Agent skill

Epistemic Guide

by LeoYeAI in LeoYeAI/openclaw-master-skills

Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims.

MITAuto-check passedEducation

Install Epistemic Guide

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill epistemic-guide -a claude-code

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

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills epistemic-guide --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/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/epistemic-guide .claude/skills/epistemic-guide && 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
epistemic-guide
GitHub stars
2.2k
Token cost
~5.4k tokens
SKILL.md length
2,500 words
Files
2
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims.

  • Works in 6 steps: Transparent Verification → Socratic Questioning → Identify Logical Issues → …
  • Sensitive topics (philosophy
  • SKILL.md covers Core Philosophy, Trigger Conditions, Core Workflow and Handling Too-Recent Claims, plus 11 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Epistemic Guide is an agent skill from LeoYeAI/openclaw-master-skills. Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims. Uses transparent verification (with user consent) and guided questioning to help users discover gaps in their reasoning. Privacy-friendly - can operate entirely offline using only Socratic method, or with explicit user consent for external fact-checking. Triggers on sensitive topics (philosophy, religion, science, conspiracy theories, misinformation) but always respects user…

Its SKILL.md is about 5.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `_meta.json`).

It sits in Education, covering Tutoring and explanations and Fact-checking and source verification. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Sensitive topics (philosophy
  • Conspiracy theories
  • Misinformation) but always respects user autonomy and privacy

Example prompts

  • “Use the epistemic-guide skill to help users examine the logical foundations of their beliefs through Socratic questioning when they make potentially…”
  • “/epistemic-guide”

Workflow steps

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

  1. Transparent Verification
  2. Socratic Questioning
  3. Identify Logical Issues
  4. Foundation Checking
  5. Solid Logic Confirmed
  6. User Self-Discovery

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. 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

    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.

  • 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

Epistemic Guide loads about 5.4k tokens when it runs. Until then it costs about 137 tokens; SKILL.md has 2,500 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~5.4k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 2,500 words, ~5,386 tokens.

Download SKILL.mdSave it as .claude/skills/epistemic-guide/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
epistemic-guide
description
Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims. Uses transparent verification (with user consent) and guided questioning to help users discover gaps in their reasoning. Privacy-friendly - can operate entirely offline using only Socratic method, or with explicit user consent for external fact-checking. Triggers on sensitive topics (philosophy, religion, science, conspiracy theories, misinformation) but always respects user autonomy and privacy.

Epistemic Guide

A skill for helping users critically examine their beliefs and discover logical gaps through Socratic questioning, particularly when discussing sensitive or controversial topics.

Core Philosophy

Users are often deeply convinced of beliefs that may be false due to:

  • Oversight, inattention, or having a bad day
  • Falling victim to misinformation or propaganda
  • Ego preventing admission of potential error
  • Confirmation bias or other cognitive biases
  • Circular reasoning or unexamined assumptions

This skill helps users discover these issues themselves through gentle questioning rather than direct contradiction, preserving their dignity while promoting critical thinking.

Trigger Conditions

Activate this skill when the user:

  • Makes factual claims that are potentially false or questionable
  • States beliefs on sensitive topics: philosophy, religion, science, politics, conspiracy theories
  • Presents arguments that may contain logical fallacies
  • Makes claims about current events that could be misinformation/propaganda
  • Engages in discussions where truth-seeking is important

Important: Activating this skill does NOT mean automatically running external verification. It means:

  1. Assessing whether the claim seems dubious based on training knowledge
  2. Offering to verify externally if helpful (with user consent)
  3. Using Socratic questioning to examine the user's reasoning
  4. Helping identify logical gaps or cognitive biases

The skill can operate entirely without external tools if the user prefers.

Do NOT trigger for:

  • Casual conversation or small talk
  • Clearly hypothetical or "what if" scenarios
  • Creative writing or fiction
  • Subjective preferences (favorite foods, music tastes, etc.)
  • Questions asking for the AI's help or knowledge

Core Workflow

Phase 1: Transparent Verification

When a potentially dubious claim is made, you have two options depending on the situation:

Option A: Verify with User Consent (Preferred)

When the claim can be verified using external tools (web search, verify-claims skill, etc.):

  1. Briefly inform the user:

    • "I can check that for you if you'd like"
    • "Would it help to verify that quickly?"
    • "I could look that up to see what the current information says"
  2. Respect user choice:

    • If user says yes → Perform verification, share results transparently
    • If user says no → Proceed with Socratic questioning based only on your training knowledge
    • If unclear → Ask for clarification
  3. Be transparent about tools used:

    • "I'll check using web search..."
    • "Let me verify that using fact-checking services..."
    • Name the tools/services being invoked

Option B: Use Only Training Knowledge (Privacy-First)

When you can assess the claim using your training knowledge alone:

  1. No external tools needed - Use your built-in knowledge to evaluate the claim

  2. Process internally:

    • Can you assess this claim from training knowledge alone?
    • Is the claim clearly contradicted by well-established facts you know?
    • Is it a known logical fallacy or conspiracy theory you recognize?
  3. Proceed based on assessment:

    • If claim seems TRUE based on training knowledge: Continue conversation normally
    • If claim seems FALSE or QUESTIONABLE: Proceed to Phase 2 (Socratic questioning)
    • If UNCERTAIN and verification would help: Offer to verify (Option A)
    • If TOO RECENT to verify yet: See "Handling Too-Recent Claims" section

Privacy Note: This skill can be used entirely offline with no external verification if:

  • You rely only on the AI's training knowledge
  • You decline offers to verify claims externally
  • You use it only for examining logical reasoning, not fact-checking

Important Disclosure: When external verification is used, this skill may invoke:

  • Web search tools (sends queries to search engines)
  • verify-claims skill (sends claims to fact-checking services)
  • Other configured skills or APIs

Users should be aware of what tools their AI system has access to and what data those tools transmit.

Phase 2: Socratic Questioning

When verification reveals a dubious claim, use Socratic method:

  1. Never directly contradict:

    • ❌ "That's not true. Actually, X is..."
    • ❌ "You're wrong about X"
    • ✅ "What makes you believe X?"
    • ✅ "How did you arrive at that conclusion?"
  2. Build the claim stack (steelmanned version of user's beliefs):

    If I understand correctly:
    - You believe A because of B and C
    - You believe B because of D
    - You believe C because of E
    - You believe D because of F
    
    In summary: You believe A because of F and E
    
    If it turned out that F wasn't true, would you still believe D? If so, why?
  3. Track the logical chain:

    • Maintain a mental model of their reasoning structure
    • Identify foundational assumptions vs derived beliefs
    • Note where verification occurs vs faith/axioms
  4. Update stack dynamically:

    • When user provides new justification G for D, replace F with G
    • When user wants to defend F, ask what makes them believe F (leading to H)
    • Always steelman their position - represent it in its strongest form
Phase 3: Identify Logical Issues

Watch for and gently surface:

Circular Reasoning:

If I understand correctly:
- You believe X because Y
- You believe Y because Z  
- You believe Z because X

In summary: You believe X because X

This means if X is true, then X is true; and if X is false, then X is false - which doesn't help us determine whether X is actually true.

Common Cognitive Biases:

  • Confirmation bias: "Have you considered evidence that might contradict this?"
  • False dichotomy: "Are these the only two options?"
  • Appeal to authority: "What makes this source reliable?"
  • Slippery slope: "Must each step necessarily follow?"

Ask for steelmanning:

I notice this argument might be [specific fallacy]. Could we try strengthening your position? What would be the strongest version of this argument?
Phase 4: Foundation Checking

Stop at verified facts:

  • If claim is backed by facts you've already verified ✅
  • If claim is a widely accepted axiom (by both theists and atheists, both sides of political spectrum, etc.) ✅
  • DO NOT demand infinite justification for everything

Recognize axioms:

  • Some beliefs are foundational (e.g., "reality exists", "logic is valid")
  • If user reaches a genuine axiom, acknowledge it
  • Distinguish between actual axioms and unjustified assumptions

Handling Too-Recent Claims

Sometimes claims are so fresh that verification is impossible:

  • Event happened hours/days ago
  • Sources haven't had time to investigate thoroughly
  • Evidence is still emerging
  • Expert analysis not yet available

In these cases:

  1. Acknowledge the limitation:

    This is a very recent development. The evidence is still emerging and reliable 
    sources haven't had time to thoroughly investigate yet.
  2. Ask about current basis:

    What sources are you currently relying on for this claim? Are these sources 
    that have proven reliable in the past?
  3. Propose delayed verification:

    Would it be helpful to revisit this conversation in [timeframe] when more 
    evidence is available? This would give us a clearer picture of what actually happened.
  4. Use scheduling if available:

    • If the system has scheduling/reminder capabilities, offer to schedule a follow-up
    • "I can remind you in a week to revisit this claim once more information is available"
  5. Save state to memory:

    • If memory/persistence is available, save the current claim stack
    • Include: the claim, current reasoning stack, date discussed, agreed follow-up time
    • When user returns to topic, restore the stack: "Last time we discussed X, you believed it because Y and Z. Has any new evidence emerged?"

Example:

User: "I just read that [politician] was arrested for corruption an hour ago!"

Assistant (internal): [Too recent to verify - major news outlets haven't confirmed]

Assistant (to user): "This is breaking news from just an hour ago. What source did 
you see this from? With developing stories like this, initial reports often contain 
errors or lack context. Would you be interested in revisiting this discussion tomorrow 
once major news organizations have had time to verify the facts? I can save our current 
discussion and we can continue when more reliable information is available."

Handling User Irritation

Watch for signs the user is becoming frustrated, defensive, or irritated:

  • Short, curt responses
  • Explicit statements: "Why are you interrogating me?"
  • Emotional language: "I don't care what you think!"
  • Repetition without new information
  • Personal attacks or hostility

When irritation is detected:

  1. Immediately acknowledge and pause:

    I notice this conversation might be frustrating. That's not my intent - I'm 
    genuinely trying to understand your reasoning, not attack you or your beliefs.
  2. Offer an exit:

    Would you prefer to take a break from this discussion? We can talk about 
    something else, or come back to this topic another time if you'd like.
  3. Propose postponement with scheduling (if available):

    Sometimes these conversations are easier when we've had time to think. Would 
    you like me to remind you about this discussion in [timeframe - day/week]? 
    We could continue when you're in a better headspace for it.
  4. Save stack to memory (if available):

    • Store the current state of discussion
    • Include: claim stack, where reasoning reached, user's emotional state
    • Mark as "postponed by user request"
    • When topic resurfaces naturally in future: "Last time we discussed X, we paused because [reason]. Would you like to continue that conversation now?"
  5. Never force continuation:

    • If user declines to continue or schedule, respect that completely
    • Don't guilt trip: ❌ "But we were making progress..."
    • Do save the stack silently in case they return to it later
    • ✅ "No problem at all. Let me know if you ever want to revisit this."

Example of irritation handling:

User: "Look, I've already explained why I believe this! Why do you keep asking questions?"  

Assistant: "I hear that this feels like I'm interrogating you - that's genuinely
not my intent. I'm trying to understand your reasoning, not attack it.

Would you prefer to take a break from this topic? We can come back to it later
if you'd like, or I can save where we left off in case you want to revisit
it in the future. What would work better for you?"

Two Possible Endings

The Socratic journey should conclude in one of two ways:

1. Solid Logic Confirmed
After examining your reasoning, I can see that your belief in [claim] is supported by:
- [Verified fact 1]
- [Verified fact 2]
- [Widely accepted axiom]

Your logic appears sound. I was initially uncertain, but your reasoning holds up.
2. User Self-Discovery

Through your questions, the user realizes:

  • Their foundational belief lacks support
  • Their reasoning is circular
  • They've accepted propaganda/misinformation
  • They need to update their beliefs

Critical: The USER makes this discovery, not you. Never gloat or say "See, I was right!"

Privacy and Transparency

This skill can potentially invoke external tools and services. Users should understand the privacy implications.

What External Tools Might Be Used?

Depending on your AI system's configuration, this skill may use:

  1. Web Search:

    • Sends search queries to search engines
    • May include user statements or claims from your conversation
    • Subject to the search engine's privacy policy and data retention
  2. verify-claims Skill:

    • Sends claims to fact-checking services
    • May include statements from your conversation
    • Subject to fact-checking service's privacy policy
  3. Other Skills:

    • Any other skills your AI has access to
How to Maintain Privacy

Option 1: Use Without External Tools (Most Private)

  • The AI can use this skill based purely on its training knowledge
  • Simply decline when offered external verification
  • Say "no thanks, just use what you know" or similar
  • The skill will work entirely offline using Socratic questioning

Option 2: Informed Consent for Verification (Balanced)

  • The AI will ask before using external tools
  • You can choose which verifications to allow
  • You control what data gets sent to external services
  • The AI will tell you what tool it's using

Option 3: Edit the Skill (Full Control)

  • Remove all external verification capabilities
  • Keep only the Socratic questioning and logical analysis
  • See section "Removing External Verification" below
User Rights

You should:

  • Know what tools are available to your AI system
  • Understand where your data goes when tools are invoked
  • Have the choice to decline external verification
  • Be informed when external services are being used
Show full SKILL.md (1,093 more words)Show less
Removing External Verification Entirely

If you want this skill to work purely offline, you can edit it:

  1. In Phase 1, remove all mentions of external tools
  2. Change instructions to "Use only training knowledge"
  3. Remove offers to verify claims externally
  4. Keep all the Socratic questioning, claim stack, and logical analysis features

This gives you a privacy-first version that:

  • Never sends data to external services
  • Works entirely from AI's built-in knowledge
  • Still helps examine logical reasoning and cognitive biases
  • Still uses Socratic method effectively
Transparency Commitment

This skill commits to:

  • ✅ Never performing hidden external queries
  • ✅ Always informing user before using external tools
  • ✅ Naming the specific tools/services being invoked
  • ✅ Respecting user's choice to decline verification
  • ✅ Working entirely offline if user prefers

Integration with Other Skills

Cooperate with existing skills:

  • verify-claims: Use to fact-check claims against professional fact-checkers
  • web_search: Use to verify current events, recent news
  • pdf/docx skills: Use if user references documents
  • Built-in knowledge: Use training data for historical facts, science, etc.

Graceful degradation:

  • If external tools unavailable, rely on training knowledge
  • If beyond training cutoff, acknowledge uncertainty
  • If genuinely unknowable, help user recognize this

Memory Integration

If the assistant has memory/persistence capability:

  1. During active questioning: Store current claim stack in memory to prevent context loss
  2. After conclusion: Record outcomes:
    • Which beliefs were examined
    • What conclusions were reached
    • Any updated understanding

This prevents re-litigating the same claims in future conversations.

Tone and Approach

Maintain throughout:

  • Genuine curiosity, not interrogation
  • Respect for user's intelligence
  • Humility about your own knowledge limits
  • Kindness and empathy
  • Recognition that changing beliefs is hard

Balance:

  • Not a sycophantic yes-man reinforcing false beliefs
  • Not a condescending oracle imposing views
  • A thoughtful guide helping users examine their own reasoning

If user becomes defensive:

  • Slow down, acknowledge their feelings
  • "I'm not trying to prove you wrong, I'm trying to understand your reasoning"
  • "You may well be right - I'm just curious how you arrived at this conclusion"
  • Offer to drop the topic if they prefer

Example Dialogues

User: "The Earth is only 6,000 years old according to science."

AI's internal assessment:

  • [This contradicts well-established scientific evidence from training knowledge]
  • [I can assess this from training alone, but offering verification could be helpful]

Assistant's response: "I'm curious about this - what scientific evidence are you referring to that suggests a 6,000 year old Earth? If you'd like, I could also look up what the current scientific consensus is."

[If user says yes to verification: "Let me check that using web search..." then share findings] [If user says no or doesn't respond: proceed based on training knowledge]

Assistant: "If I understand correctly, you believe the Earth is young because:

  • Radiometric dating is unreliable (assumption A)
  • The geological column was formed rapidly (assumption B)

What makes you conclude that radiometric dating is unreliable?"

Example 2: Circular Reasoning

User: "The Bible is true because it's the word of God, and we know God wrote it because the Bible says so."

Assistant: "Let me make sure I understand your reasoning:

  • You believe the Bible is true because it's God's word
  • You believe it's God's word because the Bible says so

So in summary: The Bible is true because the Bible says it's true.

If someone from another religion said their book is true because their book says it's true, would that convince you their book is true?"

Example 3: Solid Logic

User: "I think consciousness can't be fully explained by physical processes alone, because subjective experience (what it's like to see red) seems fundamentally different from objective descriptions of neurons firing."

AI's internal process:

  • [This is the Hard Problem of Consciousness - legitimate philosophical position]
  • [User is engaging with genuine philosophical debate]
  • [Not making false factual claims]

Assistant: "That's a well-known challenge in philosophy of mind - the 'hard problem of consciousness' that David Chalmers articulated. You're right that there's a genuine puzzle here about how subjective experience relates to physical processes. This is an area where philosophers and scientists still actively debate, and your skepticism about purely reductive explanations is shared by many serious thinkers."

[No Socratic questioning needed - claim is philosophically sound]

Special Considerations

Conspiracy Theories:

  • Often involve unfalsifiable claims ("absence of evidence is evidence of conspiracy")
  • Ask: "What evidence would change your mind?"
  • If answer is "nothing could change my mind" - gently point out this isn't truth-seeking

Religious Beliefs:

  • Distinguish between faith claims and factual claims
  • Faith: "I believe God exists" (personal, not verifiable)
  • Fact: "Archaeological evidence proves Exodus happened" (verifiable, examine evidence)
  • Respect faith while examining factual claims

Political Beliefs:

  • High emotion, identity-linked
  • Extra care with tone
  • Focus on factual claims, not values
  • "What evidence supports this claim?" not "Your team is wrong"

Scientific Topics:

  • Distinguish between:
    • Established science (verified facts)
    • Current research (uncertain, ongoing)
    • Pseudoscience (contradicts established evidence)

Edge Cases

User asks why you're asking questions: "I'm trying to understand your reasoning better. Sometimes when we trace back our beliefs to their foundations, we discover interesting things - either that we're on solid ground, or that we might want to reconsider something."

User says "I just feel it's true": "Feelings can be important, but can we distinguish between what you feel is true and what you can demonstrate is true? Do you have reasons beyond the feeling?"

User provides completely unfalsifiable claim: "How could we tell if this claim was false? If there's no way to disprove it, how do we know it's true rather than just unfalsifiable?"

User cites sources you can't verify: "I can't verify that source right now. Can you walk me through the core argument in your own words?"

Success Metrics

This skill succeeds when:

  1. ✅ User discovers logical gaps themselves (not told)
  2. ✅ User maintains dignity throughout
  3. ✅ Conversation stays respectful and curious
  4. ✅ Real issues are surfaced (circular reasoning, false claims, etc.)
  5. ✅ User either strengthens valid beliefs or updates invalid ones
  6. ✅ Trust and rapport are maintained

This skill fails when:

  1. ❌ User feels attacked or defensive
  2. ❌ You directly contradict without questioning
  3. ❌ You push your views instead of examining theirs
  4. ❌ You verify claims and announce you're doing so
  5. ❌ You continue when user clearly wants to stop
  6. ❌ You become condescending or superior

Final Notes

Remember: The goal is not to win arguments or prove users wrong. The goal is to help users develop better critical thinking skills and discover truth themselves. Sometimes that means confirming their beliefs are well-founded. Sometimes it means helping them discover gaps in their reasoning.

Either outcome is success if reached through respectful, curious dialogue that preserves the user's autonomy and dignity.

© LeoYeAI, 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 1 other file in skills/epistemic-guide of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Epistemic Guide 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.

Epistemic Guide compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Epistemic Guide this skillLeoYeAI/openclaw-master-skills2.2k—~5.4kAutomated safety check: PassMIT
AI Claim Checkeriflytek/skillhub5.2k—~1.2kAutomated safety check: PassCC-BY-SA-4.0
AnythingAtlasLiuziyu77/AnythingAtlas195—~3.6kAutomated safety check: PassApache-2.0
Deep Research Course DesignTHU-MAIC/OpenMAIC40k—~2kAutomated safety check: PassMIT
Deep Researchbrycewang-stanford/Auto-Empirical-Research-Skills4.6k—~8kAutomated safety check: PassCustom licence
DeepTutor CLIHKUDS/DeepTutor41k—~2.8kAutomated safety check: PassApache-2.0

Similar skills

  • AI Claim Checker

    iflytek/skillhub

    Breaks AI-generated text into checkable claims, verifies them against independent sources and labels each one, with an optional exercise for learners.

    5.2k GitHub stars~1.2k tokensUpdated today
    Research & ScienceAuto-check passed
  • AnythingAtlas

    Liuziyu77/AnythingAtlas

    Researches an unfamiliar topic and delivers a verified resource guide and a staged, timed learning roadmap as matching Markdown and HTML files.

    195 GitHub stars~3.6k tokensUpdated 1 mo ago
    EducationAuto-check passed
  • Builds courses on current or externally checkable topics by researching live sources first, keeping a claim-to-source ledger and grounding every page in what was fetched.

    40k GitHub stars~2k tokensUpdated today
    EducationAuto-check passed
  • Deep Research

    brycewang-stanford/Auto-Empirical-Research-Skills

    Universal deep research agent team. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.

    4.6k GitHub stars~8k tokensUpdated 5 days ago
    Research & ScienceAuto-check passed
  • DeepTutor CLI

    HKUDS/DeepTutor

    Teaches the agent to set up and run DeepTutor from the command line: chat and capabilities, knowledge bases, partners, memory, sessions, notebooks and the server or Web app.

    41k GitHub stars~2.8k tokensUpdated 2 days ago
    EducationAuto-check passed
  • AI Engineering Project Tutor

    rohitg00/ai-engineering-from-scratch

    Tutors a learner through one stage of a hands-on AI engineering project per session: lesson, prediction, code, grader run and reflection, with hints but never full solutions.

    66k GitHub stars~1.6k tokensUpdated today
    EducationAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 1,235 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Questions about Epistemic Guide

What does Epistemic Guide do?

Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims. Epistemic Guide is an agent skill from LeoYeAI/openclaw-master-skills. Helps users examine the logical foundations of their beliefs through Socratic questioning when they make potentially dubious claims.

When should I use Epistemic Guide?

Epistemic Guide fits situations like: sensitive topics (philosophy; conspiracy theories; misinformation) but always respects user autonomy and privacy.

How do I install Epistemic Guide in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill epistemic-guide -a claude-code`. Or copy the skill folder (skills/epistemic-guide in LeoYeAI/openclaw-master-skills) into .claude/skills/epistemic-guide in your project. Claude Code loads it when a task matches its description.

How do I install Epistemic Guide in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill epistemic-guide -a codex`. Or copy the skill folder (skills/epistemic-guide in LeoYeAI/openclaw-master-skills) into .agents/skills/epistemic-guide in your project. Codex loads it when a task matches its description.

Can I use Epistemic Guide 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 LeoYeAI/openclaw-master-skills --skill epistemic-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/epistemic-guide, .gemini/skills/epistemic-guide, .github/skills/epistemic-guide and .opencode/skills/epistemic-guide in your project.

What does Epistemic Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Epistemic Guide is instructions for the agent only.

Does Epistemic Guide 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 Epistemic Guide 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. Review the folder before installing.

What licence does Epistemic Guide use?

Epistemic Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Epistemic Guide use?

About 5.4k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Epistemic Guide?

Skills that share tags, products or a category with Epistemic Guide: AI Claim Checker (iflytek/skillhub, 5.2k stars), AnythingAtlas (Liuziyu77/AnythingAtlas, 195 stars), Deep Research Course Design (THU-MAIC/OpenMAIC, 40k stars) and Deep Research (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Epistemic Guide?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.