phantom-agent: Instructions file for Codex

AGENTS.md

phantom-agent AGENTS.md is an instructions file for Codex, OpenCode from vakovalskii/phantom-agent. It costs 637 tokens per session, scanned A, original, MIT.

Repository instructions for the PAC1 Python contest agent in vakovalskii/phantom-agent. They describe its intended file structure, implementation priorities, dependency rules, and preferred reasoning approach.

In plain words
What is it for?
Use them when modifying the agent, FastAPI server, benchmark runner, tools, configuration, or hot-reloadable prompts in that repository.
Why use it?
They give the coding agent project-specific boundaries so changes stay small, runnable with existing packages, and based on general capabilities rather than task-specific shortcuts.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is vakovalskii/phantom-agent's own configuration. It tells Codex and OpenCode how to work on phantom-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything phantom-agent configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/vakovalskii/phantom-agent/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/vakovalskii/phantom-agent

Made for: Codex, OpenCode.

Wrote 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.

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README.md
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Your own site
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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.

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Per session 637 This file is loaded in full into every session.
When invoked 637 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $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

Measured 2mo ago against content hash bd1f2d7249fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

AGENTS.md · 53 lines

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 orchestration
  • main_v2.py: CLI benchmark runner (headless)
  • agent_v2/agent.py: agent creation, run loop with retry logic
  • agent_v2/tools.py: tool definitions (file ops, search, skills, completion)
  • agent_v2/skills/: 12 specialized skill prompts (hot-reloadable .md files)
  • agent_v2/system_prompt.md: system prompt (hot-reloadable)
  • agent_v2/config.py: env parsing and defaults
  • agent_v2/runtime.py: async PCM gRPC dispatch
  • agent_v2/hooks.py: live logging + token tracking
  • agent_v2/db.py: SQLite persistence
  • dashboard/: 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.

Read the full file on GitHub · 53 lines

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. 2mo ago First seen · 53 lines · 637 tokens per session scan A bd1f2d7249fd

Subscribe to this mod's changes

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.

Related

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