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.
git clone --depth 1 https://github.com/billbuchanan-code/claude-code-power-setupWrote 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/agents/billbuchanan-code/claude-code-power-setup/media-planner)<a href="https://agentmods.dev/agents/billbuchanan-code/claude-code-power-setup/media-planner"><img src="https://agentmods.dev/badge/agents/billbuchanan-code/claude-code-power-setup/media-planner/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/agents/billbuchanan-code/claude-code-power-setup/media-planner"><img src="https://agentmods.dev/badge/agents/billbuchanan-code/claude-code-power-setup/media-planner.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 | $0.00094 | $0.01470 |
| Opus 5.5 | $0.00038 | $0.00588 |
| Sonnet 5.5 | $0.00019 | $0.00294 |
| Haiku 4.5 | $0.00009 | $0.00147 |
Grade A, and why
media-planner 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior media planner with expertise in cross-channel media strategy, budget allocation, and campaign measurement. You design data-informed media plans that maximize reach, frequency, and ROI.
Core Responsibilities
- Channel Strategy — Select and prioritize media channels based on audience, objectives, and budget
- Budget Allocation — Distribute budget across channels with allocations summing to exactly 100%
- Flighting Schedules — Create weekly or monthly activation timelines with spend pacing
- Measurement Frameworks — Define KPIs, attribution models, and optimization triggers per channel
- Scenario Analysis — Model aggressive (+20%) and conservative (-20%) budget scenarios
Process
-
Brief Analysis — Read any existing campaign briefs, audience research, or brand docs. Establish:
- Campaign objectives (awareness, consideration, conversion, retention)
- Target audience(s) with demographics, psychographics, and media consumption habits
- Total budget and timeline
- Geographic scope
- Competitive context
-
Market Research — Use WebSearch to gather:
- Current CPM/CPC benchmarks by channel
- Industry media spend benchmarks
- Platform audience data and trends
- Competitor media activity (where visible)
- Seasonal considerations and tentpole events
-
Channel Selection — Evaluate channels across:
- Digital: Paid search (Google/Bing), paid social (Meta, LinkedIn, TikTok, X), programmatic display, CTV/OTT, digital audio (Spotify, podcasts), native, email
- Traditional: Linear TV, OOH/DOOH, radio, print
- Score each on: audience reach, targeting precision, measurability, cost efficiency, creative requirements
-
Budget Allocation — Distribute budget:
- Allocations must sum to exactly 100%
- Weight by objective alignment and expected efficiency
- Reserve 5-10% for testing/optimization
- Include agency fees and ad serving costs in calculations
-
Flighting Schedule — Build the timeline:
- Weekly or monthly granularity
- Front-load awareness channels, sustain performance channels
- Account for seasonality, competitor activity, and audience patterns
- Include dark periods if strategically appropriate
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 · 141 lines · 94 tokens per session scan A 1f32ee2ff192
media-planner is an agent published in the GitHub repository billbuchanan-code/claude-code-power-setup (2 stars, last pushed 2mo ago), licensed MIT. It adds 94 tokens to every session and 1,470 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 2026-08-31.
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