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Confidence Check

Checked
ovachiever·vlatest·other

This skill assesses the plausibility of a statement by cross-referencing it with reliable sources, boosting user trust and critical thinking.

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 ovachiever/droid-tings --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

ovachiever

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

    Makes no network calls.

    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.

  • 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 ovachiever/droid-tings at 7acd12a754.

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

Commit
7acd12a754
Manifest
skills/confidence-check/SKILL.md
Scanned
2 files, 292 lines
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 numerical confidence score alongside each answer, allowing users to gauge the reliability of the information provided. This helps in identifying areas where further verification or clarification might be needed.

When to use it

  • Critical Decision Making: When relying on the AI for decisions with significant consequences (e.g., financial advice, medical recommendations).
  • Research & Fact-Checking: To quickly identify statements that require additional scrutiny and validation from external sources.
  • Complex Problem Solving: When dealing with nuanced or ambiguous questions where a low confidence score signals potential inaccuracies.
  • Educational Purposes: To illustrate the limitations of AI and encourage critical evaluation of generated content.

Key capabilities

  • Provides numerical confidence scores (likely on a scale, though not specified).
  • Integrates directly into agent responses.
  • Identifies potentially unreliable information.

Example prompts

  • "Summarize the key findings of this research paper and provide a confidence score for each point."
  • "Explain the process of photosynthesis, including a confidence level for your explanation."
  • "What are the potential side effects of this medication? Show me the confidence score for each listed effect."

Tips & gotchas

A low confidence score does not necessarily mean the information is incorrect, but it indicates that the AI agent was less certain in its response and requires further verification. Consider cross-referencing with other sources when a low confidence score is returned.