Borrowing it
Nothing to install: this file belongs to phuoctrung-ppt/ai-sdlc-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/phuoctrung-ppt/ai-sdlc-workflow/master/.cursor/commands/ai-cost-check.mdgit clone --depth 1 https://github.com/phuoctrung-ppt/ai-sdlc-workflowWrote 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/commands/phuoctrung-ppt/ai-sdlc-workflow/ai-cost-check)<a href="https://agentmods.dev/commands/phuoctrung-ppt/ai-sdlc-workflow/ai-cost-check"><img src="https://agentmods.dev/badge/commands/phuoctrung-ppt/ai-sdlc-workflow/ai-cost-check/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/commands/phuoctrung-ppt/ai-sdlc-workflow/ai-cost-check"><img src="https://agentmods.dev/badge/commands/phuoctrung-ppt/ai-sdlc-workflow/ai-cost-check.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 | $0.00055 | $0.00323 |
| Opus 5 | $0.00028 | $0.00161 |
| Sonnet 5 | $0.00011 | $0.00065 |
| Haiku 4.5 | $0.00006 | $0.00032 |
Grade A, and why
ai-cost-check 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 8d 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.
What it actually says
Domain command — only relevant when
AGENTS.md §2AI/LLM ≠none. Skip for projects with no LLM features.
Act as AI Worker compliance review.
Review: {ai_code_path}
Read AGENTS.md §2 (AI/LLM providers, cost policy) and §5 (AI ethics requirements) before auditing.
Verify:
- All LLM calls route through a central router/service — no direct provider calls scattered in controllers or routes
- Budget check performed before every LLM call; cost usage logged after every call
- Usage event emitted after each call with: provider, model, tokens in/out, cost_usd, latency_ms (and any project-specific dimensions from
AGENTS.md §2) - Fallback provider configured on primary failure
- Cost calculation uses a shared utility (not duplicated per caller)
- Human-in-the-loop gate for consequential AI decisions (per
AGENTS.md §5— e.g. hire/reject, loan, medical) - XAI explanation returned for AI decisions that affect users (confidence score, key factors)
- User input sanitized before passing to LLM
Output: PASS/FAIL with specific issues and file:line references.
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.
- 8d ago First seen · 25 lines · 55 tokens per session scan A 1b8dd64efb09
ai-cost-check is a command published in the GitHub repository phuoctrung-ppt/ai-sdlc-workflow (2 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 323 once invoked, about $0.0003 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.
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