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.
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill linkedin-bid-strategy-selectorgit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote 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.
[](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/linkedin-bid-strategy-selector)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/linkedin-bid-strategy-selector"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/linkedin-bid-strategy-selector/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.
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/linkedin-bid-strategy-selector"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/linkedin-bid-strategy-selector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.04939 |
| Opus 5.5 | $0.00043 | $0.01976 |
| Sonnet 5.5 | $0.00022 | $0.00988 |
| Haiku 4.5 | $0.00011 | $0.00494 |
Grade A, and why
linkedin-bid-strategy-selector 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 695 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Bid Strategy Selector
Advisor for selecting the optimal LinkedIn Ads bid strategy based on goals, budget, and account situation.
Quick Selection Guide
WHAT IS YOUR PRIMARY GOAL?
|
+---> Maximum volume & reach
| +---> MAXIMUM DELIVERY
| (Let LinkedIn optimize)
|
+---> Keep CPL/CPA under control
| +---> COST CAP
| (Target cost with flexibility)
|
+---> Full control over costs
+---> MANUAL BIDDING
(Fixed max bid per result)
Bid Strategy Overview
LINKEDIN BID STRATEGIES COMPARISON
====================================
Strategy | Control | Risk | Best For | Min. Budget
-----------------+---------+------+---------------------+------------
Maximum Delivery | None | Low | Beginners, volume | $25/day
Cost Cap | Target | Med | CPL constraints | $50/day
Manual Bidding | Exact | High | Competitive auctions| $100/day
OBJECTIVE COMPATIBILITY:
| Max Del | Cost Cap | Manual
----------------+---------+----------+--------
Brand Awareness | Y | - | Y
Website Visits | Y | Y | Y
Engagement | Y | Y | Y
Video Views | Y | Y | Y
Lead Generation | Y | Y | Y
Conversions | Y | Y | Y
Job Applicants | Y | - | Y
Maximum Delivery (Automated Bidding)
How It Works
LinkedIn automatically optimizes your bids to get as many results as possible within your budget. No control over CPC/CPL.
When to Use
- New accounts with little benchmark data
- Brand awareness campaigns
- Fast learning phase completion
- Uncertain about realistic bid ranges
- Fully spending the budget is the priority
When NOT to Use
- Strict CPL requirements
- Competitive niches where costs can explode
- When you already have benchmark data
Setup
Campaign Settings:
+-- Objective: [Based on goal]
+-- Bid type: Maximum Delivery
+-- Daily budget: Minimum $25/day
+-- Schedule: Continuous or custom
+-- Pacing: Standard (recommended)
Expected Behavior:
+-- Day 1-3: Learning, CPC/CPL fluctuates
+-- Day 4-7: Stabilization
+-- Week 2+: Consistent delivery
+-- CPL: Typically 10-30% above market benchmark
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.
- 1mo ago First seen · 695 lines · 108 tokens per session scan A 4766b2adfc43
linkedin-bid-strategy-selector is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 29d ago), licensed MIT. It adds 108 tokens to every session and 4,939 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-11.
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