Prompt Details
Model
(claude-4-7-opus)
Token size
1,476
Example input
[TARGET_OUTPUT]: The onboarding flow introduces unnecessary friction at the account verification stage. Users are asked to complete three sequential actions before accessing core functionality, which increases abandonment risk. Key observations: - Email verification lacks progress feedback - CTA language shifts between screens - Mobile form fields exceed optimal input length Recommendation: Reduce verification steps to one primary action and delay secondary profile enrichment until post-activation.
[QUALITY_RATINGS]: Structure: 8/10 Tone: 7/10 Depth: 6/10 Specificity: 8/10
[USE_CONTEXT]: Replicating structured UX audit reports for SaaS onboarding reviews.
Example output
## P.R.E.X.™ ANALYSIS — UX AUDIT REPORT
---
### ── FINDING 01 ────────────────────────────────
**TYPE:** Pattern Signal
**SIGNAL:** Mixed format — prose lead + bullet observations + imperative recommendation
**EVIDENCE:** Opening paragraph in declarative prose, mid-section shifts to a 3-item bullet list, closes with a "Recommendation:" block in imperative voice
**INFERENCE:** The original prompt instructed a structured audit format with distinct sections for diagnosis, evidence, and action — likely via explicit section labels or a template scaffold
**CONFIDENCE:** 87%
---
### ── FINDING 02 ────────────────────────────────
**TYPE:** Role Signal
**SIGNAL:** Practitioner-level UX vocabulary with measured authority
**EVIDENCE:** Terms like "friction," "abandonment risk," "CTA language," "post-activation," "profile enrichment" — all domain-precise without being academic
**INFERENCE:** Role was defined as a UX/product specialist, not a general consultant. The vocabulary suggests a prompt that named the domain explicitly (UX audit, onboarding review, or product analysis)
**CONFIDENCE:** 85%
---
### ── FINDING 03 ────────────────────────────────
**TYPE:** Pattern Signal
**SIGNAL:** Flat assertion style — no hedging, no qualifications
**EVIDENCE:** "introduces unnecessary friction," "increases abandonment risk," "Reduce verification steps" — zero softeners ("may," "might consider," "could")
**INFERENCE:** The prompt either specified a direct, confident tone or defined a role with high-authority stance (senior reviewer, lead auditor). No instruction to hedge was present.
**CONFIDENCE:** 78%
---
### ── FINDING 04 ────────────────────────────────
**TYPE:** Constraint Signal
**SIGNAL:** Deliberately shallow depth — observations are named but not quantified or explained
**EVIDENCE:** "CTA language shifts between screens" is stated without specifying which screens or what the shift is; depth score of 6/10 confirms this ceiling
**INFERENCE:** The prompt likely imposed a brevity constraint (word limit, "concise," or "summary format") — or depth was limited by the absence of input data (no actual screenshots or metrics were provided)
**CONFIDENCE:** 72%
---
### ── FINDING 05 ────────────────────────────────
**TYPE:** Structure Signal
**SIGNAL:** Numbered-action recommendation following prioritized reduction logic
**EVIDENCE:** "Reduce to one primary action and delay secondary profile enrichment" — implies prioritization framework (primary vs. secondary actions), not just a list of fixes
**INFERENCE:** Prompt may have included an instruction to prioritize recommendations by impact or to distinguish between critical-path and post-activation actions
**CONFIDENCE:** 68%
---
### ── FINDING 06 ────────────────────────────────
**TYPE:** Persona Signal
**SIGNAL:** Detached third-person analytical stance — no "I" or "we"
**EVIDENCE:** No first-person language anywhere in the output; the subject is always the product or the user, never the reviewer
**INFERENCE:** Role framing was analytical/advisory rather than collaborative. The prompt likely defined the output as a report artifact, not a conversational response.
**CONFIDENCE:** 80%
---
## ── RECONSTRUCTION CANDIDATES ─────────────────
### CANDIDATE A — Structured UX Audit Template
**Confidence: 84% Signals: 6**
```
You are a senior UX auditor specializing in SaaS onboarding
flows. When given a product area or feature description,
produce a concise audit report using this structure:
1. Opening diagnosis: one to two sentences identifying the
primary friction point and its risk implication.
2. Key observations: three to five bullet points identifying
specific, named UX issues. Be precise — name the element,
name the problem.
3. Recommendation: one to two sentences of direct, actionable
guidance. Prioritize the critical path action first; defer
secondary improvements to post-activation stages.
Tone: direct and confident. No hedging. No first-person.
Format: report artifact, not conversation.
```
---
### CANDIDATE B — Role-First with Implicit Format
**Confidence: 71% Signals: 4**
```
Act as a UX product reviewer conducting a SaaS onboarding
audit. Analyze the described flow for friction points,
drop-off risks, and inconsistent UI patterns. Lead with
the core problem, support with specific observations,
and close with a prioritized recommendation. Keep it
brief and professional. Use bullet points for observations.
```
---
### CANDIDATE C — Minimal Prompt, High-Signal Role
**Confidence: 58% Signals: 3**
```
You are a SaaS UX auditor. Review the following onboarding
flow and identify friction points, UX inconsistencies, and
one concrete improvement recommendation. Be direct and specific.
```
*Note: Below 60% confidence threshold on candidate-level basis — included as a baseline test variant only. Expect lower structural consistency across runs.*
---
## ── IMPLEMENTATION NOTE ───────────────────────
Test **CANDIDATE A** first — it replicates both the format scaffold and the role precision that account for the high Structure (8) and Specificity (8) scores. If depth remains at 6/10 and you need richer analysis, add this line to Candidate A: *"For each observation, briefly explain the UX principle being violated."* To replicate at scale for SaaS onboarding reviews, parameterize the flow description as a variable input block and keep the role and format instructions fixed.
---
By purchasing this prompt, you agree to our terms of service
CLAUDE-4-7-OPUS
Prompt Reverse Engineer™ applies the P.R.E.X.™ methodology to extract structural signals from any AI-generated text and build 2–3 ranked prompt reconstructions, each backed by traceable evidence.
**What you get per run:**
- Full signal scan of your target output (pattern, role, constraint signals)
- Evidence chain — every inference labeled with the exact feature that supports it
- 2–3 candidate prompts ranked by confidence percentage
- Signal Screen gate that flags thin evidence instead of fabr
...more
Added 2 days ago
