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/ivklgn/ai-kitWrote 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/ivklgn/ai-kit/ask-me)<a href="https://agentmods.dev/commands/ivklgn/ai-kit/ask-me"><img src="https://agentmods.dev/badge/commands/ivklgn/ai-kit/ask-me/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/ivklgn/ai-kit/ask-me"><img src="https://agentmods.dev/badge/commands/ivklgn/ai-kit/ask-me.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 | $0.00113 |
| Opus 5.5 | $0.00014 | $0.00045 |
| Sonnet 5.5 | $0.00007 | $0.00023 |
| Haiku 4.5 | $0.00004 | $0.00011 |
Grade A, and why
ask-me 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.
What it actually says
/ai-kit:ask-me
Arguments
The user invoked this command with: $ARGUMENTS
An empty value means the full list. blocking keeps only items that gate a plan step. Any other value names a plan step or topic to narrow to.
Instructions
Use the skill at skills/ask-me/SKILL.md.
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 · 16 lines · 36 tokens per session scan A 1e37024d12b5
ask-me is a command published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 113 once invoked, about $0.0001 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 2026-09-05.
Other commands, from other repositories
pull-repos
Pull all repos (parent + marketplace clones + configured project repos).
security-scan
Run security audit on codebase.
test-suite
Run comprehensive test suite with coverage analysis.
deps-update
Audit and update dependencies safely.
assemble-team
Assemble a pre-built agent team for parallel work - review, feature, debug, cross-platform, full-stack, or research.
run
Execute prompt(s) from ./prompts/ with automatic archiving - for structured prompt-based work.