aws-samples/sample-agentic-chatbot-accelerator is a full-stack AWS system for designing, deploying, testing, and improving multi-agent chatbots with text, voice, retrieval, and evaluation components. Developers use its Agent Factory, managed runtime, web interface, tool and MCP-server connections, and feedback workflows, with the catalogue containing add-ons for working with the accelerator.
Borrowing it
Nothing to install: this file belongs to aws-samples/sample-agentic-chatbot-accelerator. 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/aws-samples/sample-agentic-chatbot-accelerator/main/.claude/skills/commit/SKILL.mdgit clone --depth 1 https://github.com/aws-samples/sample-agentic-chatbot-acceleratorWrote 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/aws-samples/sample-agentic-chatbot-accelerator/commit)<a href="https://agentmods.dev/skills/aws-samples/sample-agentic-chatbot-accelerator/commit"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agentic-chatbot-accelerator/commit/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/aws-samples/sample-agentic-chatbot-accelerator/commit"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agentic-chatbot-accelerator/commit.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 | $0.00012 | $0.00400 |
| Opus 5.5 | $0.00005 | $0.00160 |
| Sonnet 5.5 | $0.00002 | $0.00080 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
commit 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.
The source is not reproduced here
Licensed MIT-0
The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 12 tokens per session scan A ef30ff90571a
commit is a skill published in the GitHub repository aws-samples/sample-agentic-chatbot-accelerator (24 stars, last pushed 2d ago), licensed MIT-0. It adds 12 tokens to every session and 400 once invoked, about $0.0000 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 2026-08-30.
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git-advanced-workflows
Master advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog to maintain clean history and recover from any situation. Use when managing complex Git histories, collaborating on feature branches, or troubleshooting repository issues.
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