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 instructions/ttxttx1111/sts2-llm/copilot-instructionsgit clone --depth 1 https://github.com/ttxttx1111/sts2-llmWrote 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/instructions/ttxttx1111/sts2-llm/copilot-instructions)<a href="https://agentmods.dev/instructions/ttxttx1111/sts2-llm/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/ttxttx1111/sts2-llm/copilot-instructions.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 | $0.01234 | $0.01234 |
| Opus 5 | $0.00617 | $0.00617 |
| Sonnet 5 | $0.00247 | $0.00247 |
| Haiku 4.5 | $0.00123 | $0.00123 |
Grade A, and why
sts2-llm copilot-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 4d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot instructions for this repository
This repository is a GitHub Copilot customization pack for a Slay the Spire 2 player agent, not an application codebase.
Source of truth for customizations
- Put direct-open agents in
.github/agents/ - Put reusable skills in
.github/skills/<skill-name>/ - Put persistent STS2 run memory in
.github/sts2-memory/ - Put shared VS Code MCP server configuration in
.vscode/mcp.json
Runtime assumptions
- The local game install is expected at
D:\program\steam\steamapps\common\Slay the Spire 2\ - Gameplay control is provided by the STS2MCP mod over
localhost:15526 - In VS Code, the shared MCP setup for this repo lives in
.vscode/mcp.json, which uses the VS Code-styleserverskey - In Copilot CLI, equivalent MCP access can come from a temporary current-session attach or from
/mcp add/~/.copilot/mcp-config.json; the CLI home config usesmcpServers - A custom agent or skill may load successfully even when the current session does not have STS2 MCP tools attached; in that case live piloting must stop at the MCP-readiness check and report the blocker plainly
- In Copilot CLI, if the current session already has STS2 MCP tools attached, treat that as good enough to play immediately rather than insisting on persistence first
- In Copilot CLI, if live STS2 piloting must also work in a fresh session or custom agent, prefer a persistent MCP configuration that is available at session start rather than relying on another session's MCP attachment
- When the only missing piece is that persistent CLI MCP config and the agent can edit local files, prefer repairing
~/.copilot/mcp-config.jsondirectly before asking the user to do manual setup
Authoring rules for this repo
- Keep skills and agent instructions reusable; do not hardcode a single run, seed, or class unless the file is explicitly scoped that way
- Prefer official Copilot customization formats and frontmatter; do not invent custom control files or ad-hoc schemas
- Encode gameplay guidance as evidence-backed heuristics, and clearly separate general rules from class-specific or relic-specific advice
- Record meaningful design decisions and behavior changes in repo documentation so the reasoning behind updates stays traceable
- Keep a concise update log whenever the player workflow changes materially, so the final merged documentation can be assembled from a clear change history
- Treat
.github/design/README.mdand.github/design/system-details.mdas the maintained entrypoints for current architecture and workflow design - Write changelog entries under
.github/changelog/with one markdown file per feature or workflow change plus an updated.github/changelog/README.mdindex - Do not use
prepare_task/as the long-term source of truth for feature history; leaveprepare_task/change-log.mdas a compatibility pointer only - When changing overall workflow, memory structure, review rules, skill boundaries, or agent orchestration, update the design docs in
.github/design/ - When the workspace is a git repository, make coherent commits for completed milestones instead of leaving important design and workflow changes ungrouped
- Preserve the distinction between:
- always-on instructions (
copilot-instructions.md) - reusable capabilities (
skills) - persistent persona/tooling (
custom agents)
- always-on instructions (
- Assume the user may interact in Chinese; default to concise Chinese unless the user switches languages
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.
- 4d ago First seen · 60 lines · 1,234 tokens per session scan A 7eaa9c98ef57
sts2-llm copilot-instructions.md is an instructions file published in the GitHub repository ttxttx1111/sts2-llm (41 stars, last pushed 1mo ago), licensed MIT. It adds 1,234 tokens to every session, about $0.0062 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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