sts2-llm live-data.instructions.md

Live-data instructions for a Slay the Spire 2 player-agent project. They treat current state files and step history as evidence for diagnosing what happened during a run.

In plain words
What is it for?
Use them to investigate live problems, inspect the latest player-step files and history, distinguish a restart using scene and action evidence, and record durable lessons only after supporting evidence is saved.
Why use it?
They reduce mistakes caused by relying on old summaries or assuming a run restarted based only on a step counter.

Instructions file for GitHub Copilot

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.

agentmods
npx agentmods add instructions/ttxttx1111/sts2-llm/live-data
Clone the repo
git clone --depth 1 https://github.com/ttxttx1111/sts2-llm

Made for: GitHub Copilot.

Per session 151 This file is loaded in full into every session.
When invoked 151 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.00151 $0.00151
Opus 5 $0.00076 $0.00076
Sonnet 5 $0.00030 $0.00030
Haiku 4.5 $0.00015 $0.00015

Measured 2d ago against content hash f47f7c16607b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sts2-llm live-data.instructions.md 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 2d 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.

deprecated/3/ai-play-slts2-2/.github/instructions/live-data.instructions.md · 11 lines

What it actually says

live 数据指令

  • 把这些文件当作运行证据,不是手写说明文档。
  • 排查 live 问题时,优先看最新 data\live\latest-standalone-player-step.json 和最近的 standalone-player-step-history.jsonl,不要先看旧 summary。
  • 不要仅凭 step counter 判断“游戏重开了”,必须结合 scene / action 证据。
  • durable lesson 应该进入 data\python-runtime\knowledge\,而且前提是证据已经先写到别处。
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. 2d ago First seen · 11 lines · 151 tokens per session scan A f47f7c16607b

Subscribe to this mod's changes

sts2-llm live-data.instructions.md is an instructions file published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 1mo ago), licensed MIT. It adds 151 tokens to every session, 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.