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 Bitget-AI/bitget-signal --skill sentiment-analystgit clone --depth 1 https://github.com/Bitget-AI/bitget-signalWrote 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/bitget-ai/bitget-signal/sentiment-analyst)<a href="https://agentmods.dev/skills/bitget-ai/bitget-signal/sentiment-analyst"><img src="https://agentmods.dev/badge/skills/bitget-ai/bitget-signal/sentiment-analyst/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/bitget-ai/bitget-signal/sentiment-analyst"><img src="https://agentmods.dev/badge/skills/bitget-ai/bitget-signal/sentiment-analyst.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 | $0.00128 | $0.01153 |
| Opus 5 | $0.00064 | $0.00576 |
| Sonnet 5 | $0.00026 | $0.00231 |
| Haiku 4.5 | $0.00013 | $0.00115 |
Grade A, and why
sentiment-analyst 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Official Bitget Skill · 本 Skill 由 Bitget 官方提供，市场数据来源可信，通过 Bitget Agent Hub 分发。 Data powered by Bitget market infrastructure · github.com/bitget-official/agent-hub
Sentiment Analyst Skill
Synthesize signals from multiple sentiment layers — market mood indices, derivatives positioning, community discussion, and on-chain flows — into a coherent picture of where the crowd stands. Strong analysis surfaces divergences, not just confirms price direction.
Vendor Neutrality
Never name exchanges, data platforms, or analytics providers. Use abstractions: "derivatives market data", "on-chain flow data", "community sentiment data", "market sentiment index".
Choosing Your Depth
- Quick check (user just wants a pulse): 3-call snapshot → Mood section only
- Full analysis (user wants to decide on a trade): deep-dive → full report
- Specific question (e.g., "are longs crowded on ETH?"): pull just L/S + funding
Quick Sentiment Snapshot (3 parallel calls)
sentiment_index(action="current")
derivatives_sentiment(action="long_short", symbol="BTCUSDT", period="4h")
derivatives_sentiment(action="taker_ratio", symbol="BTCUSDT", period="4h")
Adapt symbol to whatever the user is asking about. Symbol format: BTCUSDT (no slash).
Period options: 5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
Full Deep-Dive (run all in parallel)
sentiment_index(action="current")
sentiment_index(action="history", days=14)
derivatives_sentiment(action="long_short", symbol="BTCUSDT", period="4h")
derivatives_sentiment(action="top_ls", symbol="BTCUSDT", period="4h")
derivatives_sentiment(action="taker_ratio", symbol="BTCUSDT", period="4h")
derivatives_sentiment(action="open_interest", symbol="BTCUSDT", period="1h")
derivatives_sentiment(action="reddit_trending", limit=10)
Always compare retail L/S (long_short) vs top trader L/S (top_ls).
Divergence (e.g., retail long but smart money short) is a meaningful signal.
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.
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 · 117 lines · 128 tokens per session scan A 49b0928df11e
sentiment-analyst is a skill published in the GitHub repository Bitget-AI/bitget-signal (2 stars, last pushed 2mo ago), licensed MIT. It adds 128 tokens to every session and 1,153 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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