Sauci/.claude/commands/review-questions.md

allowed-tools, argument-hint, description

allowed-tools	argument-hint	description
Read, mcp__sauci-prod__execute_sql, mcp__sauci-prod__list_tables	<pack-name-or-id> [--explicit] [--limit=100]	Review and fix questions for text, targeting, intensity, props, and duplicates

Question Review Command

Review and validate questions: $ARGUMENTS

Task Overview

Analyze questions for issues and suggest fixes across 6 dimensions:

1. Text Phrasing - Improve wording, remove wishy-washy language
2. Audience Targeting - Fix couple/initiator gender targeting
3. Intensity Levels - Correct misassigned intensity ratings
4. Required Props - Identify missing physical props/accessories
5. Inverse Linking - Detect and link inverse question pairs using inverse_of column
6. Deletions - Flag duplicates, redundant, or broken questions

Step 1: Parse Arguments

Extract from $ARGUMENTS:

• Pack identifier: Pack name (partial match) OR pack ID (UUID)
• --explicit: Flag indicating this is an explicit/adult pack (default: false if not specified)
• --limit: Max questions to analyze (default: 100)

Step 2: Fetch Questions

Query the database:

-- If pack name provided (include inverse_of for pair detection):
SELECT q.id, q.text, q.partner_text, q.intensity, q.allowed_couple_genders, q.target_user_genders, q.required_props, q.inverse_of
FROM questions q
JOIN question_packs p ON q.pack_id = p.id
WHERE p.name ILIKE '%<pack_name>%' AND q.deleted_at IS NULL
ORDER BY q.created_at
LIMIT <limit>;

-- If pack ID provided:
SELECT id, text, partner_text, intensity, allowed_couple_genders, target_user_genders, required_props, inverse_of
FROM questions
WHERE pack_id = '<pack_id>' AND deleted_at IS NULL
ORDER BY created_at
LIMIT <limit>;

Also fetch existing props for consistency:

SELECT DISTINCT unnest(required_props) as prop
FROM questions
WHERE required_props IS NOT NULL
ORDER BY prop;

Step 3: Determine Content Type

Check if the pack is explicit:

SELECT p.name, c.is_explicit
FROM question_packs p
JOIN categories c ON p.category_id = c.id
WHERE p.id = '<pack_id>' OR p.name ILIKE '%<pack_name>%'
LIMIT 1;

Use this to set the content type rules below.

Step 4: Analyze Questions

For each question, evaluate against these criteria:

4.1 Text Analysis

Language Rules:

• ALWAYS use "your partner" - NEVER use "me", "I", "you" (as receiver), "him", "her", or gendered pronouns
• Cards are PROPOSALS, NOT interview questions - "Give your partner a massage" not "Would you like to give a massage?"
• Avoid wishy-washy language - NO "Would you...", "Have you ever...", "Do you think...", "Maybe we could..."
• No time-specific words - NO "tonight", "now", "today", "right now"
• Keep concise - ideal length is 5-12 words

Tone Rules (based on explicit flag):

For EXPLICIT packs:

• Use tasteful phrasing for common acts: "Have sex in X" (not "fuck in X"), "Perform oral" or "go down on" (not crude oral terms)
• BUT keep crude/specific terms when they ARE the activity: "Cum on your partner's tits" (cum is the act), "Use a cock ring" (that's the name)
• Rule: crude terms for specific acts/objects, tasteful terms for general sex/oral
• NEVER sanitize "cum" to "come" - they have different meanings

For NON-EXPLICIT packs:

• CRITICAL: No sexual acts, crude language, or NSFW content
• Keep language romantic, sensual, or playful without graphic terms
• Flag explicit content for removal

Partner Text Rules:

• NULL for symmetric activities (both partners do the same thing together)
• FILLED for asymmetric activities (one does something to/for the other)
• text = what the INITIATOR does
• partner_text = what the RECEIVER experiences
• Make partner_text APPEALING - frame receiver's experience positively
• When initiator causes a response (moan, cum, beg), frame as ALLOWING:
  • text: "Make your partner moan" -> partner_text: "Let your partner make you moan"
  • NOT: "Moan for your partner" (sounds forced)

4.2 Intensity Analysis

Check if current intensity matches the activity:

Level	Name	Description	Examples
1	Gentle	Emotional bonding, non-sexual	cooking, cuddling, foot massage
2	Warm	Romantic, affectionate touch	slow dance, sensual massage, kissing
3	Playful	Light sexual exploration	oral, mutual masturbation, light roleplay
4	Steamy	Explicit sex, moderate adventure	intercourse, light bondage, anal play
5	Intense	Advanced/BDSM/extreme	impact play, power dynamics, taboo kinks

4.3 Targeting Analysis

Couple Targeting (allowed_couple_genders):

• DEFAULT: null (ALL couples) unless explicit anatomical requirement
• Restrict to ['male+male', 'female+male'] ONLY if activity requires penis
• Restrict to ['female+male', 'female+female'] ONLY if activity requires vagina
• Sex toys are GENDER-NEUTRAL (vibrators, dildos, plugs work for anyone)

Initiator Targeting (target_user_genders):

• DEFAULT: null (anyone can initiate)
• Only for asymmetric questions (those with partner_text)
• Set based on who does the action in "text" field:
  • "Swallow your partner's cum" -> partner has penis -> initiator: ['female'] in M+F
  • "Deep throat your partner" -> partner has penis -> ['female'] in M+F
  • "Give your partner a massage" -> gender-neutral -> null

4.4 Props Analysis

Rules:

• Props are physical items/accessories, not body parts or acts
• Use lowercase, short, singular names (e.g., "blindfold", "remote vibrator")
• Reuse existing prop names from the catalog when possible
• If no props are required, set to null

4.5 Inverse Linking Analysis

Purpose: Detect inverse question pairs and link them using the inverse_of database column.

Detection:

1. For each asymmetric question (has partner_text), look for its inverse:
   • Inverse exists if another question has: text = this question's partner_text AND partner_text = this question's text
2. Check if the inverse_of column is correctly set

Fixes:

• If pair exists but not linked: set inverse_of on the second question to point to the first
• Symmetric questions should have inverse_of = NULL

4.6 Deletion Analysis

Deletion Categories:

• duplicate: Same core action as another question
• redundant: Minor variation with no added value
• off-tone: Violates explicit vs non-explicit rules
• unsafe: Coercion, minors, illegal acts, or consent violations
• too-vague: Not actionable or not a clear proposal
• broken: Grammar too broken to repair without inventing content
• off-topic: Not relevant to a couples intimacy app

Rules:

• Prefer edits over deletions when possible
• For duplicates: delete the weaker/less specific version
• Do NOT delete for minor wording issues

CRITICAL: Inverse Questions are NOT Duplicates

Asymmetric questions MUST exist in pairs (original + inverse). These are NOT duplicates:

Question A:
  text: "Spank your partner"
  partner_text: "Be spanked by your partner"

Question B (INVERSE - NOT A DUPLICATE):
  text: "Be spanked by your partner"
  partner_text: "Spank your partner"

These are intentionally paired so both partners get asked about both roles. When reviewing:

• If you see two questions where one's text matches the other's partner_text, they are a valid inverse pair
• Do NOT flag inverse pairs as duplicates or redundant
• Only flag as duplicate if TWO questions have the SAME text (or nearly identical text)

Step 5: Output Results

Present findings in a structured format:

Summary

Category	Count
Text fixes	X
Intensity fixes	X
Targeting fixes	X
Props fixes	X
Inverse linking fixes	X
Deletions suggested	X
No changes needed	X

Suggested Changes

For each question needing changes:

**Question ID:** <id>
**Current Text:** <text>
**Current Partner Text:** <partner_text or null>
**Current Intensity:** <intensity>
**Current inverse_of:** <uuid or null>

Issues Found:
- [ ] Text: <description of issue>
- [ ] Intensity: <current> -> <suggested> (<reason>)
- [ ] Targeting: <description>
- [ ] Props: <current> -> <suggested>
- [ ] Inverse Link: <missing/broken> - <inverse question id if found>
- [ ] DELETE: <category> - <reason>

Suggested Fix:
- Text: "<new text>"
- Partner Text: "<new partner_text>" or null
- Intensity: <new intensity>
- Couple Targets: <new allowed_couple_genders or null>
- Initiator Targets: <new target_user_genders or null>
- Required Props: <new required_props or null>
- inverse_of: <uuid or null>

SQL to Apply Fixes

After user approval, provide UPDATE statements:

-- Text/Partner Text/Intensity fixes
UPDATE questions SET
  text = '<new_text>',
  partner_text = '<new_partner_text>',
  intensity = <new_intensity>
WHERE id = '<question_id>';

-- Targeting fixes
UPDATE questions SET
  allowed_couple_genders = '<new_targets>',
  target_user_genders = '<new_initiator>'
WHERE id = '<question_id>';

-- Props fixes
UPDATE questions SET
  required_props = ARRAY[<new_props>]
WHERE id = '<question_id>';

-- Inverse linking fixes
UPDATE questions SET inverse_of = '<primary_question_id>' WHERE id = '<inverse_question_id>';

-- Deletions (soft delete)
UPDATE questions SET deleted_at = NOW() WHERE id IN ('<id1>', '<id2>', ...);

Example Usage

/review-questions "Foreplay Favorites"
/review-questions "Kink Discovery" --explicit
/review-questions 123e4567-e89b-12d3-a456-426614174000 --limit=50

Guidelines

• DO ask for clarification if pack name matches multiple packs
• DO group similar issues together for batch fixes
• DO prioritize safety issues (delete unsafe content first)
• DO preserve the core intent of questions when suggesting text fixes
• DO detect and link inverse pairs using the inverse_of column
• DON'T change questions that are already well-formed
• DON'T suggest overly restrictive targeting (prefer inclusive by default)
• DON'T create new prop names when existing ones match
• DON'T flag inverse pairs as duplicates (one's text = other's partner_text)
• DON'T forget to set inverse_of for detected inverse pairs