End-of-Article CTA Designer

Questions: Ask the user through the environment's question tool — never as plain-text prose. One question at a time, 2–4 tappable options, wait for the answer. If the environment has no question tool, ask in prose with the same options, one at a time.

End-of-Article CTA Designer

Designing an end-of-article CTA is a function of three inputs: the objective (what action), the audience (who reads it, in what relationship to the author), and the context (independent writing, newsletter, brand publication). Get those three right and the copy + form follow almost mechanically. Skip them and you get the universal failure mode: a generic "Subscribe for more" or "Learn More" that converts at the noise floor.

This skill runs a tight interview to capture those three inputs, then prescribes a CTA: copy (what it says), form (how it looks and sits on the page), mechanism (whether to use urgency, scarcity, curiosity, reciprocity, social proof, or none), an A/B test plan, and an accessibility check.

Workflow

Run the four steps below in order. Do not skip the interview. The user may have given partial context already; pull what's available from the conversation, then ask only for the missing pieces.

Step 1 — Interview

Ask one question at a time. Do not stack questions in prose. Each question must have 2-4 tappable options. Fall back to free text only if the answer genuinely cannot be enumerated.

Ask these in order, skipping any already answered:

Q1. Article context. Options: Personal / independent blog or essay · Newsletter / paid publication (Substack, beehiiv, Ghost, etc.) · Brand / company / content-marketing blog · Other (free text)

Q2. Primary objective. (Pick the one outcome you most want from a reader who finishes the article. If they say "all of them," push back: multiple objectives is the #1 cause of CTA failure.)

Options:

• Newsletter / email subscription
• Social follow / personal branding
• Lead generation (download / gated asset)
• Product or service signup / free trial
• Demo or sales call booking
• Direct purchase
• Community join (Discord / Slack / forum)
• Engagement (reply / comment / share / restack)
• Reader support (paid subscription / tip / sponsorship)
• Try-it / direct action (use the code, run the tool, fork the template, open the calculator)
• Other (free text)

If the user lists more than one, ask which is primary. You can offer 1-2 secondaries later, but the primary must be singular.

Q3. Audience and relationship. Options: First-time visitor (organic search / social) · Returning reader, not subscribed · Existing subscriber / customer · Mixed / unknown

Q4. Funnel stage. (Where is the reader mentally?) Options: TOFU: discovery, learning, no buying intent yet · MOFU: evaluating options, comparing · BOFU: ready to act, just needs a nudge · Not applicable (no buying funnel — e.g., personal blog, journalism, hobby content)

Q5. Mechanism preference. (Only ask if a mechanism could legitimately help. See references/mechanisms.md. For sophisticated, skeptical, or repeat-reader audiences, default to "None / value-only" without asking.) Options: None: value statement only · Curiosity gap ("Want to know more?") · Reciprocity (free asset first) · Discount / offer · Urgency (real deadline) · Scarcity / FOMO (limited spots) · Social proof (count / testimonial)

Capture any free-text constraints the user volunteers (length limit, brand voice, no popups, multi-language, etc.). Note them.

Step 2 — Diagnose

Map the inputs to a CTA archetype. The decision logic:

context = INDEPENDENT / PERSONAL
├── objective = newsletter / email      → Archetype A: Author-signature subscribe
├── objective = try-it / direct action  → Archetype B: Inline action + source link
├── objective = reader support / tip    → Archetype C: Reader-supported funding link
├── objective = community               → Archetype D: Proof-counted community invite
├── objective = social follow           → Archetype A (variant: lead with social links)
├── objective = engagement              → Archetype E: Specific reply prompt
└── objective = product / demo          → ⚠️ FLAG. Only valid on personal/professional
                                          blog where the author IS the product
                                          (consultants, coaches, solo founders, indie devs).
                                          Frame as "if you hit this, here's how I help"
                                          — never "Book a Demo" verbatim.

context = NEWSLETTER PUBLICATION
├── objective = growth / subs           → Archetype F: Share/restack + native widget
├── objective = engagement              → Archetype E: Specific reply prompt
├── objective = paid conversion         → Archetype G: Value-gap tease
├── objective = monetization / sponsor  → Archetype H: Inline sponsor block (not bottom)
├── objective = community               → Archetype D
└── objective = direct purchase         → Archetype K (rare on newsletters; use BOFU only)

context = BRAND / CONTENT MARKETING
├── stage = TOFU                        → Archetype I: Transitional asset (lead magnet)
├── stage = MOFU                        → Archetype J: Direct + Transitional pair
├── stage = BOFU                        → Archetype K: Direct CTA + risk reversal
├── objective = community               → Archetype D
└── objective = engagement              → Archetype E (rarely the right call here)

Read references/taxonomy.md for the full archetype catalog with copy templates, form specs, when each works, and verbatim examples from named publications.

Step 3 — Compose the recommendation

Output the recommendation in this exact structure. Do not deviate. Do not add filler.

## Recommended CTA

**Archetype:** [letter + name from decision tree] **Why this fits:** [1-2 sentences naming the input combination]

### Content (copy)

**Headline / value line:**

> [exact text]

**Body / proof line (1-2 lines):**

> [exact text]

**Button copy:**

> [exact text]

**Risk reversal / subtext (if applicable):**

> [exact text, or "Omit: would feel forced for this audience"]

### Form (structure)

- **Placement:** [end-only / end + sticky / end + mid-article repeat]
- **Visual weight:** [low / medium / high, with justification]
- **Layout:** [single button / button + text link / native widget cluster / one-line signature]
- **Proof to co-locate:** [subscriber count / star count / testimonial / named recommenders / logo wall / none]

### Mechanism

[Named mechanism + 1 sentence on why it is appropriate, OR "None: value statement carries it. Mechanisms would erode trust for this audience."]

### A/B test plan

- **First test:** [single variable, e.g., button copy A vs. B]
- **Why this one first:** [1 sentence]
- **Sample size needed:** [rough estimate based on baseline traffic, or "skip A/B for now — traffic too low" with the alternative recommendation]
- **Next 2 tests to queue:** [in priority order]

### Accessibility check

- **Color contrast:** [target ratio + concrete pairing if colors known]
- **Touch target:** [size requirement]
- **Semantic markup:** [<button> vs. <a> vs. form]
- **ARIA:** [only if non-obvious]
- **Keyboard / focus:** [requirement]
- **Color-independence:** [non-color affordance]

After printing the recommendation, list 2-3 anti-patterns the user is at risk of falling into given their inputs, directly, as a contrarian check. Pull these from references/anti-patterns.md.

If the user is writing in a non-English language, translate the content section into that language but keep the structure (headings, labels) in English. Honor formality cues (e.g., tu vs. vous in French, du vs. Sie in German) based on prior conversation context, and flag the choice explicitly.

Step 4 — Offer next moves

Suggest 2-3 follow-up directions:

1. Steelman the opposite. Offer to design the CTA you would recommend against — e.g., the hard-sell version on a TOFU post — so the user can see why it fails.
2. Variant for a different audience or platform. If the article will be cross-posted (own site + Medium + LinkedIn + a syndication network), offer to rewrite per platform.
3. End-to-end review. Offer to audit the rest of the article for CTA-supporting signals: author bio, related-post links, in-line proof.