Evaluation
CheckedThis "Evaluation" skill assesses text for clarity, tone, and potential biases, helping refine content for better impact and accuracy.
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 mjunaidca/mjs-agent-skills --skill evaluation -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
mjunaidca
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 mjunaidca/mjs-agent-skills at b829650de9.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- b829650de9
- Scanned
- 4 files, 1,058 lines
About this skill
What it does
This skill provides an evaluation capability, allowing AI agents to assess and provide feedback on various inputs. It can be used to analyze text, code, or other data formats based on specified criteria. The agent can then generate a structured report summarizing its findings and suggesting improvements.
When to use it
- Code Review: Have the agent evaluate a piece of code for style, efficiency, and potential errors before submission.
- Content Analysis: Get an AI-powered critique of written content like blog posts or marketing copy.
- Design Feedback: Request feedback on design mockups or prototypes based on usability principles.
- Performance Assessment: Evaluate the output of another agent to determine its effectiveness and identify areas for refinement.
Key capabilities
- Evaluation of text, code, and other data formats.
- Generation of structured reports with findings and suggestions.
- Assessment based on specified criteria.
Example prompts
- "Evaluate this Python code snippet for potential bugs and style issues: [code]"
- "Can you assess this marketing copy for clarity and persuasiveness? [copy]"
- "Provide feedback on this design mockup, focusing on user experience."
Tips & gotchas
The quality of the evaluation depends heavily on the specificity of the criteria provided. Clearly defining what aspects should be evaluated will yield more useful results.