Skip to content
TrustedSkillsbeta
Back to all skills

Confidence Check

Checked
microck·vlatest·other

This skill assesses the plausibility of a statement by cross-referencing it with reliable sources, helping users verify information and avoid misinformation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it Confidence Check, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add microck/ordinary-claude-skills --skill "Confidence Check" -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

microck

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Only contacts known or declared hosts: github.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    github.comsource host

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned microck/ordinary-claude-skills at 1056d293d4.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
1056d293d4
Manifest
skills_all/confidence-check/SKILL.md
Scanned
4 files, 268 lines
Copies in repo
2 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Confidence Check skill assesses the certainty of an AI agent's responses. It provides a confidence score, ranging from 0 to 100, indicating how sure the agent is about its answer. This allows users to gauge the reliability of information and determine if further verification is needed.

When to use it

  • Fact Verification: When you need to confirm the accuracy of an AI-generated statement before acting on it.
  • Complex Reasoning: When dealing with intricate questions where multiple interpretations are possible, assess how confident the agent is in its chosen path.
  • Decision Making: Use the confidence score as one factor when making decisions based on information provided by the AI agent.
  • Identifying Knowledge Gaps: Low confidence scores can highlight areas where the agent's knowledge is limited or uncertain.

Key capabilities

  • Provides a numerical confidence score (0-100).
  • Evaluates certainty in responses.
  • Helps assess reliability of AI output.

Example prompts

  • "What is the capital of France? Confidence Check."
  • "Explain quantum entanglement. Provide a Confidence Check after your explanation."
  • "Summarize this article: [article link]. Please also give me a confidence score for the summary."

Tips & gotchas

The skill relies on the underlying AI model's ability to self-assess; therefore, its accuracy is dependent on the model itself. A high confidence score doesn’t guarantee correctness, and a low score doesn’t necessarily mean the information is wrong – it just means the agent isn't sure.