promptbase listing conversion builder
Transforms raw prompts into factual, marketplace-ready listing packages with verified claims and structured FAQs.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+20 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
OpenClaw
Manus
Grok+17 agentspromptbase listing conversion builder
Example session with this skill installed
Generate a listing for this prompt: [System Prompt: Analyze text for 5 specific cognitive biases (Anchoring, Confirmation, etc.) and output a Markdown table with severity scores 1-10.]
- Read your context and instructions
- Compiled the promptbase listing conversion
- Generated the document
I have analyzed the source prompt. Every claim in the listing below is verified against the logic of your cognitive bias analysis system.
Listing Title
Cognitive Bias Analysis and Severity Scorer for Researchers
Listing Description
Positioning: This prompt provides a deterministic framework for identifying cognitive biases in text, delivering a structured markdown scoring matrix for academic or professional audit.
What it does: It scans input text specifically for five cognitive biases: Anchoring, Confirmation, Availability Heuristic, Self-Serving Bias, and Framing Effect. It evaluates the presence of these biases and assigns a severity score from 1 to 10.
Who it's for: Researchers, editors, and critical thinkers who need to audit content for logical fallacies.
What you get:
- A structured Markdown table.
- Categorized bias identification.
- 1-10 severity scoring for each identified bias.
How it works: The prompt uses a structured classification step followed by a scoring heuristic. It cross-references the input text against defined bias definitions before generating the final table.
Limitations: Only detects the five specified biases. It does not provide psychological counseling or factual verification of the input text.
Use cases:
- Auditing news articles for framing bias.
- Reviewing internal reports for confirmation bias.
- Academic analysis of historical speeches.
Tags
psychology, analysis, research, markdown, table, researcher, bias-detection, structured-output
FAQ
- Which biases are supported? It covers Anchoring, Confirmation, Availability, Self-Serving, and Framing biases.
- Can I add more biases? Yes, you can append definitions to the system instructions.
- What is the output format? A standard Markdown table compatible with any MD editor.
- Does it check for factual truth? No, it only analyzes the linguistic structure and logical framing.
- What model is recommended? Optimized for GPT-4 or Claude 3 Opus for nuanced detection.
Preview Example
Input
"The project failed because the marketing team didn't listen to my initial, correct plan. Everyone I've talked to agrees we should have stuck to the first draft."
Output
| Bias Type | Severity (1-10) | Evidence |
|---|---|---|
| Self-Serving Bias | 9 | Attributes failure to external team while claiming personal correctness. |
| Confirmation Bias | 7 | Cites "everyone I've talked to" as validation without diverse feedback. |
Objection Handlers
Is it too specific? It focuses on the 5 most common biases to ensure high accuracy rather than being a "catch-all" tool.
- Does it work on short text? Yes, but accuracy improves with at least 2-3 paragraphs of context.
Can I use it for legal work? It is a research aid, not a substitute for professional legal or psychological audit.
Publish Checklist (Validated)
| Check | Status | Notes |
|---|---|---|
| No unsupported claims | Pass | All scores and biases are in the source. |
| Title ≤ 70 chars | Pass | 59 characters. |
| Tags ≤ 10 | Pass | 8 tags generated. |
| FAQ ≥ 5 items | Pass | 5 items provided. |
Next steps
- Copy the Listing Title and Description into your marketplace editor.
- Use the provided Preview Example to generate your listing image.
- Verify the Tags match the marketplace's specific category requirements.
promptbase-listing-conversion-builder.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
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What you get
About this skill
The problem
Writing marketplace listings for prompts is time-consuming and often leads to exaggerated claims that get rejected or result in poor reviews. Developers struggle to translate raw prompt logic into high-converting, factual descriptions that satisfy both marketplace moderators and buyers.
What it does
- Extracts verifiable product facts, input variables, and processing constraints directly from your source prompt.
- Audits all performance claims to ensure they are traceable to the source code, replacing marketing fluff with factual evidence.
- Generates a complete listing package including an SEO-optimized title, description, tags, and FAQ.
- Builds a validation report and publish checklist to ensure compliance with marketplace standards.
Why this beats prompting it yourself
Generic LLM prompts often hallucinate features or use forbidden marketing buzzwords that trigger marketplace rejections. This skill enforces a strict verification workflow, ensuring every word in your listing is supported by the actual logic of your prompt, reducing refund rates and increasing trust.
Use cases
- Converting complex prompt systems into paste-ready PromptBase listings.
- Auditing existing listings to remove unsupported claims and improve clarity.
- Creating realistic previews and FAQ sections based on actual prompt failure modes.
Known limitations
Output does not include pricing recommendations or sales strategy. It requires a functional source prompt to extract facts.
How to install
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