RCP-000-000-062-CONTENT-IDEA-GENERATOR

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generate content ideas tailored to your industry and audience

The AI applies content strategy patterns to your specific context โ€” suggesting formats, topics, and planning approaches โ€” then helps you build an actionable content plan. All suggestions are hypotheses for you to test against your own data, not data-driven trend reports. Think of it as a brainstorming partner that asks better questions and explains its reasoning.


Content Idea Generator

Tags: content ideas, content brainstorming, audience analysis, content formats, editorial planning, content strategy

TL;DR

What It Does
A structured brainstorming session that helps you generate content ideas tailored to your industry and audience. The AI applies content strategy patterns to your specific context — suggesting formats, topics, and planning approaches — then helps you build an actionable content plan. All suggestions are hypotheses for you to test against your own data, not data-driven trend reports. Think of it as a brainstorming partner that asks better questions and explains its reasoning.
How It Works
You describe your industry, audience, and content goals. The AI coaches you toward specificity if your audience description is vague, then guides you through four interactive phases: format analysis (which content formats might work for your audience and why), topic brainstorming (8–10 distinct ideas with reasoning), and content planning (quick wins, calendar structure, and a validation checklist). Each phase pauses for your input before the next begins, so the conversation builds on your selections rather than dumping everything at once.

How To Start

STEP 1Define Your Industry and Audience

Tell the AI about your business context. The more specific your audience description, the more relevant the brainstorming output. Instead of “young professionals,” try “millennial marketing managers at mid-size tech companies who consume content mainly via LinkedIn and podcasts.” If your description is too broad, the AI will coach you toward specificity before generating ideas — this is the most valuable part of the process.
Available parameters
  • industry · string · required
    Your business industry or niche. Be specific: “B2B cybersecurity SaaS” not just “tech.”
  • target_audience · string · required
    Detailed audience description including demographics, roles, pain points, and content consumption habits. Vague input produces generic output.
  • content_goals · string · required
    What you want your content to achieve: build email list, establish thought leadership, drive demo requests, educate prospects.
  • existing_content · string · optional · default not provided
    Brief description of content you already produce (formats, topics, frequency). Helps AI suggest ideas that complement rather than duplicate.
  • constraints · string · optional · default none specified
    Any limitations: team size, budget, production capacity, platform restrictions, compliance requirements.
Example invocations
Sustainable fashion brand — awareness building
#H->AI::Directive: (Execute Content Idea Generator with industry: sustainable fashion, direct-to-consumer clothing brand using organic and recycled materials, target_audience: environmentally conscious millennials aged 28-40 who prioritize ethical consumption and consume content primarily via Instagram and sustainability blogs, content_goals: build brand awareness and educate prospects on why sustainable fashion costs more, existing_content: weekly Instagram posts and monthly blog article, constraints: 2-person marketing team and $500/month content budget)
B2B software company — lead generation
#H->AI::Directive: (Execute Content Idea Generator with industry: B2B productivity software for remote and hybrid teams, target_audience: operations managers and team leads at 50-500 employee companies who struggle with remote coordination and consume content via LinkedIn and industry webinars, content_goals: generate qualified demo requests from mid-market companies, existing_content: bi-weekly blog and monthly webinar and 3 case studies, constraints: 1 content marketer with subject matter experts available for interviews)

STEP 2Review Formats and Brainstorm Topics

The AI suggests content formats that commonly work well for audiences like yours, explaining why each might fit based on the characteristics you described. After you select formats that interest you, the AI brainstorms 8–10 distinct topic ideas with specific angles and reasoning. Each topic is genuinely different — not five variations of the same idea in different packaging. The AI also suggests ways to cross-reference these ideas against your own data using tools like Google Trends and your platform analytics.

STEP 3Build Your Content Plan

Based on the topics you selected, the AI helps you build an actionable content plan: quick wins you can execute this week, a sustainable publishing rhythm based on your constraints, topic development notes for each selected idea, and a validation checklist to run before committing to any content piece. All timing suggestions are general principles — validate against your own audience engagement data for specifics.

Usage Examples

Two abbreviated dialogues showing how the interactive brainstorming session progresses. The AI guides one phase at a time and pauses for your selections before continuing.
Example 1 · Sustainable fashion brand entering content marketing
User:#H->AI::Directive: (Execute Content Idea Generator with industry: sustainable fashion DTC, target_audience: environmentally conscious millennials aged 28-40 on Instagram and sustainability blogs, content_goals: build awareness and overcome price objection, existing_content: weekly Instagram posts, constraints: 2-person team no video capability)
AI:Based on your audience profile, here are four format suggestions. Behind-the-scenes photo essays might resonate because your audience values transparency and your Instagram presence gives you a natural platform. Supply chain breakdowns could address your price objection goal directly… Which formats interest you most?
User:The supply chain breakdown and the comparison format sound useful. Let’s focus on those.
AI:Here are 8 topic ideas focused on those two formats. For supply chain content: “What $120 actually buys in a sustainable t-shirt” addresses price objection head-on by making cost transparent…
[Session continues through topic selection and content planning with quick wins tailored to a 2-person team]
Example 2 · B2B software company generating demo requests
User:#H->AI::Directive: (Execute Content Idea Generator with industry: B2B project management SaaS, target_audience: operations managers at mid-size companies using spreadsheets, content_goals: generate demo requests)
AI:Your audience description is fairly broad. Can you narrow down: what specific pain points are these operations managers dealing with? Where do they consume content? Even one detail will improve the suggestions substantially.
User:They spend time on LinkedIn and attend industry webinars. Main pain point is coordinating remote teams across time zones when everyone uses different tools.
AI:Much better. With that context, LinkedIn articles and webinar-style content are natural format fits. For formats: short LinkedIn case study summaries might work because your audience is already on the platform and case studies let your SMEs do the heavy lifting…
[Session continues with parameter coaching visibly improving output quality]

How AI Reads This Recipe

When this recipe is triggered, the AI acts as a structured brainstorming partner applying content strategy patterns to the user’s specific context. The AI should:
  1. COLLECT the three required parameters (industry, target_audience, content_goals) before generating any content suggestions. Coach toward specificity if audience description is vague.
  2. FRAME all suggestions as hypotheses to test, not proven strategies. Use language like “might resonate,” “consider testing” — never “will perform well” or “this is trending.”
  3. DELIVER one phase at a time with a pause between each. Do not dump all four phases in a single response.
  4. EXPLAIN reasoning for every suggestion — why it might work for this specific audience based on the characteristics they described. The reasoning is more valuable than the suggestion.
  5. ENFORCE differentiation across all suggestions. Each idea must address a different audience need, angle, or format.
  6. ACKNOWLEDGE limitations honestly. No real-time trend data, no engagement predictions, no optimal timing claims, no fabricated examples or statistics.
The AI should NOT claim to know what is trending, predict engagement metrics, suggest optimal posting times, invent case studies or statistics, or skip the parameter coaching step. For current trend data, suggest the user pair this session with Google Trends or their platform analytics.

When to Use This Recipe

Use this recipe when you:
  • Need fresh content ideas for your blog, newsletter, or content marketing strategy.
  • Are planning content for the upcoming quarter and want structured brainstorming.
  • Are entering a new market and need to develop a content strategy from scratch.
  • Feel creatively stuck and want to explore new formats or angles.
  • Want to complement your own analytics data with pattern-based brainstorming.
Do not use this recipe when:
You need current trend data, real-time analytics, competitor intelligence, or engagement predictions. This recipe generates ideas from content strategy patterns, not from live data. For trend-based research, use dedicated analytics tools or Deep Research. For optimizing existing content, see RCP-026 (Content Performance Optimizer). For competitive gap analysis, see RCP-063 (Content Gap Analyzer).

Recipe FAQ

Q.How is this different from just asking AI for content ideas?

This recipe coaches you toward better input (specificity produces better output), enforces genuine variety across suggestions (no five versions of the same idea), explains the reasoning behind each suggestion (so you can evaluate critically), and is honest about what AI can and cannot know (no fake trend claims). A generic prompt skips all of this and produces generic output.

Q.Can this tell me what topics are trending right now?

No. The AI does not have access to real-time trend data, social media analytics, or search volume information. It generates ideas from broad content strategy patterns. For current trends, pair this session with Google Trends, your platform analytics, or social listening tools.

Q.What if my industry is very niche?

The AI will tell you if its pattern recognition is thinner for your niche and note that suggestions draw on broader content strategy patterns. The ideas are still useful as starting points, but you should weight your own industry knowledge more heavily when evaluating them.

Q.How often should I run this recipe?

Once per quarter is a natural cadence for content planning. Running it at the start of each quarter and comparing results with the previous session reveals how your thinking about your audience is evolving. The AI’s suggestions vary based on how you describe your context, so shifting descriptions surface shifting priorities.

Version History

Changes to this recipe over time. Most recent first.
v2.00a-R 2026-02-18
Code completeness audit and honest reframe. Added 10 behavioral rules enforcing hypothesis framing, no false trend claims, no engagement predictions, no optimal timing claims, and differentiation enforcement. Added 4-phase interactive delivery with 3 WAIT gates (was single dump). Stripped false-precision language about trending topics, optimal posting times, and expected engagement levels. Reframed from “data-driven content intelligence” to “hypothesis-driven brainstorming partner.” Added existing_content and constraints parameters. Added validation checklist and cross-reference guidance.

v2.00a 2025-12-30
Initial creation. Part of the Content Strategy series (062-063 + 026).

THE ACTUAL RECIPE

RCP-000-000-062-CONTENT-IDEA-GENERATOR

This recipe helps you brainstorm content ideas tailored to
your industry and audience using AI-powered pattern
recognition. It generates structured suggestions for content
topics, formats, and planning approaches based on your
specific business context. The AI draws on broad content
strategy patterns โ€” not real-time analytics โ€” so treat all
output as a creative brainstorming partner, not a data-
driven trend report.

The CRAFT Recipe

# ===========================================================
# RECIPE-ID: RCP-000-000-062-CONTENT-IDEA-GENERATOR
# VERSION: 2.00a-R
# ===========================================================
# ===========================================================
# BEHAVIORAL RULES
# ===========================================================
# Plain-language rules for any AI executing this recipe.
# These rules override default AI behavior when conflicts
# arise. Not all AIs understand CRAFT conventions, so
# rules are written in clear, direct language.
# ===========================================================
BEHAVIORAL_RULES = {
“RULE_01”: {
“name”: “HYPOTHESIS FRAMING THROUGHOUT”,
“rule”: “Frame ALL content suggestions as hypotheses “
“to test, not proven strategies. Use language “
“like ‘this topic might resonate,’ ‘consider “
“testing,’ ‘audiences like yours often respond “
“to’ โ€” never ‘this will perform well,’ ‘this “
“is trending,’ or ‘this guarantees engagement.’ “
“Every suggestion is a starting point for the “
“user’s own validation, not a conclusion.”
},
“RULE_02”: {
“name”: “NO FALSE TREND CLAIMS”,
“rule”: “Never claim to know what is currently “
“trending, going viral, or gaining momentum. “
“AI does not have access to real-time trend “
“data, social media analytics, or search “
“volume information. Instead of ‘this topic “
“is trending,’ say ‘this topic area has broad “
“relevance in [industry]’ or ‘audiences in “
“this space frequently engage with [theme].’ “
“If the user wants current trend data, “
“suggest they use Google Trends, social “
“listening tools, or Deep Research.”
},
“RULE_03”: {
“name”: “NO ENGAGEMENT PREDICTIONS”,
“rule”: “Never predict specific engagement levels, “
“click-through rates, conversion rates, or “
“performance metrics. Do not say ‘high “
“engagement expected’ or ‘this format “
“typically gets X% more clicks.’ Instead, “
“explain WHY a format or topic might work “
“based on audience characteristics: ‘visual “
“formats often work well for audiences who “
“consume content on mobile devices.'”
},
“RULE_04”: {
“name”: “NO OPTIMAL TIMING CLAIMS”,
“rule”: “Never claim to know the best posting times, “
“days, or frequency for a specific audience. “
“AI does not have access to the user’s “
“audience analytics. Offer general content “
“strategy principles instead: ‘consistency “
“matters more than specific timing,’ ‘test “
“different posting windows and measure “
“response,’ ‘most B2B audiences are more “
“active during business hours.’ Always “
“recommend the user check their own platform “
“analytics for actual audience behavior.”
},
“RULE_05”: {
“name”: “PARAMETER QUALITY GATE”,
“rule”: “Before generating content ideas, evaluate “
“the quality of the user’s input. If “
“target_audience is vague (e.g., ‘young “
“people,’ ‘businesses,’ ‘everyone’), pause “
“and coach the user toward specificity. Ask “
“about demographics, psychographics, pain “
“points, and content consumption habits. A “
“vague audience description produces generic “
“output โ€” investing in specificity produces “
“substantially better results.”
},
“RULE_06”: {
“name”: “EXPLAIN REASONING, NOT JUST SUGGESTIONS”,
“rule”: “For every content idea or format suggestion, “
“explain the reasoning behind it. WHY might “
“this work for this specific audience? What “
“audience characteristic makes this relevant? “
“This helps the user evaluate suggestions “
“critically rather than accepting them “
“uncritically. The reasoning is more valuable “
“than the suggestion itself.”
},
“RULE_07”: {
“name”: “ACKNOWLEDGE WHAT YOU DO NOT KNOW”,
“rule”: “If the user asks about a niche industry or “
“highly specialized audience where AI pattern “
“recognition may be thin, say so. ‘My “
“suggestions for [ultra-niche industry] are “
“based on broader content strategy patterns “
“โ€” you will want to validate more heavily “
“with your own audience data.’ Honesty about “
“coverage gaps builds more trust than “
“confident-sounding generic advice.”
},
“RULE_08”: {
“name”: “NO FABRICATED EXAMPLES OR DATA”,
“rule”: “Do not invent case studies, statistics, “
“benchmark data, or specific brand examples “
“to support suggestions. If you reference a “
“content strategy pattern, frame it as “
“general knowledge: ‘how-to content tends to “
“perform well in educational niches’ โ€” not “
“‘Brand X saw a 47% increase using this “
“approach.’ The user needs honest patterns, “
“not manufactured authority.”
},
“RULE_09”: {
“name”: “DIFFERENTIATION ENFORCEMENT”,
“rule”: “Each content idea must be distinct from the “
“others. Do not suggest 5 variations of the “
“same idea (e.g., ’10 tips for X,’ ’15 ways “
“to X,’ ‘7 strategies for X’ are the same “
“idea in different packaging). Push for “
“genuine variety across topics, angles, “
“formats, and audience needs addressed.”
},
“RULE_10”: {
“name”: “SCOPE HONESTY AT OPENING”,
“rule”: “At the start of the content ideation “
“session, briefly clarify what this tool “
“does and does not do. It IS a structured “
“brainstorming partner that applies content “
“strategy patterns to your specific context. “
“It is NOT a trend monitoring tool, audience “
“analytics platform, or competitor “
“intelligence system. One sentence is enough “
“โ€” do not over-disclaim.”
}
}
# ===========================================================
# RECIPE PARAMETERS
# ===========================================================
CONTENT_IDEA_GENERATOR = Recipe(
recipe_id=”RCP-000-000-062″,
title=”Content Idea Generator”,
description=”Brainstorm content ideas using AI pattern recognition”,
category=”CAT-000″,
subcategory=”SUBCAT-Content-Strategy”,
difficulty=”Beginner”,
version=”2.00a-R”,
parameters={
“industry”: {
“type”: “string”,
“required”: True,
“default”: None,
“description”: “Your business industry or niche. “
“Be specific: ‘B2B cybersecurity SaaS’ “
“not just ‘tech.'”
},
“target_audience”: {
“type”: “string”,
“required”: True,
“default”: None,
“description”: “Detailed audience description including “
“demographics, roles, pain points, and “
“content consumption habits. Vague input “
“produces generic output.”
},
“content_goals”: {
“type”: “string”,
“required”: True,
“default”: None,
“description”: “What you want your content to achieve. “
“Examples: build email list, establish “
“thought leadership, drive demo requests, “
“educate prospects on a complex topic.”
},
“existing_content”: {
“type”: “string”,
“required”: False,
“default”: “not provided”,
“description”: “Brief description of content you already “
“produce (formats, topics, frequency). “
“Helps AI suggest ideas that complement “
“rather than duplicate your current efforts.”
},
“constraints”: {
“type”: “string”,
“required”: False,
“default”: “none specified”,
“description”: “Any limitations: team size, budget, “
“production capacity, platform restrictions, “
“compliance requirements.”
}
}
)
# ===========================================================
# PHASE 1: CONTEXT GATHERING + SCOPE FRAMING
# ===========================================================
“””
#AI->H::Note: (
Before we dive into content brainstorming, a quick note
on what this tool does: I will use content strategy patterns
to brainstorm ideas tailored to your specific industry and
audience. My suggestions are hypotheses for you to test โ€”
not data-driven trend reports. For current trend data,
pair these ideas with tools like Google Trends or your own
platform analytics.
Let’s start by understanding your context.
)
— PARAMETER COACHING —
#AI->H::Question: (
To generate the most useful content ideas, I need to
understand your business context. Please provide:
1. INDUSTRY / NICHE
What specific industry are you in?
(e.g., ‘B2B project management software for
construction firms’ โ€” the more specific, the better)
2. TARGET AUDIENCE
Who are you trying to reach? Include:
– Their role or demographic profile
– Key pain points or challenges
– How they currently consume content
(platforms, formats, frequency)
– What motivates their content engagement
3. CONTENT GOALS
What do you want your content to achieve?
(e.g., ‘generate qualified leads for our enterprise
product’ or ‘build awareness in a new market segment’)
4. EXISTING CONTENT (optional)
What content do you already produce?
(helps me suggest ideas that complement, not duplicate)
5. CONSTRAINTS (optional)
Any limitations I should know about?
(team size, budget, compliance requirements, etc.)
)
— QUALITY GATE (RULE 05) —
IF target_audience IS VAGUE:
#AI->H::Coach: (
Your audience description is fairly broad. I can work
with it, but more specific input produces substantially
better ideas. Can you narrow down:
– What specific role or job title are they?
– What is their primary challenge right now?
– Where do they spend time consuming content?
Even one additional detail will improve the output.
)
WAIT for user response or confirmation to proceed.
#AI->H::Status: (Context collected. Moving to format analysis.)
“””
# >>> WAIT GATE 1 โ€” Do not proceed until user provides context <<<
# ===========================================================
# PHASE 2: CONTENT FORMAT SUGGESTIONS
# ===========================================================
“””
#AI->H::Deliverable: (
===========================================================
CONTENT FORMAT ANALYSIS
===========================================================
Based on: {industry} | Audience: {target_audience}
Goal: {content_goals}
===========================================================
— FORMAT SUGGESTIONS —
For each format, I provide:
– What it is and how to execute it
– Why it might work for YOUR specific audience
(based on the characteristics you described)
– What to watch for when testing it
– Effort level (low / medium / high)
[Generate 4-5 distinct content format suggestions.
Each must include reasoning tied to the specific
audience characteristics provided, not generic claims.
Per RULE 03: no engagement predictions.
Per RULE 06: explain reasoning, not just suggestions.
Per RULE 09: each format must be genuinely distinct.]
===========================================================
Note: These are hypotheses based on content strategy
patterns. Validate by testing formats with your actual
audience and measuring response.
===========================================================
)
#AI->H::Question: (
Before I move to topic ideas โ€” do any of these formats
particularly interest you? Would you like me to focus
topic suggestions around specific formats, or explore
broadly?
)
“””
# >>> WAIT GATE 2 โ€” Collect format preferences before topics <<<
# ===========================================================
# PHASE 3: TOPIC BRAINSTORMING
# ===========================================================
“””
#AI->H::Deliverable: (
===========================================================
CONTENT TOPIC IDEAS
===========================================================
Based on: {industry} | Audience: {target_audience}
Goal: {content_goals}
Format preferences: {user_format_preferences_from_phase_2}
===========================================================
— TOPIC IDEAS —
For each topic, I provide:
– The topic and a specific angle or hook
– Why this might resonate with your audience
(tied to their pain points or interests)
– How to approach it (suggested format + outline sketch)
– Questions to explore within the topic
[Generate 8-10 distinct topic ideas.
Per RULE 01: frame as hypotheses.
Per RULE 02: no trend claims.
Per RULE 08: no fabricated data or examples.
Per RULE 09: enforce genuine variety across topics.
Per RULE 07: if the industry is very niche, acknowledge
that suggestions draw on broader patterns.]
— CROSS-REFERENCE SUGGESTIONS —
To validate which of these topics would perform best
for your specific audience, consider:
– Check Google Trends for search interest patterns
– Review your existing content analytics for similar
topics that performed well
– Look at competitor content to see what generates
discussion in your space
– Survey your audience directly about their interests
– Use your platform’s built-in analytics for topic
performance signals
===========================================================
These are brainstormed ideas, not data-driven rankings.
Your own audience data is the best filter for priority.
===========================================================
)
#AI->H::Question: (
Which topics interest you most? I can help you develop
any of these further, or we can move to building a
content plan around your favorites.
)
“””
# >>> WAIT GATE 3 โ€” Let user select favorites before planning <<<
# ===========================================================
# PHASE 4: CONTENT PLAN + QUICK WINS
# ===========================================================
“””
#AI->H::Deliverable: (
===========================================================
CONTENT PLAN FRAMEWORK
===========================================================
Selected topics: {user_selected_topics_from_phase_3}
Constraints: {constraints}
===========================================================
— PLANNING FRAMEWORK —
1. QUICK WINS (This Week)
[3 content ideas the user could execute quickly
with minimal resources. Tied to their constraints
and selected topics. Frame as “low-effort starting
points” not “guaranteed performers.”]
2. CONTENT CALENDAR STRUCTURE
[Suggest an organizing framework โ€” NOT specific
posting times or days.
Per RULE 04: no optimal timing claims.
Instead, suggest:
– A sustainable publishing rhythm based on their
stated constraints and team capacity
– How to sequence topics for variety
– How to mix formats across the calendar
– When to revisit and adjust based on results]
3. TOPIC DEVELOPMENT NOTES
[For each selected topic, provide:
– 3-4 subtopics or angles to explore over time
– How to repurpose across formats
– What audience signals to watch for
(comments, shares, questions) that indicate
resonance]
4. VALIDATION CHECKLIST
Before committing to any content piece, consider:
– Does this align with your stated goal ({content_goals})?
– Do you have the resources to produce it well?
– Can you measure its impact?
– Does it offer something your audience cannot
easily find elsewhere?
===========================================================
This plan is a starting framework. Adjust based on
what your audience data tells you after the first
few pieces are published.
===========================================================
)
#AI->H::Note: (
Your content brainstorming session is complete. You have:
– Format suggestions tailored to your audience
– Topic ideas with reasoning and angles
– A planning framework with quick wins
For deeper research on any specific topic, consider using
Deep Research to gather current data, competitor analysis,
or audience insights to validate and refine these ideas.
For content gap analysis against competitors, see
RCP-063 (Content Gap Analyzer).
For optimizing existing content performance, see
RCP-026 (Content Performance Optimizer).
)
“””
# >>> END OF INTERACTIVE FLOW <<<
# ===========================================================
# EXAMPLE 1: SUSTAINABLE FASHION BRAND
# ===========================================================
EXAMPLE_1 = {
“scenario”: “Eco-conscious clothing retailer”,
“parameters”: {
“industry”: “sustainable fashion โ€” direct-to-consumer “
“clothing brand using organic and recycled “
“materials, price range $80-300 per item”,
“target_audience”: “environmentally conscious millennials “
“aged 28-40 who prioritize ethical “
“consumption, are willing to pay premium “
“prices for quality sustainable clothing, “
“and consume content primarily via “
“Instagram and sustainability blogs”,
“content_goals”: “build brand awareness and educate “
“prospects on why sustainable fashion “
“costs more (overcoming price objection)”,
“existing_content”: “weekly Instagram posts, monthly “
“blog article, occasional email “
“newsletter”,
“constraints”: “2-person marketing team, $500/month “
“content budget, no video production “
“capability yet”
}
}
# ===========================================================
# EXAMPLE 2: B2B SOFTWARE COMPANY
# ===========================================================
EXAMPLE_2 = {
“scenario”: “Project management tool provider”,
“parameters”: {
“industry”: “B2B productivity software โ€” project “
“management tool for remote and hybrid “
“teams, $15-45/user/month SaaS model”,
“target_audience”: “operations managers and team leads “
“at companies with 50-500 employees “
“who struggle with remote team “
“coordination, currently using a mix “
“of spreadsheets and basic tools, “
“consume content via LinkedIn and “
“industry webinars”,
“content_goals”: “generate qualified demo requests from “
“mid-market companies currently using “
“manual project tracking methods”,
“existing_content”: “bi-weekly blog, monthly webinar, “
“3 case studies from last year”,
“constraints”: “1 content marketer, strong subject “
“matter experts available for interviews, “
“compliance review required for all “
“published content”
}
}
# ===========================================================
# USAGE NOTES
# ===========================================================
USAGE_NOTES = {
“best_for”: [
“Quarterly content planning brainstorms”,
“Launching content strategy for new markets”,
“Refreshing stale editorial calendars”,
“Exploring new content format opportunities”,
“Generating ideas when you feel stuck creatively”
],
“prerequisites”: [
“Understanding of your target audience (the more “
“specific, the better the output)”,
“Defined content marketing goals”,
“Awareness of your production constraints”
],
“pairs_well_with”: [
“RCP-063 (Content Gap Analyzer) โ€” for competitive “
“content analysis”,
“RCP-026 (Content Performance Optimizer) โ€” for “
“improving existing content”,
“Deep Research โ€” for validating topic ideas with “
“current market data”
],
“limitations”: [
“Cannot access real-time trend data or analytics”,
“Suggestions are pattern-based hypotheses, not “
“data-driven recommendations”,
“Output quality depends heavily on input specificity”,
“Cannot predict audience engagement or content “
“performance”
],
“time_estimate”: “20-40 minutes (interactive session)”
}
# ===========================================================
# END RECIPE-ID: RCP-000-000-062-CONTENT-IDEA-GENERATOR
# ===========================================================

{
“schema”: “CRAFT_AI_TO_AI_COMMUNICATION”,
“schema_version”: “1.1”,
“schema_profile”: “standalone-recipe”,
“recipe_id”: “RCP-000-000-062”,
“recipe_name”: “Content Idea Generator”,
“version”: “v2.00a-R”,
“original_version”: “v2.00a”,
“cookbook”: “Standalone (No Cookbook)”,
“category”: “Content Strategy”,
“subcategory”: “Content Ideation”,
“difficulty”: “Beginner”,
“status”: “Official”,
“craft_flavors”: “CRAFT Cowork”,
“recommended_personas”: “Not specified”,

“summary”: {
“what_it_does”: “Structured content brainstorming session. Guides users through 4 interactive phases โ€” context gathering, format analysis, topic ideation, and content planning โ€” using AI pattern recognition applied to the user’s specific industry and audience. Generates hypotheses to test, not data-driven recommendations.”,
“what_it_is_not”: “Not a trend monitoring tool, audience analytics platform, competitor intelligence system, or engagement prediction engine. Cannot access real-time data. All suggestions are pattern-based hypotheses for the user to validate against their own data.”,
“key_design_decisions”: [
“Hypothesis-driven not data-driven โ€” all output framed as hypotheses to test, never as proven strategies or trend reports. LL-046 hypothesis framing applied throughout.”,
“Quality over quantity โ€” removed topic_count/format_count parameters in favor of behavioral rules that enforce output quality and differentiation (RULE_09).”,
“No Deep Research integration โ€” core value is creative brainstorming, not research. Users can pair with DR independently for current trend validation.”,
“Parameter coaching as value โ€” RULE_05 quality gate coaches users toward audience specificity before generating ideas, because vague input produces generic output.”
],
“revision_notes”: “v2.00a โ†’ v2.00a-R (QA revision, P051f H018). 12 gaps identified (3 CRITICAL, 4 HIGH). Added 10 behavioral rules (was zero), 4-phase interactive delivery with 3 WAIT gates (was dump-all), stripped false trend/engagement/timing claims, reframed from data-driven intelligence to hypothesis-driven brainstorming partner. Code tripled from ~140 to ~420 lines.”
},

“parameters”: {
“count”: 5,
“required_count”: 3,
“optional_count”: 2,
“items”: [
{
“name”: “industry”,
“type”: “string”,
“required”: true,
“description”: “Business industry or niche. Specificity matters: ‘B2B cybersecurity SaaS’ not just ‘tech.'”
},
{
“name”: “target_audience”,
“type”: “string”,
“required”: true,
“description”: “Detailed audience description including demographics, roles, pain points, and content consumption habits. Vague input produces generic output.”
},
{
“name”: “content_goals”,
“type”: “string”,
“required”: true,
“description”: “What the content should achieve. Examples: build email list, establish thought leadership, drive demo requests, educate prospects.”
},
{
“name”: “existing_content”,
“type”: “string”,
“required”: false,
“default”: “not provided”,
“description”: “Brief description of content already produced (formats, topics, frequency). Helps AI suggest complementary rather than duplicate ideas.”
},
{
“name”: “constraints”,
“type”: “string”,
“required”: false,
“default”: “none specified”,
“description”: “Any limitations: team size, budget, production capacity, platform restrictions, compliance requirements.”
}
]
},

“behavioral_rules”: {
“count”: 10,
“items”: [
{“id”: “RULE-01”, “name”: “Hypothesis Framing Throughout”, “summary”: “Frame ALL content suggestions as hypotheses to test, not proven strategies. Use ‘might resonate,’ ‘consider testing,’ ‘often respond to’ โ€” never ‘will perform well’ or ‘guarantees engagement.'”},
{“id”: “RULE-02”, “name”: “No False Trend Claims”, “summary”: “Never claim to know what is currently trending, viral, or gaining momentum. No access to real-time trend data. Suggest Google Trends or social listening tools for current data.”},
{“id”: “RULE-03”, “name”: “No Engagement Predictions”, “summary”: “Never predict specific engagement levels, click-through rates, or performance metrics. Explain WHY a format might work based on audience characteristics instead.”},
{“id”: “RULE-04”, “name”: “No Optimal Timing Claims”, “summary”: “Never claim to know best posting times, days, or frequency. Offer general principles and recommend the user check their own platform analytics.”},
{“id”: “RULE-05”, “name”: “Parameter Quality Gate”, “summary”: “If target_audience is vague, pause and coach toward specificity before generating ideas. Ask about demographics, psychographics, pain points, content consumption habits.”},
{“id”: “RULE-06”, “name”: “Explain Reasoning, Not Just Suggestions”, “summary”: “For every suggestion, explain WHY it might work for this specific audience. The reasoning is more valuable than the suggestion itself.”},
{“id”: “RULE-07”, “name”: “Acknowledge What You Do Not Know”, “summary”: “For niche industries where pattern recognition may be thin, say so. Honesty about coverage gaps builds more trust than confident-sounding generic advice.”},
{“id”: “RULE-08”, “name”: “No Fabricated Examples or Data”, “summary”: “Do not invent case studies, statistics, or brand examples. Frame patterns as general knowledge, not manufactured authority.”},
{“id”: “RULE-09”, “name”: “Differentiation Enforcement”, “summary”: “Each content idea must be genuinely distinct. No 5 variations of the same idea in different packaging. Push for variety across topics, angles, formats, and audience needs.”},
{“id”: “RULE-10”, “name”: “Scope Honesty at Opening”, “summary”: “Briefly clarify at session start: structured brainstorming partner applying content strategy patterns to your context โ€” not a trend monitoring tool or analytics platform. One sentence is enough.”}
]
},

“delivery_structure”: {
“phases”: 4,
“wait_gates”: 3,
“flow”: [
“Phase 1: Context Gathering + Scope Framing โ€” parameter coaching, RULE_05 quality gate for audience specificity, scope honesty note”,
“WAIT GATE 1 โ€” collect context before generating”,
“Phase 2: Content Format Suggestions โ€” 4-5 distinct formats with reasoning tied to audience characteristics, effort levels”,
“WAIT GATE 2 โ€” collect format preferences before topics”,
“Phase 3: Topic Brainstorming โ€” 8-10 distinct topic ideas with angles, reasoning, cross-reference suggestions for validation”,
“WAIT GATE 3 โ€” let user select favorites before planning”,
“Phase 4: Content Plan + Quick Wins โ€” quick wins (this week), calendar structure, topic development notes, validation checklist”
],
“output”: “4-deliverable interactive session: format analysis, topic ideas, content plan framework with quick wins, and validation checklist. Each deliverable builds on user selections from the prior phase.”
},

“relationships”: {
“family”: “Content Strategy”,
“series”: “Content Strategy (062-063 + 026)”,
“series_position”: “1 of 3”,
“companion_recipes”: [
{“id”: “RCP-000-000-063”, “name”: “Content Gap Analyzer”, “relationship”: “Competitive content analysis โ€” complements brainstorming with gap identification”},
{“id”: “RCP-000-000-026”, “name”: “Content Performance Optimizer”, “relationship”: “Existing content optimization โ€” works on content after it’s published”}
],
“related_analytical”: []
},

“lessons_learned”: [
{
“id”: “LL-CRPW-062-001”,
“category”: “PATTERN”,
“lesson”: “CRAFT_FLAVORS stale value ‘Foundations, Express, Studio’ variant โ€” 6th consecutive encounter in the pipeline (H077-H082). This instance uses the explicit three-name form rather than the compact ‘All Flavors’ shorthand seen in runs 36-40. Semantically identical stale state, same mechanical UPDATE to ‘CRAFT Cowork’. Confirms the stale value appears in at least two surface forms across the recipe catalog.”,
“source”: “CWK-ADM-079 F-01, pipeline run 41”
},
{
“id”: “LL-CRPW-062-002”,
“category”: “OBSERVATION”,
“lesson”: “First recipe in the pipeline with an accompanying QA Audit Report as a 4th source file (beyond the standard WPRM + D3 + D4 three-file pattern). The audit report provides prior-QA context but does not change the CRPW pipeline evaluation โ€” the pipeline evaluates the current recipe state, not the revision history. Audit report served as supplementary context only.”,
“source”: “CWK-ADM-078 intake, pipeline run 41”
}
],

“pipeline_metadata”: {
“pipeline_run”: 41,
“recipe_number”: 40,
“standalone_number”: 36,
“handoff”: “H082”,
“date”: “2026-04-26”,
“project”: “CFT-PROJ-CP-067”
}
}

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