prompt pack release qa
Audit prompt products for release blockers, inconsistencies, and buyer friction using a P0-P3 severity scale.
$5
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentsprompt pack release qa
Example session with this skill installed
Audit my 'Python Refactor Pro' prompt pack. The description says it handles legacy code, but the prompt instructions only mention modern syntax. Here is the prompt text: [system prompt text...]
- Read your context and instructions
- Compiled the prompt release qa
I have completed the audit for the 'Python Refactor Pro' prompt pack. The review identified a critical inconsistency between the marketing claims and the instruction set.
Audit Report - Python Refactor Pro
Section 1 – Executive Summary
Readiness Level: Not Ready. The package contains one P0 blocker regarding functional inconsistency and two P2 moderate issues regarding missing guidance. The prompt fails to deliver on the primary value proposition mentioned in the description.
Section 2 – Asset Map
| Asset | Type | Status |
|---|---|---|
| Python Refactor Pro Description | Marketing Copy | Analyzed |
| System Prompt Text | Prompt Logic | Analyzed |
| Example Outputs | User Sample | Not Supplied |
Section 3 – Findings
-
Dimension: Inconsistencies
Severity: P0
Evidence: Description claims "handles legacy code," but Prompt Text lines 12-15 explicitly state "Focus exclusively on PEP 8 and Python 3.10+ syntax."
Issue: The prompt actively rejects the legacy code it claims to support.
Recommended Fix: Update lines 12-15 to: "Analyze input for both legacy Python 2.x patterns and modern 3.x syntax. Provide migration paths for deprecated libraries." -
Dimension: Missing Guidance
Severity: P2
Evidence: "Not supplied"
Issue: No instructions for the user on how to handle external dependencies or library-specific refactoring.
Recommended Fix: Add a 'Setup' section to the user guide explaining that users should paste relevant library versions for better context. -
Dimension: Repetition
Severity: P3
Evidence: "Ensure the code is clean. Make sure the output is readable."
Issue: Redundant instructions consuming tokens.
Recommended Fix: Consolidate to: "Output clean, PEP 8 compliant code."
Section 4 – Release Decision
RELEASE DECISION: NOT READY
BLOCKERS REMAINING: 1
NEXT ACTION: Align the system prompt instructions with the legacy code support claims in your description.
AUDIT ID: RPQA-d9e2b8
Next steps
- Apply the P0 fix to line 12 of your system prompt.
- Consolidate redundant instructions to save tokens.
- Resubmit the prompt for a final P0 clearance check.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Publishing a prompt pack with broken instructions, redundant boilerplate, or legal risks damages your reputation and leads to refund requests. Sellers often miss friction points or inconsistencies because they are too close to their own work.
What it does
- Inventories all supplied assets, prompts, and marketing claims to ensure package completeness.
- Identifies P0 blockers including legal risks, broken functionality, and platform ToS violations.
- Detects buyer friction such as missing setup steps or confusing prerequisites.
- Flags weak differentiation where prompts lack substantive value over free alternatives.
- Generates targeted code-style patches for identified issues rather than vague suggestions.
Why this beats prompting it yourself
General-purpose prompts often provide generic praise or surface-level edits. This skill enforces a rigorous P0-P3 severity scale and mandatory asset mapping, ensuring every claim is backed by evidence found in your files. It prevents the AI from "hallucinating" that your product is perfect by requiring exact quotes for every audit dimension.
Use cases
- Reviewing a Gumroad prompt pack before the final launch.
- Auditing complex system prompts for redundant logic or "token waste."
- Checking marketing copy against actual prompt behavior to prevent false claims.
- Identifying missing edge-case handling in specialized B2B prompts.
Known limitations
Cannot evaluate dimensions if the user does not provide the corresponding assets. It does not perform live execution testing of prompts.
Requires manual input of prompt text and descriptions. Cannot perform live API testing or execute prompts in real-time. Missing assets will result in skipped audit dimensions.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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