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 agiprolabs/claude-trading-skills --skill birdeye-apigit clone --depth 1 https://github.com/agiprolabs/claude-trading-skillsWrote 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/agiprolabs/claude-trading-skills/birdeye-api)<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/birdeye-api"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/birdeye-api/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/agiprolabs/claude-trading-skills/birdeye-api"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/birdeye-api.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.02230 |
| Opus 5 | $0.00016 | $0.01115 |
| Sonnet 5 | $0.00006 | $0.00446 |
| Haiku 4.5 | $0.00003 | $0.00223 |
Grade A, and why
birdeye-api 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Birdeye API — Solana Market Data
Birdeye aggregates market data across all Solana DEXes (and 13 other chains). Prices, OHLCV candles, trade history, token metadata, security info, and wallet analytics. Primary data source for Solana token research and historical analysis.
Note: For real-time trading systems, use Yellowstone gRPC (see yellowstone-grpc skill). Birdeye is best for historical data, research, and analysis workflows.
Quick Start
1. Get an API Key
Sign up at birdeye.so — free tier: 30K compute units/month, 1 req/sec.
export BIRDEYE_API_KEY="your-api-key"
2. Install Dependencies
uv pip install httpx pandas python-dotenv
3. First Request
import httpx, os
API_KEY = os.environ["BIRDEYE_API_KEY"]
headers = {"X-API-KEY": API_KEY, "x-chain": "solana", "accept": "application/json"}
# Get SOL price
resp = httpx.get(
"https://public-api.birdeye.so/defi/price",
headers=headers,
params={"address": "So11111111111111111111111111111111111111112"},
)
price = resp.json()["data"]["value"]
print(f"SOL: ${price}")
Core Endpoints
All endpoints use base URL https://public-api.birdeye.so with X-API-KEY and x-chain headers.
Token Price
# Single token price (10 CU)
GET /defi/price?address=TOKEN_MINT
# Multiple token prices (variable CU)
POST /defi/multi_price
Body: {"addresses": ["MINT1", "MINT2", "MINT3"]}
# Price at specific timestamp (10 CU)
GET /defi/historical_price_unix?address=TOKEN_MINT&unixtime=1700000000
# Historical price series (60 CU)
GET /defi/history_price?address=TOKEN_MINT&address_type=token&type=15m&time_from=T1&time_to=T2
OHLCV Candles
The primary endpoint for backtesting data.
# Token OHLCV (40 CU, max 1000 candles per request)
GET /defi/ohlcv?address=TOKEN_MINT&type=15m&time_from=T1&time_to=T2
Timeframes: 1m, 3m, 5m, 15m, 30m, 1H, 2H, 4H, 6H, 8H, 12H, 1D, 3D, 1W, 1M
Response:
{
"data": {
"items": [
{"o": 23.5, "h": 24.1, "l": 23.2, "c": 23.8, "v": 1234567.89, "unixTime": 1692175200, "type": "15m"}
]
},
"success": true
}
What ships with it
5 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.
- 11d ago First seen · 254 lines · 32 tokens per session scan A 0ea1b2dad958
birdeye-api is a skill published in the GitHub repository agiprolabs/claude-trading-skills (354 stars, last pushed 8d ago), licensed MIT. It adds 32 tokens to every session and 2,230 once invoked, about $0.0002 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.
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