Borrowing it
Nothing to install: this file belongs to TenureAI/PhD-Zero. 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/TenureAI/PhD-Zero/main/.agents/skills/research-workflow/SKILL.mdgit clone --depth 1 https://github.com/TenureAI/PhD-ZeroWrote 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/skills/tenureai/phd-zero/research-workflow)<a href="https://agentmods.dev/skills/tenureai/phd-zero/research-workflow"><img src="https://agentmods.dev/badge/skills/tenureai/phd-zero/research-workflow/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/skills/tenureai/phd-zero/research-workflow"><img src="https://agentmods.dev/badge/skills/tenureai/phd-zero/research-workflow.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 | $0.00127 | $0.04362 |
| Opus 5.5 | $0.00051 | $0.01745 |
| Sonnet 5.5 | $0.00025 | $0.00872 |
| Haiku 4.5 | $0.00013 | $0.00436 |
Grade A, and why
research-workflow 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 1mo 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 — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Workflow
Mission
Drive AI R&D tasks with small, testable, evidence-first steps while supporting durable long-running execution, aggressive experience retrieval, and DR-first external search.
Orchestration Order
CRITICAL: Each step below that names a skill MUST be executed by calling Skill(skill: "<name>"). Do NOT simulate or skip the skill — actually invoke it via the Skill tool. Producing output that a skill should produce without invoking that skill is a workflow violation.
For non-trivial tasks, run this order:
Skill(skill: "run-governor")— Initialize run policy (mode + run_id) and reconcile active long actions before any execution.Skill(skill: "project-context")— Resolve runtime context before experiment/report/eval execution. MUST call when env setup is needed.- Understand user objective and current code/evidence state.
Skill(skill: "human-checkpoint")— Clarify ambiguous requirements. MUST call when intake is incomplete.- Complete intake checkpoint before planning or decomposition.
Skill(skill: "memory-manager")— Run bootstrap retrieval and initialize durable working state. MUST call before planning.Skill(skill: "deep-research")— Use as the default external search gateway whenever outside evidence is needed, and always when research-intent keywords appear.Skill(skill: "research-plan")— Build execution plan. MUST call for planning-heavy requests or after deep-research scoping.- Confirm plan as required by mode.
Skill(skill: "experiment-execution")— Execute experiment. MUST call for any actual run/launch/monitor.- Replan on major issues when needed.
- Emit stage reports and maintain report index.
Skill(skill: "memory-manager")— Close-out writeback. MUST call before task completion.Skill(skill: "paper-writing")— Write paper deliverable. MUST call only when user explicitly asks for paper output.
Mode-Aware Interaction Policy
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 392 lines · 127 tokens per session scan A 0875ab40cd31
research-workflow is a skill published in the GitHub repository TenureAI/PhD-Zero (53 stars, last pushed 7mo ago), licensed MIT. It adds 127 tokens to every session and 4,362 once invoked, about $0.0005 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.
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