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/tenureai/phd-zero/agents-mdgit clone --depth 1 https://github.com/TenureAI/PhD-ZeroWhat 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 | $0.03031 | $0.03031 |
| Opus 5 | $0.01515 | $0.01515 |
| Sonnet 5 | $0.00606 | $0.00606 |
| Haiku 4.5 | $0.00303 | $0.00303 |
Grade A, and why
PhD-Zero 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 yesterday.
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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI R&D Workspace
This workspace is for AI research and development tasks (reproduction, debugging, evaluation, training, and experiment planning).
⚠ Mandatory Skill Routing — MUST follow, violations are NOT acceptable
Every non-trivial task MUST go through the skill pipeline via the Skill tool. Do NOT answer research questions, run experiments, or write papers by generating freeform text without first invoking the corresponding skill.
Routing Order (execute top-down, stop at the first matching rule)
research-workflow(PRIMARY ORCHESTRATOR) — invoke FIRST for any non-trivial task. All downstream skills below should be invoked FROM WITHIN research-workflow, not standalone.deep-research— MANDATORY when user message contains ANY research-intent keyword:- Chinese: 调研/研究/对比/综述/文献/证据/机制/根因/为什么/可行性/路线图/分析/探索
- English: research/investigate/compare/survey/literature/evidence/mechanism/root-cause/why/feasibility/roadmap/analyze/explore
- If ANY keyword matches → you MUST invoke
deep-research. No exceptions. Skipping is a routing violation.
experiment-execution— when user asks to run/launch/start/resume/monitor an experiment.research-plan— when user asks for a proposal, roadmap, ablation plan, or study design.paper-writing— ONLY when user explicitly asks to draft/write/revise a paper or section.project-context— when environment setup or runtime fields are needed before execution.run-governor— at run start to set mode + run_id.memory-manager— bootstrap at run start, writeback at task end, trigger-based in between.human-checkpoint— for safety risks, high-resource approvals, or hard blockers.
Self-Check Before Every Reply
Before producing any substantive response, you MUST run this mental checklist:
- Is this task non-trivial? → If yes, did I invoke
research-workflow? If not, invoke it NOW. - Does the user message contain any research-intent keyword from rule 2? → If yes, did I invoke
deep-research? If not, invoke it NOW. - Am I about to answer a research question with freeform text instead of skill output? → STOP. Invoke the skill first.
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.
- yesterday First seen · 179 lines · 3,031 tokens per session scan A 1d441ec93652
PhD-Zero AGENTS.md is an instructions file published in the GitHub repository TenureAI/PhD-Zero (52 stars, last pushed 5mo ago), licensed MIT. It adds 3,031 tokens to every session, about $0.0152 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.
Other instructions, from other repositories
nano-scientist CLAUDE.md
Claude Code instructions for AI4Scientist/nano-scientist, covering claude.md, project, run, pipeline and architecture.
Auto-Research-Skills AGENTS.md
Instructions for brycewang-stanford/Auto-Research-Skills, covering agent coordination, before editing, generated files, validation and handoff.
dr-claw AGENTS.md
AGENTS.md instructions for OpenLAIR/dr-claw, covering dr. claw repository guidance, repository map, skill-library routing, durable constraints and validation.
lite-research-agents AGENTS.md
Instructions for frankaging/lite-research-agents, covering codex cli — research agent boot contract, on startup, sandbox rule, invoking skills and no subagent spawning.
lite-research-agents CLAUDE.md
Instructions for frankaging/lite-research-agents, covering claude code — research agent boot contract, on startup, sandbox rule, invoking skills and no external processes.
she-love-me CLAUDE.md
Instructions for 863401402/she-love-me, covering claude.md and 唯一工作流.