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/epam/ai-dial-ui-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/epam/ai-dial-ui-kit/apply-review)<a href="https://agentmods.dev/commands/epam/ai-dial-ui-kit/apply-review"><img src="https://agentmods.dev/badge/commands/epam/ai-dial-ui-kit/apply-review/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/epam/ai-dial-ui-kit/apply-review"><img src="https://agentmods.dev/badge/commands/epam/ai-dial-ui-kit/apply-review.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 | $0.00000 | $0.00238 |
| Opus 5.5 | $0.00000 | $0.00095 |
| Sonnet 5.5 | $0.00000 | $0.00048 |
| Haiku 4.5 | $0.00000 | $0.00024 |
Grade A, and why
apply-review 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 25d 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
Apply review feedback (fixes only)
You are in fix-only mode.
- Input — Use the prioritized review from this thread (from
/review-changesor pasted comments). If there is no numbered or clear list, ask the user to paste the must-fix items. - Scope — Address only the listed issues (must-fix first, then nice-to-have if the user asked). Do not introduce unrelated cleanups, renames, or “while we’re here” edits.
- Traceability — For each review item, either fix it or reply with a short reason it is out of scope / won’t fix (with user confirmation if debatable).
- Regression — Prefer minimal diffs; keep public API stable unless the review explicitly requires a breaking change.
- Verify — After fixes run
npm run typecheck,npm run lint,npm run test. Ensure Storybook-related files still typecheck if you touched stories.
Do not perform a full new review in this turn unless the user asks.
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.
- 25d ago First seen · 12 lines · 0 tokens per session scan A ad552b28d5ff
apply-review is a command published in the GitHub repository epam/ai-dial-ui-kit (10 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 238 tokens. 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 2026-09-19.
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