scientific-problem-selection

scientific-problem-selection is a skill for Claude Code, Codex from KunAgent/Kun. It costs 30 tokens per session (330 once invoked), scanned A, original, no licence file.

A research-planning tool for judging and ranking research questions by importance, originality, feasibility, evidence, resources, ethics, and testability. A research question is testable when evidence could show whether it is supported or not.

In plain words
What is it for?
Use it to select and prioritize research questions before investing time, resources, or experiments.
Why use it?
It helps researchers compare ideas instead of choosing only by interest or intuition. It brings practical limits and ethical concerns into the choice.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to select and prioritize research questions before investing time, resources, or experiments.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kunagent/kun/scientific-problem-selection
Install

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.

Any agent
npx skills add KunAgent/Kun --skill scientific-problem-selection
Clone the repo
git clone --depth 1 https://github.com/KunAgent/Kun

Made for: Claude Code, Codex.

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.

agentmods badge for scientific-problem-selection

README.md
[![agentmods](https://agentmods.dev/badge/skills/kunagent/kun/scientific-problem-selection/github.svg)](https://agentmods.dev/skills/kunagent/kun/scientific-problem-selection)
Your own site
<a href="https://agentmods.dev/skills/kunagent/kun/scientific-problem-selection"><img src="https://agentmods.dev/badge/skills/kunagent/kun/scientific-problem-selection/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.

agentmods 80×15 button for scientific-problem-selection

Your own site · 80×15
<a href="https://agentmods.dev/skills/kunagent/kun/scientific-problem-selection"><img src="https://agentmods.dev/badge/skills/kunagent/kun/scientific-problem-selection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 330 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin unknown 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 $0.00030 $0.00330
Opus 5 $0.00015 $0.00165
Sonnet 5 $0.00006 $0.00066
Haiku 4.5 $0.00003 $0.00033

Measured 3d ago against content hash 225148210a9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

scientific-problem-selection 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 3d 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.

resources/bundled-skills/scientific-problem-selection/SKILL.md · 38 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

2 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.

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. 3d ago First seen · 38 lines · 30 tokens per session scan A 225148210a9d

Subscribe to this mod's changes

scientific-problem-selection is a skill published in the GitHub repository KunAgent/Kun (6,294 stars, last pushed yesterday), with no licence file. It adds 30 tokens to every session and 330 once invoked, about $0.0002 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 2026-09-06.

Related

Other skills, from other repositories

social-physics-filter

Unified boundary enforcement, interpersonal diagnostic, and relational audit engine. Absorbs 40 psychology + 2 social protocols and all relationship case studies.

winstonkoh87/Athena-Public · 34 tokens

distribution-physics

Analyzes market dynamics and go-to-market strategies using "Distribution First" architecture.

winstonkoh87/Athena-Public · 20 tokens

ai-agents-research-methodology

How a hunch becomes an accepted result in this repo. Covers the evidence bar, hypothesis-predicts-numbers discipline, and the idea lifecycle from contradiction log through probe, eval baseline, ADR debate, calibrated gate, and post-ship monitoring. Use when you say how do I prove this idea, run the idea lifecycle…

rjmurillo/ai-agents · 118 tokens

autoresearch

Run bounded automated experiment iterations by recording baselines, applying hypothesis patches, comparing metrics, protecting regression guards, and deciding keep, discard, rollback, or block. Use when automated research is requested or a repo/skill needs evidence-backed research, metric tracking, or safe…

jscraik/Agent-Skills · 59 tokens

weather-query

Use when users ask about weather conditions, forecasts, or climate information for locations in China.

xyva-yuangui/XyvaClaw · 21 tokens

browser-automation

Local Python-based browser automation toolkit using Playwright. Provides command-line tools for navigating, interacting with, and testing web applications without using MCP protocols. Supports clicking, typing, hovering, screenshots, content extraction, and JavaScript execution.

archubbuck/workspace-architect · 50 tokens