (reversal noise), rank on months 2-12.
George & Hwang (2004): Stocks within 10% of 52-week high earn ~1.23%/month long-short vs stocks far from high. Mechanism: anchoring bias - investors slow to push past prior resistance, so nearness predicts continuation.
Combined signal: High 12m momentum AND near 52wk high = double confirmation. Strongest continuation setup.
Stage 0 - Decision Memory (load FIRST)
Before analysis, load prior decisions so verdicts stay consistent across sessions:
mcp__aifolimizer__get_cross_ticker_lessonswithmax_lessons=3- portfolio-level win/loss patterns- For any name you issue a per-ticker BUY/SELL/TRIM/HOLD on, also load
mcp__aifolimizer__get_ticker_decision_history(ticker=…, max_decisions=5) andmcp__aifolimizer__get_ticker_reflection(symbol=…, n=3).
Reconciliation rule: if a prior decision exists and your new read flips it, state explicitly WHY it changed (new data / catalyst / price move). Never silently contradict a logged decision - that drift is exactly what this prevents.
How to run
- Call
mcp__aifolimizer__get_profile- account types, capital - Call
mcp__aifolimizer__get_portfolio- all holdings, current weights - Call
mcp__aifolimizer__get_technicalsfor all held symbols -pct_from_52w_high,pct_from_52w_low,minervini_score,technical_score, trend - Call
mcp__aifolimizer__backtest_portfoliowithstrategy="buy_hold"for 12-month return per symbol - Call
mcp__aifolimizer__get_positioning_signalsfor top 8 holdings - crowding check before any add signal - Call
mcp__aifolimizer__get_factor_snapshot- is the MOMENTUM FACTOR itself working?Momtrailing-252d positive = regime tailwind for this whole scan; negative = momentum regime weak, downgrade all continuation conviction one notch - Call
mcp__aifolimizer__get_search_interestwithkeywords=[top 3-5 momentum names]- search-demand confirmation. Rising interest + price momentum = retail fuel; but cross with crowding (surge + consensus = late-stage, suppress add)
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.
- 11d ago First seen · 107 lines · 72 tokens per session scan A 25a33f7e8e9e
momentum-scanner is a skill published in the GitHub repository tusharagg1/aifolimizer (2 stars, last pushed 9d ago), licensed MIT. It adds 72 tokens to every session and 1,787 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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