TypingMindTypingMindThe best frontend for AI
Evidence Based Replies logo

Evidence Based Replies

Community
AtlasOmnia
evidence-based-replies

evidence-based-replies — Compare a person's claim to a cited paper or source, isolate what the evidence actually supports, and draft concise replies that correct overreach without sounding evasive.

Overview

PublisherAtlasOmnia
Repositorydonna-starter
Skill nameevidence-based-replies
Stars
131
Forks
9
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AtlasOmnia on GitHub. Read the source before you install it.

Installation

Install the Evidence Based Replies AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AtlasOmnia/donna-starter/tree/main/skills/research/evidence-based-replies
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AtlasOmnia/donna-starter.git /tmp/donna-starter
mkdir -p .claude/skills
cp -r /tmp/donna-starter/skills/research/evidence-based-replies .claude/skills/evidence-based-replies
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evidence Based Replies in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evidence Based Replies on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evidence Based Replies is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Evidence-Based Replies

Use this skill when the user wants to:

  • compare someone's claim to a research paper, benchmark, article, or repo README
  • draft a reply that corrects a misunderstanding of the evidence
  • separate "the source supports X" from "the source does not support Y"
  • turn a source-comparison into a Reddit/X/forum-ready response

Core principle

Do not stop at summarizing the source. The deliverable is usually the distinction:

  1. what the source actually establishes
  2. what stronger conclusion the other person is trying to import into it
  3. why that leap does not follow

If the user is asking for a reply, the misunderstanding of the evidence must be addressed explicitly, not left implicit.

Default workflow

  1. Read the conversation/claim carefully.
  2. Extract the specific proposition the other person is asserting from the source.
  3. Read the cited source.
  4. Split findings into:
  • Supported by the source
  • Not established by the source
  • Reasonable but unproven extrapolations
  1. Compare the source type:
  • empirical paper
  • benchmark paper
  • opinion/design README
  • repo guidance / author doctrine
  1. Draft the response around the distinction, not around vague disagreement.

Required output shape

When explaining the comparison, prefer this structure:

  • "The paper/source does show ..."
  • "What it does not show is ..."
  • "That is the step I disagree with."
  • "So my criticism is not X; it is Y."

This pattern prevents straw-manning and keeps the correction precise.

Writing guidance for this user

the user prefers concise, practical responses. For forum replies:

  • lead with the misunderstanding, not with throat-clearing
  • avoid generic "both sides have a point" filler
  • make the inferential gap explicit
  • distinguish directionally true claims from overclaims
  • prefer operational language over academic hedging

If he says a draft "needs to address the misunderstanding of the research," revise around the evidentiary gap immediately.

Pitfalls

  • Do not equate "source says style matters" with "source proves this specific implementation is better."
  • Do not let a repo README or manifesto carry the evidentiary weight of a paper.
  • For software/config claims, prefer current upstream docs and source code over stale third-party guides; explicitly label stale or unverified config paths instead of treating all cited paths as current.
  • When fact-checking a complaint, distinguish: true current behavior, stale terminology, fair UX criticism, and rhetorical overclaim. Do not collapse those into a simple true/false verdict.
  • Do not answer only at the concept level if the user needs a postable reply.
  • Do not bury the key distinction in paragraph four.
  • Do not over-hedge once the inferential error is clear.

Heuristic: evidence ladder

From strongest to weakest:

  1. direct empirical finding in the cited paper
  2. constrained implication from that finding
  3. plausible implementation guess
  4. repo philosophy / author preference

Label which rung the person's claim sits on.

Forum-ready reply recipe

For Reddit/X/forum use:

  1. Sentence 1: identify the misunderstanding.
  2. Sentence 2: state what the paper actually supports.
  3. Sentence 3: state what it does not support.
  4. Sentence 4+: tie back to the concrete artifact under debate.
  • references/research-overclaim-patterns.md — session-derived example of correcting a paper-based overclaim in a SOUL.md / persona-file debate.

Public support files

  • references/research-overclaim-patterns.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Evidence Based Replies AI skill do?

evidence-based-replies — Compare a person's claim to a cited paper or source, isolate what the evidence actually supports, and draft concise replies that correct overreach without sounding evasive.

Why use Evidence Based Replies on TypingMind?

Because you install it once and use it with any model. Evidence Based Replies is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evidence Based Replies in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AtlasOmnia/donna-starter/tree/main/skills/research/evidence-based-replies. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evidence Based Replies?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evidence Based Replies?

As many as you like. As long as a model supports skills, you can use Evidence Based Replies with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evidence Based Replies AI skill free?

Yes. It is published on GitHub by AtlasOmnia under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Related AI Skills

View all
affaan-m logo

Deep Research

affaan-m
CommunityPopular

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any…

40.4K
270.2K
1 files
View
affaan-m logo

Exa Search

affaan-m
CommunityPopular

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search…

40.4K
270.2K
1 files
View
mattpocock logo

Wayfinder

mattpocock
CommunityPopular

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

22.3K
264.4K
1 files
View
NousResearch logo

Creative Ideation

NousResearch
OrganizationPopular

Generate ideas via named methods from creative practice.

53.5K
250.4K
27 files
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇