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.
npx agentmods add skills/yennanliu/investskill/technical-analysisnpx skills add yennanliu/InvestSkill --skill technical-analysisgit clone --depth 1 https://github.com/yennanliu/InvestSkillWhat 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 | $0.00009 | $0.07241 |
| Opus 5 | $0.00005 | $0.03621 |
| Sonnet 5 | $0.00002 | $0.01448 |
| Haiku 4.5 | $0.00001 | $0.00724 |
Grade A, and why
technical-analysis 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 3d 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 — 634 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Analysis
⚠️ Data Verification — Do This Before Any Analysis
Before running any analysis, always retrieve the latest market data for the ticker:
- Fetch current price — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data.
- Confirm key figures — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill.
- State your data source — note where the numbers came from (e.g., "Google Finance, June 19 2026") at the top of the output.
- Flag stale data explicitly — if live data is unavailable, display this warning before proceeding:
⚠️ Live data unavailable. The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.
Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.
Perform technical analysis of US stocks using price action, chart patterns, and technical indicators.
Chart Pattern Analysis
-
Trend Identification
- Primary trend (uptrend, downtrend, sideways)
- Trend strength and momentum
- Support and resistance levels
- Trendline analysis
-
Classic Chart Patterns
- Head and shoulders, inverse H&S
- Double/triple tops and bottoms
- Cup and handle
- Triangles (ascending, descending, symmetrical)
- Flags and pennants
- Wedges and channels
-
Candlestick Patterns
- Reversal patterns (doji, hammer, shooting star, engulfing)
- Continuation patterns
- Multi-candle formations
Technical Indicators
-
Trend Indicators
- Moving averages (SMA, EMA: 20, 50, 200-day)
- Moving average crossovers
- MACD (Moving Average Convergence Divergence)
- ADX (Average Directional Index)
-
Momentum Indicators
- RSI (Relative Strength Index)
- Stochastic oscillator
- Williams %R
- Rate of Change (ROC)
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.
- 3d ago First seen · 634 lines · 9 tokens per session scan A f6fef29872d1
technical-analysis is a skill published in the GitHub repository yennanliu/InvestSkill (196 stars, last pushed 3d ago), licensed MIT. It adds 9 tokens to every session and 7,241 once invoked, about $0.0000 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 2026-08-30.
Other skills, from other repositories
dcf-model
DCF valuation: free cash flow projections, WACC, terminal value, sensitivity analysis.
initiating-coverage
Full equity research initiation: company research, financial model, valuation, charts, 30-50 page report.
comps-analysis
Comparable company analysis: operating metrics, valuation multiples, peer benchmarking.
ui-design
Design-quality reference for financial-research visual output: typography, color, composition, and avoiding generic AI aesthetics.
onboarding
First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.
user-profile
Manage user profile including watchlists, portfolio, and preferences.