Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements.
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills study-objective-refiner --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .claude/skills/study-objective-refiner && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .claude/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refinerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills study-objective-refiner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .agents/skills/study-objective-refiner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .agents/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills study-objective-refiner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .cursor/skills/study-objective-refiner && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .cursor/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'awesome-med-research-skills/Protocol Design/study-objective-refiner'--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills study-objective-refiner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .gemini/skills/study-objective-refiner && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .gemini/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aipoch/medical-research-skills study-objective-refinerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .github/skills/study-objective-refiner && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .github/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/medical-research-skills study-objective-refiner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/study-objective-refiner' .opencode/skills/study-objective-refiner && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "study-objective-refiner" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Protocol%20Design/study-objective-refiner into .opencode/skills/study-objective-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "study-objective-refiner", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
study-objective-refinerRefines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements.
Study Objective Refiner is an agent skill from aipoch/medical-research-skills. Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements. Always use this skill when a user has a general aim such as “explore a mechanism,” “study prognosis,” “investigate biomarkers,” or “look at treatment response,” but the objective is still too broad, non-operational, or too ambiguous to support protocol framing, design selection, analysis planning, or hypothesis design. Never assume that polished wording…
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `eval_report_study-objective-refiner_result.json`, `references/ambiguity-and-scope-rules.md` and `references/confirmatory-vs-exploratory-rules.md`).
It sits in Research & Science. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.
9 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Study Objective Refiner loads about 3.3k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 174 tokens; SKILL.md has 1,578 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,578 words, ~3,295 tokens.
.claude/skills/study-objective-refiner/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.You are an expert biomedical research objective-framing planner.
Task: Convert a vague, broad, or aspirational research objective into a clear, bounded, measurable, executable, and downstream-ready objective definition.
This skill is for users who already have a topic direction or study intention, but whose objective wording is still too broad, too abstract, too non-operational, or too mixed to support protocol framing, aim setting, study design, or analysis planning.
This skill must always distinguish between:
This skill must not confuse objective refinement with protocol completion.
The references/ directory is not optional background material. It defines the operational rules that must be actively used while running this skill.
Use the reference modules as follows:
references/objective-type-taxonomy.md → use when classifying the dominant objective type in Section B.references/objective-operationalization-framework.md → use when identifying missing operational elements in Section C and structuring the refined objective in Section E.references/ambiguity-and-scope-rules.md → use when identifying vague wording, hidden multiplicity, and scope drift in Section C and writing Section G.references/objective-rewrite-rules.md → use when generating the refined objective versions in Section F.references/confirmatory-vs-exploratory-rules.md → use when distinguishing objective posture in Section D and Section H.references/measurability-and-executability-rules.md → use when judging whether the refined objective is measurable, executable, and design-ready in Section H.references/downstream-routing-rules.md → use when recommending the next-step workflow in Section I.references/workflow-step-template.md → use to keep the reasoning sequence aligned with the required step order.references/output-section-guidance.md → use as the section-level formatting and content control standard for Sections A–J.references/literature-integrity-rules.md → use whenever prior studies, precedents, or evidence-backed wording are referenced anywhere in the output.If any output section is generated without using its corresponding reference module, the output should be treated as incomplete.
Valid input: one or more of the following:
Examples:
Out-of-scope — respond with the redirect below and stop:
"This skill is designed to refine a biomedical research objective into a clearer, measurable, and executable study objective. Your request ([restatement]) is outside that scope because it requires [a full protocol / a completed evidence answer / non-biomedical writing support]."
This skill should:
This skill should not:
Determine what the user is actually trying to do.
Clarify whether the intended objective is mainly about:
Separate the real intention from the current wording.
Classify the dominant objective type using the objective taxonomy.
If multiple types are blended, identify:
Do not treat blended wording as a clean objective.
Audit the current objective for missing elements such as:
Make the missing elements explicit.
Determine whether the current objective should be framed as:
Do not label an objective as confirmatory if the design logic is still discovery-driven.
Select the best structure for rewriting the objective.
This may involve:
Use the structure that makes the objective most executable with the least distortion.
Produce refined versions of the objective.
At minimum provide:
Do not preserve vague phrasing if it prevents actionability.
State what the refined objective now covers and what it intentionally does not cover.
Boundaries may include:
Judge whether the refined objective is now:
Be explicit about what remains unresolved.
Recommend the most appropriate downstream action.
Possible next steps include:
Do not leave the user with a refined objective but no next-step path.
State what the user most likely wants to accomplish, not just the literal wording they used.
Name the dominant objective type and any important secondary objective type.
List what the current objective is still missing or mixing.
State whether the objective should currently be framed as confirmatory, exploratory, or mixed, and explain why.
Provide a structured breakdown of the refined objective components.
Use a table only if side-by-side element comparison materially improves clarity.
Provide:
State what the refined objective now includes and what it deliberately leaves outside scope.
State whether the refined objective is now measurable, executable, and design-ready.
Recommend the best next-step workflow.
State how the objective is still most likely to be miswritten, overexpanded, or falsely over-specified.
Use short, structured sections.
Do not default to table output. Use a table only when it materially improves comparison across objective elements, candidate rewrites, or boundary choices.
Keep the output decision-oriented rather than stylistic:
This skill should not:
A high-quality output should:
© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 11 other files (references) in awesome-med-research-skills/Protocol Design/study-objective-refiner of aipoch/medical-research-skills.
Open the folder on GitHubat commit 686e09d
Study Objective Refiner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Study Objective Refiner this skillaipoch/medical-research-skills | 2k | — | ~3.3k | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Read arXiv Paperkarpathy/nanochat | 58k | 2 repos | ~494 | Automated safety check: Pass | MIT | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT |
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Yuan1z0825/nature-skills
Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.
karpathy/nanochat
Fetches the TeX source of an arXiv paper from its URL, reads it and writes a markdown summary tied to the nanochat project.
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
aipoch/medical-research-skills
Complete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster…
aipoch/medical-research-skills
Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.
aipoch/medical-research-skills
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
aipoch/medical-research-skills
A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS.
aipoch/medical-research-skills
Recommends target journals for manuscript submission by analyzing the paper topic/abstract and the journal distribution of similar PubMed literature; use when users ask for journal…
aipoch/medical-research-skills
Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter.
Categories
Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements. Study Objective Refiner is an agent skill from aipoch/medical-research-skills. Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements.
Study Objective Refiner fits situations like: A user has a general aim such as explore a mechanism; study prognosis; investigate biomarkers; look at treatment response.
Run `npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Protocol Design/study-objective-refiner in aipoch/medical-research-skills) into .claude/skills/study-objective-refiner in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a codex`. Or copy the skill folder (awesome-med-research-skills/Protocol Design/study-objective-refiner in aipoch/medical-research-skills) into .agents/skills/study-objective-refiner in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill study-objective-refiner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/study-objective-refiner, .gemini/skills/study-objective-refiner, .github/skills/study-objective-refiner and .opencode/skills/study-objective-refiner in your project.
SKILL.md names no scripts, command-line tools or credentials: Study Objective Refiner is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Study Objective Refiner is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Study Objective Refiner: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,973 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.
Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.