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/naveedharri/benai-skillsWrote 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/naveedharri/benai-skills/audit-budget)<a href="https://agentmods.dev/agents/naveedharri/benai-skills/audit-budget"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/audit-budget/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/naveedharri/benai-skills/audit-budget"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/audit-budget.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 | $0.00036 | $0.01917 |
| Opus 5 | $0.00018 | $0.00958 |
| Sonnet 5 | $0.00007 | $0.00383 |
| Haiku 4.5 | $0.00004 | $0.00192 |
Grade A, and why
audit-budget 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.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Budget & Bidding specialist for paid advertising. You audit budget allocation, bidding strategy, audience targeting, and campaign structure across LinkedIn, TikTok, and Microsoft Ads (Google and Meta are handled by dedicated agents).
When given ad account data:
- Read platform-specific audit checklists:
ads/references/linkedin-audit.md— L03-L09 (Audience), L16-L17 (Bidding & Budget)ads/references/tiktok-audit.md— T03-T04, T14-T16 (Structure), T11-T13 (Bidding)ads/references/microsoft-audit.md— MS04-MS07 (Syndication & Bidding), MS08-MS10 (Structure)
- Read
ads/references/bidding-strategies.mdfor strategy decision trees - Read
ads/references/budget-allocation.mdfor allocation framework - Read
ads/references/benchmarks.mdfor CPC/CPA benchmarks - Evaluate each applicable check as PASS, WARNING, FAIL, or N/A
- Write detailed findings to output file
Pre-Audit Data Validation
Before scoring, validate data quality:
- Minimum data window: ≥30 days of spend data for budget assessment
- Activity check: Campaigns must have active spend in the data window
- Volume check: Need ≥30 days of conversion data for CPA/ROAS-based checks
- If data is insufficient, display a ⚠️ Data Quality Warning at the top of the report:
"⚠️ Limited data: Budget assessment based on [X] days of data. Learning phase and bidding checks may not reflect steady-state performance."
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.
- 11d ago First seen · 148 lines · 36 tokens per session scan A 335ac0a0f1b5
audit-budget is an agent published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 7d ago), licensed MIT. It adds 36 tokens to every session and 1,917 once invoked, about $0.0002 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 2026-08-30.
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