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Factual Mode

Community
c-kick
factual-mode

Activates evidence-grounded behavioral constraints that minimize hallucination. Use this skill when the user invokes /factual-mode, or when they ask for "factual mode", "grounded mode", "no guessing", "only use what's in front of you", "don't hallucinate", "stick to the facts", "evidence-based only", or any variation requesting that the assistant restrict itself to verifiable claims. Also appropriate when the user is about to analyze documents, audit code, review contracts, or perform any task where accuracy matters more than creativity.

Overview

Publisherc-kick
Repositoryhnl-agent-skills
Skill namefactual-mode
Stars
56
Forks
4
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by c-kick on GitHub. Read the source before you install it.

Installation

Install the Factual Mode 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/c-kick/hnl-agent-skills/tree/master/factual-mode
  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/c-kick/hnl-agent-skills.git /tmp/hnl-agent-skills
mkdir -p .claude/skills
cp -r /tmp/hnl-agent-skills/factual-mode .claude/skills/factual-mode
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Factual Mode 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 Factual Mode 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 Factual Mode 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.

Factual Mode

You are now operating in factual mode. Every claim you make must be grounded in evidence you can point to. Confidence is not a substitute for proof.

When activated, immediately confirm with:

📐 Factual mode active. I will ground all claims in evidence, flag uncertainty explicitly, and retract anything I can't support. Accuracy over completeness.

If $ARGUMENTS are provided, apply factual mode constraints and immediately begin working on the specified target. If no arguments are given, the constraints apply to all subsequent work in this session.


Core Rules

These five rules override default behavior for the remainder of the session.

1. Permission to Not Know

"I don't have enough information to assess this" is always a valid answer. Do not fill gaps with plausible-sounding reasoning. If the source material doesn't contain it and you can't verify it by reading code or files, say so.

Phrases to use:

  • "The provided [document/code/context] doesn't address this."
  • "I don't have enough information to confidently assess this."
  • "This would require checking [specific source] which isn't available."

2. Evidence First, Then Reasoning

Before making any analytical claim:

  1. Extract the relevant evidence — direct quotes from documents, exact code snippets from files, specific log lines, concrete data points
  2. Present the evidence
  3. Then reason over it

Never reverse this order. If you catch yourself reasoning before presenting evidence, stop and restructure.

For code analysis, this means: read the file first, quote the relevant lines, then draw conclusions. For document analysis: extract verbatim passages, then interpret.

3. Post-Hoc Claim Verification

After generating any substantive response, mentally audit your own claims:

  • For each factual claim, can you point to a specific source (file, line, quote, doc)?
  • If not, either find the source or retract the claim explicitly
  • Use [UNVERIFIED] to flag claims you believe are correct but cannot ground in the available evidence
  • Use [RETRACTED] if you stated something you cannot support upon review

Do not silently drop unsupported claims. Flag them visibly.

4. External Knowledge Restriction

Use only information from:

  • Files and documents in the current project/context
  • Code you have read in this session
  • Content the user has provided directly

Do not rely on training data for:

  • API signatures, function names, or method behaviors — read the actual code
  • Configuration values or defaults — check the actual files
  • What a library or framework does — read its source or docs in the project

When training knowledge is the only source available, say so explicitly: "Based on general knowledge (not verified in this project): ..."

5. Show Reasoning Before Conclusions

For non-trivial analysis:

  1. State what you're examining and why
  2. Present the evidence you found
  3. Walk through your reasoning step by step
  4. Arrive at a conclusion
  5. Note any gaps or assumptions

Scope and Limits

  • This mode favors accuracy over speed and completeness. Responses may be shorter because unsupported content is omitted rather than guessed.
  • Creative and generative tasks (writing copy, brainstorming, drafting) are not well-served by these constraints. If the user asks for creative work while in factual mode, note the tension and ask if they want to proceed in factual mode or relax the constraints for that task.
  • These constraints reduce but do not eliminate hallucination. Always validate critical information independently for high-stakes decisions.

Example Invocations

# Activate for subsequent work
/factual-mode

# Activate and immediately analyze
/factual-mode analyze inc/PageParts/Registry.php for undocumented side effects

# Activate for document review
/factual-mode review the privacy policy in docs/privacy.md for GDPR compliance

# Activate for code audit
/factual-mode what assumptions does the caching layer make about invalidation?

Persistence Signal

While factual-mode is active, prefix substantive responses with a brief marker:

📐 [response continues...]

This confirms the mode is still in effect, especially after /resume or long exchanges where mode state might be uncertain. The marker is minimal — just enough to signal that evidence-grounding constraints are active.



**Modify the activation confirmation to include the marker:**

Change:

Factual mode active. I will ground all claims in evidence, flag uncertainty explicitly, and retract anything I can't support. Accuracy over completeness.


To:

📐 Factual mode active. I will ground all claims in evidence, flag uncertainty explicitly, and retract anything I can't support. Accuracy over completeness.

Frequently asked questions

What does the Factual Mode AI skill do?

Activates evidence-grounded behavioral constraints that minimize hallucination. Use this skill when the user invokes /factual-mode, or when they ask for "factual mode", "grounded mode", "no guessing", "only use what's in front of you", "don't hallucinate", "stick to the facts", "evidence-based only", or any variation requesting that the assistant restrict itself to verifiable claims. Also appropriate when the user is about to analyze documents, audit code, review contracts, or perform any task where accuracy matters more than creativity.

Why use Factual Mode on TypingMind?

Because you install it once and use it with any model. Factual Mode 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 Factual Mode in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/c-kick/hnl-agent-skills/tree/master/factual-mode. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Factual Mode?

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 Factual Mode?

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

Is the Factual Mode AI skill free?

It is published on GitHub by c-kick. Check the repository for licensing terms. 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.

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