Borrowing it
Nothing to install: this file belongs to vakovalskii/phantom-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vakovalskii/phantom-agent/main/AGENTS.mdgit clone --depth 1 https://github.com/vakovalskii/phantom-agentWrote 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/vakovalskii/phantom-agent/agents-md)<a href="https://agentmods.dev/instructions/vakovalskii/phantom-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/vakovalskii/phantom-agent/agents-md/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/instructions/vakovalskii/phantom-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/vakovalskii/phantom-agent/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00637 | $0.00637 |
| Opus 5.5 | $0.00255 | $0.00255 |
| Sonnet 5.5 | $0.00127 | $0.00127 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade A, and why
phantom-agent 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 2mo 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS
This subtree contains the PAC1 Python contest agent. Optimize for correctness, small surface area, and low dependency count.
Local Goals
- Keep the implementation minimal and runnable with the packages already present in
pyproject.toml. - Reuse the generated BitGN SDK and protobuf types directly instead of wrapping everything in another framework.
- Avoid benchmark-id branching or task-id hardcoding unless there is no protocol-level alternative.
- Prefer generic file-system reasoning over PAC1-specific heuristics.
- Prefer capability discovery plus broad intent classes over phrase-specific routing. Narrow keyword heuristics are a last-resort fallback, not the primary architecture.
Preferred Structure
server.py: FastAPI backend + SSE streaming + benchmark orchestrationmain_v2.py: CLI benchmark runner (headless)agent_v2/agent.py: agent creation, run loop with retry logicagent_v2/tools.py: tool definitions (file ops, search, skills, completion)agent_v2/skills/: 12 specialized skill prompts (hot-reloadable.mdfiles)agent_v2/system_prompt.md: system prompt (hot-reloadable)agent_v2/config.py: env parsing and defaultsagent_v2/runtime.py: async PCM gRPC dispatchagent_v2/hooks.py: live logging + token trackingagent_v2/db.py: SQLite persistencedashboard/: React + Vite frontend
Implementation Rules
- Keep the loop deterministic and bounded.
- Bootstrap with explicit grounding calls before the free-form task loop.
- Preserve a generic command vocabulary based on runtime capabilities: tree, list, read, search, write, move, delete, mkdir, context, answer.
- Format tool outputs in stable shell-like shapes when that improves model grounding.
- Keep completion reporting explicit and typed.
- Put tunables behind environment variables or small constants, not string literals scattered through the code.
- Prefer extraction of tiny pure helpers over repeated inline formatting logic.
- Use BDD for policy and loop changes. Express scenarios as
Given / When / Then, then implement deterministic tests for those scenarios with minimal tooling. - Treat contest paths as case-sensitive. Reuse the exact casing returned by the runtime and try known filename variants only when the policy intentionally supports them.
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.
- 2mo ago First seen · 53 lines · 637 tokens per session scan A bd1f2d7249fd
phantom-agent AGENTS.md is an instructions file published in the GitHub repository vakovalskii/phantom-agent (32 stars, last pushed 6mo ago), licensed MIT. It adds 637 tokens to every session, about $0.0025 per session on Opus 5.5. 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.
phantom-agent AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| phantom-agent AGENTS.mdvakovalskii/phantom-agent | Instructions file | 32 | 6mo ago | MIT | A | 637 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |