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 Senpi-ai/senpi-skills --skill senpi-trading-runtimegit clone --depth 1 https://github.com/Senpi-ai/senpi-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/senpi-ai/senpi-skills/senpi-trading-runtime)<a href="https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-trading-runtime"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-trading-runtime/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/senpi-ai/senpi-skills/senpi-trading-runtime"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-trading-runtime.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 | $0.00157 | $0.01789 |
| Opus 5 | $0.00078 | $0.00894 |
| Sonnet 5 | $0.00031 | $0.00358 |
| Haiku 4.5 | $0.00016 | $0.00179 |
Grade A, and why
senpi-trading-runtime 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 yesterday.
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Senpi Trading Runtime — the runtime contract
This skill is infrastructure: the canonical knowledge of how the Senpi runtime
(@senpi-ai/runtime) behaves and how a strategy interacts with it. The lifecycle skills —
author (build), ops (install/monitor), discover (recommend) — reference this one for the contract.
The runtime model
A strategy runs from a runtime.yaml that points at an in-repo Python module. The runtime spawns and
supervises that module and calls a frozen scan(inputs, ctx) every interval_seconds. The
division of labor is fixed:
- Your code produces signals — nothing else.
scan(inputs, ctx)reads market and account data and returns alist[dict]of candidate signals. It does not open, close, size, schedule, or execute anything. - The runtime owns everything downstream: scheduling (
interval_seconds), spawning + supervising + restarting the scanner, validating (signal_data_schema) + de-duplicating the signals you return, sizing & order execution (FEE_OPTIMIZED_LIMIT), slot accounting,risk.guard_rails, the two-phase DSL trailing-stop exits, and crash-safe position reconcile on restart.
How your code talks to the runtime
The interaction surface is small and one-directional — you read, you return signals, the runtime acts.
runtime.yamldeclares the scanner(s), the action gate, the exit engine, and the risk guard-rails, and passes author tunables down viainputs:. →references/runtime-yaml.mdscan(inputs, ctx)is the single entry point.inputsis the runtime'sinputs:map;ctxgives you:ctx.senpi_mcp.call_tool(name, args)— the Senpi MCP client, read-only (market, account, leaderboard, discovery,strategy_get*, …). It is the only way to fetch data.ctx.state— transactional, runtime-persisted history (last()/append()/len) for dedup, rotation, and first-seen ledgers; advances only on a clean tick.ctx.wallet— the strategy's wallet address.- →
references/scan-contract.md
- The return value is a
list[dict], one per candidate signal (asset,direction,marginPct,leverage,data{}). The runtime validates eachdata{}against the runtime.yaml'ssignal_data_schema, then sizes, executes, and manages exits.
What ships with it
9 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.
- references/dsl-protection-check.md 5.0 KB
- references/runtime-cli.md 14 KB
- references/runtime-concepts.md 15 KB
- references/runtime-yaml.md 16 KB
- references/scan-contract.md 13 KB
- scripts/gen_catalog.py 13 KB runs code
- scripts/min_budget.py 8.8 KB runs code
- tests/fixtures/min_budget_golden.json 1.7 KB
- tests/test_min_budget_golden.py 2.6 KB runs code
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.
- yesterday Changed 46dc3afd76ca
- 12d ago First seen · 114 lines · 157 tokens per session scan A a7308b6c8df2
senpi-trading-runtime is a skill published in the GitHub repository Senpi-ai/senpi-skills (123 stars, last pushed today), licensed MIT. It adds 157 tokens to every session and 1,789 once invoked, about $0.0008 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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