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 seb1n/awesome-ai-agent-skills --skill budget-planninggit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-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/skills/seb1n/awesome-ai-agent-skills/budget-planning)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/budget-planning"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/budget-planning/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/seb1n/awesome-ai-agent-skills/budget-planning"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/budget-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.02367 |
| Opus 5 | $0.00015 | $0.01184 |
| Sonnet 5 | $0.00006 | $0.00473 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
budget-planning 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 9d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Budget Planning
Create structured budgets by department, track actual spending against targets, and produce variance analyses that explain deviations. This skill supports top-down and bottom-up budgeting approaches, handles multi-department allocation, and generates actionable reports that highlight where spending is on track and where corrective action is needed.
Workflow
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Gather Historical Data Collect 6-12 months of actual spending data broken down by department and cost category. Identify trends, seasonal patterns, and one-time expenses that should be excluded from baseline calculations. Compute trailing averages and growth rates for each line item to establish a data-driven starting point.
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Set Budget Targets by Department Define top-level budget envelopes for each department based on company revenue targets, strategic priorities, and historical run rates. Apply growth adjustments — departments investing in new initiatives may get 15-25% increases while mature cost centers target flat or declining budgets. Ensure the sum of department budgets aligns with the company-wide operating expense target.
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Allocate Line Items Break each department budget into specific line items: personnel (salaries, benefits, contractors), software and tools, travel, marketing spend, office and facilities, professional services, and discretionary. Assign monthly phasing — some costs are evenly distributed while others are front-loaded (annual software renewals) or seasonal (Q4 marketing pushes).
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Track Actuals vs. Budget As actual spending data comes in, map each transaction to the corresponding budget line item and period. Calculate period-to-date (MTD, QTD, YTD) actuals and compare against the phased budget. Compute both absolute dollar variance and percentage variance for each line item.
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Generate Variance Reports Produce variance analysis showing over- and under-budget categories with explanations. Classify variances as timing (spending shifted between months but will normalize), volume (more/less activity than planned), rate (unit costs differ from plan), or permanent (structural change requiring budget revision). Project year-end estimates based on current run rates.
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.
- 9d ago First seen · 118 lines · 30 tokens per session scan A aa72e45a4ec5
budget-planning is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 2,367 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 2026-09-03.
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