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 phuonghx/aim-cli --skill token-optimizergit clone --depth 1 https://github.com/phuonghx/aim-cliWrote 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/phuonghx/aim-cli/token-optimizer)<a href="https://agentmods.dev/skills/phuonghx/aim-cli/token-optimizer"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/token-optimizer/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/phuonghx/aim-cli/token-optimizer"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/token-optimizer.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 | $0.00043 | $0.00579 |
| Opus 5.5 | $0.00017 | $0.00232 |
| Sonnet 5.5 | $0.00009 | $0.00116 |
| Haiku 4.5 | $0.00004 | $0.00058 |
Grade A, and why
token-optimizer 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token Optimizer (aim-rtk)
AI agents pay for every token read or written. During development, excessive logs or full-file rewrites waste cost and exhaust context windows. Follow these optimization guidelines.
1. RTK (Rust Token Killer) Command Principles
Whenever running terminal commands, reduce output to the bare minimum needed for debug/analysis:
A. Git Operations (Save 60-80% tokens)
- Status: Use
git status -sinstead of a rawgit status. - Diff: Use
git diff --statfirst to see which files changed. Pull specific diffs viagit diff <file>instead of dumping all files. - Log: Always limit history, e.g.,
git log -n 5 --oneline. - Commits: Avoid verbose outputs on pushes or pulls.
B. Builds & Compilation (Save 80-90% tokens)
- Pipe command outputs to filter for errors or warnings (e.g. on Unix use
cmd | grep -E "Error|Warning", on Windows usecmd | Select-String "Error"). - For TypeScript, run
tsc --noEmitbut group outputs or check only modified files. - Avoid printing full successful build metrics.
C. Testing (Save 90-99% tokens)
- Do not run the entire test suite in verbose mode.
- Filter test runs to target only the specific file or test name:
- Jest/Vitest:
npm test -- -t "test-name" - Pytest:
pytest -k "test_name" - Go:
go test -run "TestName"
- Jest/Vitest:
- Instruct the runner to print failures only (e.g.,
--reporter=lineor--summary-only).
D. File Navigation & Search (Save 60-75% tokens)
- Do not read whole files just to locate a function or variable. Use
grepsearch or symbol lookup first. - Only load line ranges of interest (e.g., lines 40-80) instead of reading 1000 lines.
- Limit directory listing: use
globorgit ls-filesinstead of listing all subdirectories recursively.
2. Token-Efficient Editing
- Use targeted replacements: Never replace an entire file if you only need to modify a 10-line block. Use specific replace tools that replace precise lines by matching target content.
- Commit frequently: Small commits keep the git diff concise, making it easier for subsequent AI steps to understand what changed.
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 · 42 lines · 43 tokens per session scan A 5945a61a179e
token-optimizer is a skill published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 3mo ago), licensed MIT. It adds 43 tokens to every session and 579 once invoked, about $0.0002 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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