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/gigshow/decker-ai/decker-developernpx skills add gigshow/decker-ai --skill decker-developergit clone --depth 1 https://github.com/gigshow/decker-aiWrote 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/gigshow/decker-ai/decker-developer)<a href="https://agentmods.dev/skills/gigshow/decker-ai/decker-developer"><img src="https://agentmods.dev/badge/skills/gigshow/decker-ai/decker-developer.svg" alt="Measured on agentmods" 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 | $0.00066 | $0.01416 |
| Opus 5 | $0.00033 | $0.00708 |
| Sonnet 5 | $0.00013 | $0.00283 |
| Haiku 4.5 | $0.00007 | $0.00142 |
Grade A, and why
decker-developer scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -H "X-API-Key: dk_live_..." \ How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decker Developer API 스킬
Goal
개발자가 Decker Public API를 연동하는 데 필요한 키 발급·인증·엔드포인트·Rate Limit 안내.
1. API 키 발급 (무료)
전체 흐름 (3단계):
- decker-ai.com 회원가입
- 로그인 → 설정 → 텔레그램 → 연동 코드 발급 → 텔레그램
/start {코드} - 텔레그램 @deckerclawbot 에서:
/apikey
→ dk_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 발급
/apikey reset— 기존 키 폐기 후 재발급.- 키는 한 번만 전체 표시. 분실 시
/apikey reset.
Tier: 기본 FREE (30 req/day). 상위 플랜 문의는 텔레그램.
2. 인증 헤더
모든 Public API 요청에 헤더 추가:
X-API-Key: dk_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Base URL: https://api.decker-ai.com
3. Public Endpoints
GET /api/v1/public/signals/{symbol}/latest
최신 시그널 — 방향·진입가·목표가·손절가·진행률.
curl -H "X-API-Key: dk_live_..." \
"https://api.decker-ai.com/api/v1/public/signals/BTCUSDT/latest?timeframe=1h"
응답:
{
"symbol": "BTCUSDT",
"timeframe": "1h",
"direction": "long",
"entry_price": 94200.0,
"target_price": 97500.0,
"stop_loss": 92800.0,
"current_price": 95100.0,
"progress_pct": 27.3,
"generated_at": "2026-04-23T09:00:00+00:00"
}
timeframe 가능값: 15m, 30m, 1h, 4h, 8h, 1d, 1w
operation_gate: GO = 진입 신호 / WATCH = 관측 중 / HOLD = 대기 (GO만 진입 권고)
GET /api/v1/public/signals/{symbol}/narrative
규칙 기반 구조 서사 — LLM 비용 없음, deterministic.
curl -H "X-API-Key: dk_live_..." \
"https://api.decker-ai.com/api/v1/public/signals/BTCUSDT/narrative?timeframe=4h"
응답:
{
"symbol": "BTCUSDT",
"timeframe": "4h",
"narrative": "BTC 4h: A-사이클 진행 중, 트리거 활성 — 상승 1단계 목표 유효.",
"axis": "bullish",
"generated_at": "2026-04-23T08:00:00+00:00"
}
4. Rate Limit
| Tier | 일일 한도 | 비고 |
|---|---|---|
| FREE | 30 req/day | 웹 Settings→API Keys · 텔레그램 /apikey |
| PRO | 1,000 req/day | $20/mo |
| ENTERPRISE | 100,000 req/day | 문의 |
429 응답 시 내일 리셋. 헤더: X-RateLimit-Remaining.
5. 시그널 소스 투명성
Public API는 engine:live_l1 소스만 반환한다.
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 · 170 lines · 66 tokens per session scan A 72a04f236b4a
decker-developer is a skill published in the GitHub repository gigshow/decker-ai (3 stars, last pushed 3d ago), licensed MIT. It adds 66 tokens to every session and 1,416 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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