Evaluate Skill
CheckedThis skill assesses a user’s skills based on provided details, offering insights for targeted learning and development.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add maxoreric/sop-engine --skill evaluate-skill -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
maxoreric
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.
Automated safety checks
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 maxoreric/sop-engine at c90ff7adff.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- c90ff7adff
- Manifest
- skills/evaluate-skill/SKILL.md
- Scanned
- 2 files, 182 lines
- Copies in repo
- 2 — all of them scanned
About this skill
What it does
This skill allows an AI agent to assess and provide feedback on the quality of a given piece of work. It can analyze text, code, or other structured data based on specified criteria. The evaluation includes identifying strengths and weaknesses, suggesting improvements, and assigning a relative score.
When to use it
- Code Review: Have the AI evaluate a snippet of code for style, efficiency, and potential errors before submission.
- Writing Assessment: Get feedback on drafts of documents, reports, or creative writing pieces regarding clarity, grammar, and overall impact.
- Design Critique: Receive an assessment of design concepts based on established principles like usability and aesthetics.
- Process Optimization: Evaluate the effectiveness of a workflow or process and identify areas for improvement.
Key capabilities
- Evaluates text-based content
- Provides constructive feedback
- Identifies strengths and weaknesses
- Suggests improvements
- Assigns relative scores
Example prompts
- "Evaluate this Python code snippet: [code]"
- "Please critique this email draft for clarity and tone."
- "Assess the design of this landing page based on usability principles."
Tips & gotchas
The quality of the evaluation depends heavily on the specificity of the criteria provided. Clearly defining what constitutes "good" or "bad" will yield more useful results.