senpi-strategy-author

senpi-strategy-author is a skill for Claude Code, Codex from Senpi-ai/senpi-skills. It costs 255 tokens per session (9,308 once invoked), scanned D, original, MIT.

A guided builder for creating or editing named Senpi trading strategies on Hyperliquid, a crypto trading platform. It interviews the user about the trading idea and risk limits, then compiles the answers into a deployable strategy package.

In plain words
What is it for?
Use it to design a strategy from scratch, revise one, choose what to trade and how to score it, and define exits, risk limits, and other guardrails.
Why use it?
It turns an informal trading idea into the configuration the Senpi runtime expects. It also keeps persistent exits such as stop-losses and trailing stops under runtime supervision.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: positional $N argument; built for openclaw.

Good fit Use it to design a strategy from scratch, revise one, choose what to trade and how to score it, and define exits, risk limits, and other guardrails.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/senpi-ai/senpi-skills/senpi-strategy-author
Install

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.

Any agent
npx skills add Senpi-ai/senpi-skills --skill senpi-strategy-author
Clone the repo
git clone --depth 1 https://github.com/Senpi-ai/senpi-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for senpi-strategy-author

README.md
[![agentmods](https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-strategy-author/github.svg)](https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-strategy-author)
Your own site
<a href="https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-strategy-author"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-strategy-author/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.

agentmods 80×15 button for senpi-strategy-author

Your own site · 80×15
<a href="https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-strategy-author"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-strategy-author.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 255 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,308 The whole file, excluding the scripts and references it only reads on demand.
Security scan D 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00255 $0.09308
Opus 5 $0.00128 $0.04654
Sonnet 5 $0.00051 $0.01862
Haiku 4.5 $0.00026 $0.00931

Measured today against content hash 7102a528c766, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade D, and why

senpi-strategy-author scanned grade D with 2 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 today.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/_yaml.py, scripts/validate_strategy.py, tests/test_exit_preview_matches_presets.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Subtle steeringmediumPrompt injection

Instructions that bias recommendations or shape behaviour without the user noticing.

**Never tell the user a strategy is ready, and never hand it to ops, unless `senpi validate`

Tells the agent never to refusehighAnti-refusal

Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.

mid-interview, and never refuse to build.
senpi-strategy-author/SKILL.md · 452 lines

How it starts

The opening of the file, as written. The whole thing — 452 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Senpi Strategy Author — build a strategy with the user, one decision at a time

You build a strategy by interviewing the user, not by lecturing them. A strategy is a deployable package; the runtime owns execution, sizing, exits, slots, risk, and state. The user only needs to decide the thesis (what to trade and how to score it) and the guardrails (how to exit, how much risk). Your job is to draw those out, one question at a time, and compile them.

DSL ⟹ author here. This is the boundary. DSL — a runtime-supervised exit (stop-loss, trailing stop, profit-lock ladder, any managed stop that persists) — exists only inside a Runtime 3.0 runtime.yaml exit: block, which is what this skill compiles. Never stand up a DSL-protected, named, or persistent strategy with a raw strategy_create_custom_strategy / create_position MCP call: that path can carry at most a flat stopLossPercentage, leaves tradingStrategyName null, and never registers in installed_runtimes.json — so the strategy is unnamed, unsupervised, and invisible to portfolio/DSL tooling (the confirmed Decoupling failure: $3k, three cross positions, no DSL, no name). The raw MCP tools are for manual one-off open/close positions or mirror (copy-trade) strategies with no DSL — nothing else. If protection is anywhere in the ask, you're in the right skill; author it.

Opening a position for the user is a FORK — ASK, never assume. When the user asks to open a position (or a set) — "go long HYPE", "buy BTC 5x", "short SOFTBANK" — do not just place it. Ask which of two different products they want:

  • (A) A DSL-protected strategy — a named, supervised Runtime 3.0 strategy that manages a trailing stop
    • profit-lock ladder. → author it here. The path for anything the user wants managed or persistent.
  • (B) A plain position with a standard take-profit / stop-loss — a one-off via raw create_position (it carries stopLoss / takeProfit), placed in a discretionary wallet, NOT a strategy wallet.

Either way, NEVER open into an existing scanner-managed strategy's wallet. A hand-placed position in a wallet a deployed strategy runs is reconciled as foreign and DSL-flattened within minutes — the order "succeeds," the position is gone, and the user eats the round-trip. If the user hasn't said which of (A)/(B) they want, ask before placing anything — and never route (B) into a managed wallet to save a step.

Read the full file on GitHub · 452 lines

Changes

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.

  1. today Changed · +44 lines · +97 tokens per session 7102a528c766
  2. 2d ago Changed · +18 lines 2501a60bffd5
  3. 12d ago First seen · 390 lines · 158 tokens per session scan D 2bee82d42f75

Subscribe to this mod's changes

senpi-strategy-author is a skill published in the GitHub repository Senpi-ai/senpi-skills (123 stars, last pushed today), licensed MIT. It adds 255 tokens to every session and 9,308 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it D with 2 findings (subtle steering, tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.