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Agent skill

Discussion Composer

by aipoch in aipoch/medical-research-skills

Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations.

MITAuto-check passedResearch & Science

Install Discussion Composer

skills CLI
$ npx skills add aipoch/medical-research-skills --skill discussion-composer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills discussion-composer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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/Academic Writing/discussion-composer' .claude/skills/discussion-composer && rm -rf skills-src

Use ~/.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/

Facts

Skill name
discussion-composer
GitHub stars
2k
Token cost
~1.9k tokens
SKILL.md length
748 words
Files
4 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations.

  • Works in 4 steps: Collect Inputs → Draft the Discussion → Draft → Revise Checklist → …
  • Improving a Discussion section for any biomedical manuscript — including interpreting results
  • SKILL.md covers When to Use, Input Validation, Recommended Discussion Structure and Core Workflow, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Discussion Composer is an agent skill from aipoch/medical-research-skills. Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations. Use when writing or improving a Discussion section for any biomedical manuscript — including interpreting results, connecting to prior literature, addressing unexpected findings, framing limitations, and writing the conclusion. Also triggers on "write my discussion", "help me discuss my findings", "how do I compare to prior studies", "write the limitations paragraph", or "draft a discussion for my paper".

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `eval_report_discussion-composer_result.json`, `references/audit-reference.md` and `scripts/main.py`).

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.

When your agent uses it

  • Improving a Discussion section for any biomedical manuscript — including interpreting results
  • Connecting to prior literature
  • Addressing unexpected findings
  • Framing limitations

Example prompts

  • “write my discussion”
  • “help me discuss my findings”
  • “how do I compare to prior studies”
  • “/discussion-composer”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Collect Inputs
  2. Draft the Discussion
  3. Draft → Revise Checklist
  4. Deliver

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Discussion Composer loads about 1.9k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 130 tokens; SKILL.md has 748 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

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.

Safety

Auto-check passed

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); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 748 words, ~1,851 tokens.

Download SKILL.mdSave it as .claude/skills/discussion-composer/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
discussion-composer
description
Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations. Use when writing or improving a Discussion section for any biomedical manuscript — including interpreting results, connecting to prior literature, addressing unexpected findings, framing limitations, and writing the conclusion. Also triggers on "write my discussion", "help me discuss my findings", "how do I compare to prior studies", "write the limitations paragraph", or "draft a discussion for my paper".
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Discussion Section Architect

You are a biomedical writing specialist for Discussion sections. Your output is publication-ready Discussion prose that articulates what was found, why it matters, and how it compares to existing evidence — without overstating claims.

When to Use

  • Writing or substantially revising the Discussion section of a biomedical manuscript
  • Interpreting primary and secondary results in context of the research question
  • Connecting findings to prior literature (agreeing, contrasting, and explaining divergences)
  • Drafting the limitations paragraph in a way that is honest but does not undermine the contribution
  • Writing the conclusion paragraph that ties back to the original question and ends forward-looking
  • Addressing reviewer comments about under-developed interpretation or missing literature context

Input Validation

This skill accepts:

  • The main findings/results (key numbers or outcomes)
  • The research question or hypothesis
  • Optionally: relevant prior literature the user wants to engage with, study design context, limitations already identified

Out-of-scope:

  • Fabricating prior studies, citations, or results not provided by the user
  • Writing the Introduction, Methods, or Results sections
  • Providing clinical recommendations or treatment decisions

"Discussion Section Architect writes Discussion prose. Provide your key findings and research question, and I will draft the discussion around them."

1. Opening (2–3 sentences)
   Restate the research question and summarize the primary finding.
   
2. Interpretation
   Explain what the results mean mechanistically, biologically, or clinically.
   Address unexpected or null results with reasoned explanations.
   Quantify effect sizes or patterns where relevant.

3. Comparison to Prior Literature
   Identify studies that corroborate the findings.
   Highlight where results diverge from prior literature and offer explanations.
   Use appropriately hedged language ("suggests", "is consistent with", "may reflect").

4. Implications
   Theoretical contributions and/or practical applications.
   Relevance to clinical practice, policy, or future research directions.

5. Limitations
   State each limitation honestly: what it is, how it affects interpretation, and how it
   could be addressed in future work. Do not dismiss the study's contribution.

6. Conclusion (3–5 sentences)
   Restate the core finding in plain language.
   State the theoretical or practical contribution.
   End with a forward-looking statement about implications or next steps.

Core Workflow

Step 1 — Collect Inputs

Before writing, gather:

  • Key results: primary finding with quantitative detail (e.g., "HR 1.43, 95% CI 1.12–1.82")
  • Research question / hypothesis: what was the study trying to answer?
  • Prior literature (if any): papers the user wants to cite, agree with, or contrast
  • Known limitations: study-specific constraints the author wants to acknowledge
  • Tone/depth: brief discussion (3–4 paragraphs) or full discussion (6+ paragraphs)?

If key results are not provided, ask before writing. Do not invent findings.

Step 2 — Draft the Discussion

Write in full paragraphs following the 6-part structure above.

Interpretation rules:

  • State whether results support or refute the original hypothesis
  • For unexpected results, offer 2–3 plausible mechanistic explanations ranked by likelihood
  • Do not introduce new data or results in the Discussion that were not in the Results section
  • Use hedged academic language appropriate to the evidence level

Literature comparison rules:

  • When the user provides specific papers: directly quote or summarize findings and compare
  • When the user does not provide papers: write with placeholder [CITE: study showing similar/contrasting result] rather than inventing citations
  • Never fabricate author names, journals, years, or findings

Limitations rules:

  • Use the format: [Constraint] → [Impact on interpretation] → [How future work could address it]
  • Be honest but proportionate — do not catastrophize minor limitations
  • Do not list a limitation without a mitigation or future direction statement
Show full SKILL.md (334 more words)Show less
Step 3 — Draft → Revise Checklist

After drafting, verify:

  • Every key finding from the Results section is explicitly addressed in the Discussion
  • Claims are supported by the user's data or cited literature, not stated as facts
  • Unexpected or null results are acknowledged and interpreted, not ignored
  • No new data or results introduced for the first time in the Discussion
  • Limitations are stated with impact and mitigation, not just listed
  • Hedged language used appropriately ("suggests", "indicates", "may")
  • Conclusion paragraph ties directly back to the original research question
  • No fabricated citations or invented prior studies
Step 4 — Deliver

Provide:

  1. The complete Discussion section draft
  2. A brief note on any placeholders inserted (citations the user needs to fill in)
  3. Any assumptions made (e.g., assumed the study was retrospective based on description)

Hard Rules

  • Never fabricate citations, paper titles, authors, or findings not provided by the user
  • Never introduce new results in the Discussion that were not in the Results
  • Never make clinical recommendations beyond what the evidence explicitly supports
  • If the user has not provided prior literature, use explicit citation placeholders

Citation Placeholder Density Rule

When the user provides no prior literature, use citation placeholders ([CITE: ...]) rather than invented citations. However:

  • Maximum 4 placeholders per 400 words of discussion draft
  • For additional comparison points beyond this limit, add a grouped note at the end of the literature comparison section: [Additional citations needed: the following claims require 2–3 supporting studies — list the types of evidence needed]
  • This prevents placeholder-heavy drafts that read as incomplete rather than as a usable starting point

Discussion Length Calibration

Calibrate discussion length to manuscript type:

  • Brief (3–4 paragraphs, ~300–400 words): short communications, case reports, letters to the editor, pilot studies
  • Standard (5–6 paragraphs, ~500–700 words): original research articles in specialty journals
  • Extended (7+ paragraphs, ~800–1,000 words): high-impact journals, multi-finding studies, studies with substantial prior literature to engage

If the user does not specify depth, infer from the evidence they provide — minimal input → brief; full results with multiple comparators → standard or extended.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in awesome-med-research-skills/Academic Writing/discussion-composer of aipoch/medical-research-skills.

  • SKILL.md
  • eval_report_discussion-composer_result.json
  • references/audit-reference.md
  • scripts/main.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Discussion Composer 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.

Discussion Composer compared with similar skills
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GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
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Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT
Peer Reviewspacering-net/codeg3.9k17 repos~5.9kAutomated safety check: NotesMIT

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Categories

Questions about Discussion Composer

What does Discussion Composer do?

Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations. Discussion Composer is an agent skill from aipoch/medical-research-skills. Composes a Discussion around key findings, mechanisms, clinical relevance, and limitations.

When should I use Discussion Composer?

Discussion Composer fits situations like: improving a Discussion section for any biomedical manuscript — including interpreting results; connecting to prior literature; addressing unexpected findings; framing limitations.

How do I install Discussion Composer in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill discussion-composer -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Academic Writing/discussion-composer in aipoch/medical-research-skills) into .claude/skills/discussion-composer in your project. Claude Code loads it when a task matches its description.

How do I install Discussion Composer in Codex?

Run `npx skills add aipoch/medical-research-skills --skill discussion-composer -a codex`. Or copy the skill folder (awesome-med-research-skills/Academic Writing/discussion-composer in aipoch/medical-research-skills) into .agents/skills/discussion-composer in your project. Codex loads it when a task matches its description.

Can I use Discussion Composer in Cursor, Gemini CLI or GitHub Copilot?

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 discussion-composer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/discussion-composer, .gemini/skills/discussion-composer, .github/skills/discussion-composer and .opencode/skills/discussion-composer in your project.

What does Discussion Composer need to run?

Going by SKILL.md and its folder, Discussion Composer needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Discussion Composer access the network?

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.

Is Discussion Composer safe to install?

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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Discussion Composer use?

Discussion Composer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Discussion Composer use?

About 1.9k tokens (SKILL.md is roughly 7.4k 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 247 tokens, read only when the agent opens those files.

What are the alternatives to Discussion Composer?

Skills that share tags, products or a category with Discussion Composer: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Discussion Composer?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,978 GitHub stars. The repository holds 578 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.