social-ad

social-ad is a skill for Claude Code from inklate/social-skills. It costs 163 tokens per session (1,837 once invoked), scanned A, original, MIT.

A writing helper for creating several paid-ad versions for Facebook, Instagram, LinkedIn, X, and TikTok.

In plain words
What is it for?
Use it to create ad angles, text variations, calls to action, and short creative briefs for a product or promotion.
Why use it?
It removes the need to adapt one offer manually for every platform and ad format. It also helps keep the ad aligned with the landing page and brand rules.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the social-skills plugin — 14 skills shipped together

Good fit Use it to create ad angles, text variations, calls to action, and short creative briefs for a product or promotion.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/inklate/social-skills/social-ad
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add inklate/social-skills --skill social-ad
Clone the repo
git clone --depth 1 https://github.com/inklate/social-skills

Made for: Claude Code.

Or install social-skills, the plugin that ships this one along with the rest of its 14 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for social-ad

README.md
[![agentmods](https://agentmods.dev/badge/skills/inklate/social-skills/social-ad/github.svg)](https://agentmods.dev/skills/inklate/social-skills/social-ad)
Your own site
<a href="https://agentmods.dev/skills/inklate/social-skills/social-ad"><img src="https://agentmods.dev/badge/skills/inklate/social-skills/social-ad/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for social-ad

Your own site · 80×15
<a href="https://agentmods.dev/skills/inklate/social-skills/social-ad"><img src="https://agentmods.dev/badge/skills/inklate/social-skills/social-ad.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 163 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,837 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00163 $0.01837
Opus 5 $0.00081 $0.00919
Sonnet 5 $0.00033 $0.00367
Haiku 4.5 $0.00016 $0.00184

Measured 12d ago against content hash f08097b7eab3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

social-ad scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/social-ad/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Produce placement-ready ad copy variant sets — an angle matrix crossed with every copy part each platform needs, plus a one-line creative brief per variant.

Context

Read social-context.md at the project root (also check .agents/social-context.md) for brand voice, audience, product positioning, and banned phrases (proof points come from the offer and landing page in step 1). If it's missing, offer to run the social-context skill first, but don't block — ask 2–3 quick inline questions and proceed:

  • What's the offer, the price, and the single strongest proof point?
  • Who's the audience, in one sentence?
  • Any voice rules — words you never use, no exclamation marks, no "unlock"?

Workflow

  1. Ingest the offer. Get the landing page URL or offer description and read it closely. Extract four things: the concrete promise, the price/commitment, the strongest proof point (a number, a named customer, a guarantee), and where the CTA actually sends people. If the landing page's promise and the user's framing disagree, flag it before drafting — ad-to-page mismatch kills conversion and quality scores, and no copy fixes it.
  2. Ask audience temperature. Cold, warm (engaged but never bought), or retargeting (visited or abandoned)? This is not optional — the copy is structurally different:
    • Cold: name the problem before the product; the reader doesn't know they're shopping yet.
    • Warm: lead with the offer and the proof; they know the category, sell the difference.
    • Retargeting: reference the visit ("Still thinking it over?") and lean on objection-flips and risk-reversal (trial, guarantee, cancel-anytime). If the user wants multiple temperatures, treat each as its own variant set — don't average them into mush.
  3. Confirm placements. Which of Meta (Facebook/Instagram feed), LinkedIn (sponsored content), X, TikTok? Only draft what's requested; each placement is real work, not a find-and-replace.
  4. Build the angle matrix. For this specific offer, write one crisp sentence per angle before drafting anything:
    • Pain — the ongoing cost of the status quo, in the audience's own units (hours, dollars, missed deals).
    • Aspiration — the after-state, concrete enough to picture, not "transform your workflow".
    • Social proof — a real number or a real name from context or the landing page. Never invented; if none exists, say so and drop the angle.
    • Objection-flip — name the #1 objection out loud and answer it head-on ("Yes, another tool. This one deletes three.").
    • Honest urgency — a real deadline or capacity limit only. If none exists, replace this angle with a second pain or proof variant. Never fake it.
  5. Draft per placement. For each placement, write 3–5 variants, each from a different angle, each containing every copy part the platform uses (see Quality bar). Front-load ruthlessly: the visible-truncation point, not the hard limit, is your real budget for the first idea — a hook that dies at "…more" was never a hook.
  6. Write the creative brief line. One line per variant telling the designer exactly what the visual is: subject, composition, text overlay if any. Concrete ("split screen: messy spreadsheet vs. clean dashboard, overlay '4 hours → 20 minutes'"), never mood-board vapor ("something clean and modern"). The brief should visualize the angle, not just the product.
  7. Compliance pass. Check every variant against the rules that get ads rejected or accounts flagged:
    • No second-person call-outs of sensitive attributes — health conditions, financial hardship, religion, ethnicity, age. "Struggling with debt?" fails Meta review; "Debt doesn't have to be permanent" passes. Rewrite from "you are X" to "X exists / X is solvable".
    • No fake scarcity, invented countdowns, or "only 3 left" that isn't true.
    • No unverifiable superlatives ("the #1 tool") without a citable source.
    • Every claim in the ad must appear on, or be supported by, the landing page.
  8. Pick the CTA button per variant. The button is part of the copy, chosen from each platform's actual vocabulary (see Quality bar). Default mapping: "Learn More" for cold, "Sign Up" / "Get Offer" for warm and retargeting, "Shop Now" only for direct purchase, "Download" / "Request Demo" when that's literally the next step.
  9. Label everything. Tag each variant [placement / angle / temperature] so when performance data comes back, the user can map winners and losers to the matrix and commission the next round intelligently.
  10. Verify against the Quality bar. Before handing off, count every copy part of every variant against its placement's real limits in the Quality bar — count, don't eyeball — and check every variant against the Additional bars. Fix any overflow or miss; a variant that overflows its placement is not placement-ready.

Read the full file on GitHub · 93 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 93 lines · 163 tokens per session scan A f08097b7eab3

Subscribe to this mod's changes

social-ad is a skill published in the GitHub repository inklate/social-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 163 tokens to every session and 1,837 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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