instagram-performance-marketing

instagram-performance-marketing is a skill for Claude Code from uppifyagency/bettercallclaudegrowth. It costs 84 tokens per session (2,803 once invoked), scanned A, original, MIT.

A reference guide to performance advertising on Instagram and Facebook through Meta Ads Manager. It explains campaigns that aim to produce conversions, such as purchases or sign-ups, using audiences, creative, retargeting, and location choices.

In plain words
What is it for?
Use it to study campaign objectives, audience and lookalike targeting, geographic targeting, creative, accelerated spending, retargeting, CPM, and CPA.
Why use it?
It organizes the factors that affect advertising costs and results, including cost per thousand impressions and cost per acquisition. It is intended to make campaign decisions more systematic.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Part of the bettercallclaudegrowth plugin — 9 skills, 11 commands, 3 agents shipped together

Good fit Use it to study campaign objectives, audience and lookalike targeting, geographic targeting, creative, accelerated spending, retargeting, CPM, and CPA.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing
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 uppifyagency/bettercallclaudegrowth --skill instagram-performance-marketing
Clone the repo
git clone --depth 1 https://github.com/uppifyagency/bettercallclaudegrowth

Made for: Claude Code.

Or install bettercallclaudegrowth, the plugin that ships this one along with the rest of its 9 skills, 11 commands, 3 agents.

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 instagram-performance-marketing

README.md
[![agentmods](https://agentmods.dev/badge/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing/github.svg)](https://agentmods.dev/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing)
Your own site
<a href="https://agentmods.dev/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing"><img src="https://agentmods.dev/badge/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing/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 instagram-performance-marketing

Your own site · 80×15
<a href="https://agentmods.dev/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing"><img src="https://agentmods.dev/badge/skills/uppifyagency/bettercallclaudegrowth/instagram-performance-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,803 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 $0.00084 $0.02803
Opus 5 $0.00042 $0.01401
Sonnet 5 $0.00017 $0.00561
Haiku 4.5 $0.00008 $0.00280

Measured 11d ago against content hash e378ce3d42c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

instagram-performance-marketing 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 11d 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.

bettercallclaudegrowth/skills/instagram-performance-marketing/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Instagram Performance Marketing — The Programmatic Guide to Conversion Marketing

Author: Robert Thomas (Leadedly Publishing, 2025) | Pages: ~127 | Chapters: 17 | Generated: 2026-06-08

Despite the title, the book is a hands-on playbook for Meta Ads Manager (Facebook + Instagram) conversion campaigns. Every framework optimizes one master equation: lower CPM → lower CPA.

How to Use This Skill

  • Without arguments — load the core frameworks below for reference.
  • With a topic — ask about lookalike audiences, campaign objectives, CPM, accelerated ad spend, etc.; I find and read the relevant chapter.
  • With a chapter — ask for ch10; I load that specific chapter file.
  • Browse — ask "what chapters do you have?" to see the full index.

When you ask about a topic not in Core Frameworks below, I read the relevant chapter file before answering.


Core Frameworks & Mental Models

The master thesis — "The lower your CPM, the lower your CPA." (Ch17) Cost Per Acquisition is downstream of Cost per 1,000 Impressions. You almost never optimize CPA directly; you attack CPM (via geo + broad audiences + high-CTR creative + algorithm training), and CPA falls with it. This is the lens for every other decision.

The Seven Pillars of Performance Marketing (Ch3) — the diagnostic checklist; audit/launch any campaign in this order:

  1. Campaign Objective Selection — the single highest-leverage choice.
  2. Audience Targeting — seed with first-party data, expand with lookalikes.
  3. GEO Targeting — widen geography to crush CPM.
  4. Ad Creative — video for CTR + engagement signals.
  5. Ad Settings — quiet cost levers (placements, etc.).
  6. Landing Page Optimization — convert the traffic you paid for.
  7. Post-Ad Engagement — automate instant follow-up.

Objective = an instruction to Meta's algorithm, not a label. (Ch4) The objective tells Meta which behavioral cohort to spend on. Match it to the exact action you want: Sales/Conversions for purchases, Engagement→Lead Forms for leads, App Installs for downloads. Picking cheaper proxy objectives (e.g. Traffic) gets you visitors who never convert — same spend, worse result. CPM cost ladder: Awareness/Reach (lowest) < Engagement/Traffic/Lead Gen < Conversions (highest) — but a conversion objective with broad audience + wide GEO nets lower CPM than a conversion objective restricted to the US.

Read the full file on GitHub · 125 lines

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. 11d ago First seen · 125 lines · 84 tokens per session scan A e378ce3d42c9

Subscribe to this mod's changes

instagram-performance-marketing is a skill published in the GitHub repository uppifyagency/bettercallclaudegrowth (5 stars, last pushed 3mo ago), licensed MIT. It adds 84 tokens to every session and 2,803 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

linkedin-employee-advocacy

Stand up and run a LinkedIn employee advocacy program for a marketing or sales team. Covers 14-day launch playbook, brand-guideline governance, per-post time budget, cadence benchmarks, and team ROI (reach, engagement, pipeline). Triggers on "employee advocacy", "get the team posting", "scale LinkedIn across team"…

sergebulaev/linkedin-skills · 82 tokens

docs-drift

Documentation-drift audit for this plugin monorepo. Audit either each scoped plugin's unreleased changelog claims or its latest shipped release from the previous reachable plugin-name--v tag, then verify that plugin READMEs, docs, CLAUDE.md or AGENTS.md files, and root documentation tell the truth for the matching…

gtapps/claude-code-hermit · 170 tokens

cco-tools

Show what tools actually cost in tokens — learned per-tool averages from observed results, replacing the hardcoded MCP/Agent guesses.

egorfedorov/claude-context-optimizer · 27 tokens

test-run

Run plugin test suites in this monorepo and report a concise pass/fail summary. Optional plugin slug arg; without arg, runs all plugins under plugins/.

gtapps/claude-code-hermit · 35 tokens

github-pr-creation

Creates GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing…

fvadicamo/dev-agent-skills · 75 tokens

design-system-reference

Style guides and implementation rules for frontend design. Works with design-discovery agent which handles context gathering and VS-based style recommendations. Contains detailed style guides, anti-patterns, and implementation checklists.

wigtn/wigtn-plugins · 43 tokens