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 skills add ntaffzii/Skill-Agents --skill market-breadth-analyzergit clone --depth 1 https://github.com/ntaffzii/Skill-AgentsWrote 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/ntaffzii/skill-agents/market-breadth-analyzer)<a href="https://agentmods.dev/skills/ntaffzii/skill-agents/market-breadth-analyzer"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/market-breadth-analyzer/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/ntaffzii/skill-agents/market-breadth-analyzer"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/market-breadth-analyzer.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 | $0.00127 | $0.00962 |
| Opus 5 | $0.00063 | $0.00481 |
| Sonnet 5 | $0.00025 | $0.00192 |
| Haiku 4.5 | $0.00013 | $0.00096 |
Grade A, and why
market-breadth-analyzer 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 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.
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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Breadth Analyzer
Overview
A cap-weighted index (S&P 500, Nasdaq) can rise while most individual stocks fall — a handful of large names carry the average. Breadth measures actual participation: what fraction of a universe is trading above a given moving average. This skill computes that from a CSV the user already has (or pastes), so it works with no paid market-data API.
Not financial advice. This is a descriptive statistic over data you supply. A single breadth reading in isolation is a weak signal — see Known limitations.
When to use
- เช็คว่าตลาดกำลังขึ้นแบบกว้าง (broad) หรือขึ้นแค่ไม่กี่ตัว (narrow)
- Scoring a watchlist or index-constituent CSV for % above 50-day/200-day moving average
- Part of a daily/weekly market-regime check (pairs naturally with uptrend-analyzer and exposure-coach)
When NOT to use
- The user wants an actual buy/sell signal from one breadth reading — breadth informs market posture, it is not a trade trigger on its own
- No price/MA data is available at all and the user isn't willing to supply even a rough CSV — this skill has nothing to compute on
Core knowledge
Definition: breadth % = (number of tickers with price > moving average) / (total tickers with valid data) × 100. Most common MA choices: 50-day (shorter-term participation) and 200-day (longer-term trend participation).
Rough interpretation bands (starting heuristic, not calibrated — tune against your own universe's history):
| Breadth % | Reading |
|---|---|
| ≥ 70% | Broad participation |
| 50-69% | Moderate participation |
| 30-49% | Narrow participation |
| < 30% | Weak participation |
Data-quality handling: rows with missing or non-numeric price/MA values are excluded and reported, not silently treated as "below the MA" — folding bad data into the score in either direction would quietly bias the result.
Common mistakes
- Treating a single breadth reading as a standalone buy/sell signal instead of one input to overall market posture.
- Silently dropping rows with bad data instead of excluding-and-reporting them — this can shift the percentage without anyone noticing.
- Comparing breadth readings computed against different MAs (50-day vs. 200-day) as if they measure the same thing — always state which MA a given percentage refers to.
- Assuming
price == macounts as "above" — this implementation uses strict>, so an exact match counts as not-above; be explicit about that boundary when reporting results.
What ships with it
1 file 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.
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.
- 8d ago First seen · 62 lines · 127 tokens per session scan A e10f39868b2c
market-breadth-analyzer is a skill published in the GitHub repository ntaffzii/Skill-Agents (4 stars, last pushed today), licensed MIT. It adds 127 tokens to every session and 962 once invoked, about $0.0006 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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