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/cesarfrancots/xolotl-code/agents-mdgit clone --depth 1 https://github.com/cesarfrancots/Xolotl-CodeWhat 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 | $0.00854 | $0.00854 |
| Opus 5 | $0.00427 | $0.00427 |
| Sonnet 5 | $0.00171 | $0.00171 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade A, and why
Xolotl-Code AGENTS.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 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.
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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
graphify
This project has a graphify knowledge graph at graphify-out/.
Rules:
- Before answering architecture or codebase questions, read graphify-out/GRAPH_REPORT.md for god nodes and community structure
- If graphify-out/wiki/index.md exists, navigate it instead of reading raw files
- After modifying code files in this session, run
graphify update .to keep the graph current (AST-only, no API cost)
Model Harness Configuration
Supported Models
| Alias | Provider | Endpoint | Context | Thinking |
|---|---|---|---|---|
kimi-coding |
Kimi Coding | api.kimi.com/coding/v1 |
256K | Yes (32K budget) |
kimi2.6 |
Moonshot | api.moonshot.cn/v1 |
256K | Yes |
minimax2.7 |
MiniMax | api.minimax.chat/v1 |
1M | Yes |
deepseek |
DeepSeek | api.deepseek.com |
1M | Yes |
glm5.1 |
Zhipu GLM | open.bigmodel.cn/api/paas/v4 |
128K | Yes |
qwen3.6 |
Alibaba Qwen | dashscope.aliyuncs.com/compatible-mode/v1 |
128K | Yes |
sonnet |
AWS Bedrock | bedrock-runtime.us-east-1.amazonaws.com |
200K | Yes |
opus |
AWS Bedrock | bedrock-runtime.us-east-1.amazonaws.com |
200K | Yes |
Environment Variables
KIMI_CODING_API_KEY- Kimi K2.6 Coding API (coding-optimized model)KIMI_API_KEY- Standard Kimi / Moonshot APIMINIMAX_API_KEY- MiniMax APIDEEPSEEK_API_KEY- DeepSeek APIGLM_API_KEY- Zhipu GLM APIDASHSCOPE_API_KEY- Alibaba Qwen APIANTHROPIC_API_KEY- Anthropic direct APIBEDROCK_API_KEY- AWS Bedrock API key
Model-Specific Behavior
Kimi K2.6 Coding:
- Uses extended thinking with 32K budget
- Optimized system prompt for software engineering tasks
- Aggressive file reading (threshold: 12 files)
- Higher compaction ratio (0.7) due to 256K context
MiniMax 2.7:
- 1M token context - most generous for large codebases
- Aggressive file reading (threshold: 10 files)
- Prefers comprehensive initial research
DeepSeek V4:
- 1M token context
- Thinking mode enabled by default;
maxeffort is available - Good fit for chat, evals, and agentic coding tasks
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 · 90 lines · 854 tokens per session scan A 03d152f930c1
Xolotl-Code AGENTS.md is an instructions file published in the GitHub repository cesarfrancots/Xolotl-Code (5 stars, last pushed 2mo ago), licensed MIT. It adds 854 tokens to every session, about $0.0043 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 2026-08-31.
Other instructions, from other repositories
openinterpreter AGENTS.md
Instructions for openinterpreter/openinterpreter, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
dsh-TUI AGENTS.md
AGENTS.md instructions for ccch1mneyyy/dsh-TUI, covering agents.md, 仓库布局, 命令, 上游边界与契约 and 约定与红线.
golembot CLAUDE.md
Instructions for 0xranx/golembot, covering golembot — project conventions for claude code, architecture hard constraints, things you must never do, interface change rules and file responsibility boundaries.
sortie copilot-instructions.md
Instructions for sortie-ai/sortie, covering sortie coding & review standards, 1. layered imports (downward only; violation is critical), 2. concurrency safety, 3. workspace path safety (critical: security boundary) and 4. persistence (sqlite).
copperhead CLAUDE.md
Instructions for copperheadhq/copperhead, covering claude.md, what this repo is, sources of truth, workflow (openspec) and architecture (per spec.md §2).
pi-ask AGENTS.md
Instructions for eko24ive/pi-ask, covering agents.md, project scope, project goals, tech stack and commands.