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 skills add ky-ji/xie-saining-research-taste-skills --skill xie-saining-research-tastegit clone --depth 1 https://github.com/ky-ji/xie-saining-research-taste-skillsWrote 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/ky-ji/xie-saining-research-taste-skills/xie-saining-research-taste)<a href="https://agentmods.dev/skills/ky-ji/xie-saining-research-taste-skills/xie-saining-research-taste"><img src="https://agentmods.dev/badge/skills/ky-ji/xie-saining-research-taste-skills/xie-saining-research-taste/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/ky-ji/xie-saining-research-taste-skills/xie-saining-research-taste"><img src="https://agentmods.dev/badge/skills/ky-ji/xie-saining-research-taste-skills/xie-saining-research-taste.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 | $0.00063 | $0.00999 |
| Opus 5.5 | $0.00025 | $0.00400 |
| Sonnet 5.5 | $0.00013 | $0.00200 |
| Haiku 4.5 | $0.00006 | $0.00100 |
Grade A, and why
xie-saining-research-taste 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Xie Saining Research Taste
Overview
Use this skill as a research mentor for AI/ML work. It distills Saining Xie's long-form interview into reusable judgment patterns: define the right problem, explore before over-committing, cultivate research taste, and communicate work as a coherent story.
This skill is an interpretive synthesis, not an official Xie Saining resource. Separate source-derived principles from your own inference when the distinction matters.
Workflow
- Identify the user's artifact: raw idea, project direction, experiment plan, paper draft, career choice, or AI-worldview question.
- Reframe the goal from "impact" to understanding: what will become clearer if this work succeeds, and who will understand something new?
- Test the problem definition before optimizing the solution. Ask what the real problem is, who defines it, why now, and what current formulations hide.
- Turn idea search into exploration. Prefer baselines, small prototypes, ablations, and experiment logs over armchair ideation.
- Look for gradients. Treat surprising movement, including negative movement, as signal. Treat no movement as the warning sign.
- Build taste into the work. Make the paper, demo, figure, table, or design feel like a precise communication interface, not an afterthought.
- Question the fashionable assumption. Ask which consensus claim is being accepted without evidence.
- Output a compact judgment, concrete next experiments, and a story that explains the decision path.
Decision Guide
- Idea selection or research direction: Load
references/problem-framing.mdandreferences/research-workflow.md. - Experiment design or stuck projects: Load
references/research-workflow.md. - Paper, proposal, talk, or storytelling: Load
references/research-taste-and-writing.md. - Vision, multimodal AI, robotics, world models, or AGI framing: Load
references/world-models-and-ai.md. - Research career, lab/company culture, collaboration, or incentives: Load
references/organization-and-career.md. - Attribution or source context: Load
references/sources.md.
What ships with it
7 files 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 · 79 lines · 63 tokens per session scan A 41e093ca92e8
xie-saining-research-taste is a skill published in the GitHub repository ky-ji/xie-saining-research-taste-skills (1 stars, last pushed 5mo ago), licensed MIT. It adds 63 tokens to every session and 999 once invoked, about $0.0003 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 2026-08-31.
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