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.
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 agentmods add skills/aws-samples/sample-agentic-chatbot-accelerator/ai-dlcnpx skills add aws-samples/sample-agentic-chatbot-accelerator --skill ai-dlcgit 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/ai-dlc)<a href="https://agentmods.dev/skills/aws-samples/sample-agentic-chatbot-accelerator/ai-dlc"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agentic-chatbot-accelerator/ai-dlc.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.00780 |
| Opus 5 | $0.00014 | $0.00390 |
| Sonnet 5 | $0.00005 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
ai-dlc 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 4d 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 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.
- 4d ago First seen · 42 lines · 27 tokens per session scan A 838793b66ce2
ai-dlc is a skill published in the GitHub repository aws-samples/sample-agentic-chatbot-accelerator (22 stars, last pushed yesterday), licensed MIT-0. It adds 27 tokens to every session and 780 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
amazon-bedrock-agentcore-mcp
Documentation on AgentCore platform services.
library-development
Build and extend strands-compose — the declarative YAML to strands resolution library in src/strandscompose. Use when adding or editing config schema, loaders, resolvers, orchestration builders, model/mcp/tool/hook resolution, streaming, manifests, or the CLI. Library source only; not tests, examples, or docs.
library-testing
Write, repair, and reason about tests for the strands-compose library in tests/. Use whenever adding, fixing, or reviewing tests, or deciding what to test for a library change. Defines what is worth testing, what is not, and how. Library tests only; not examples or docs prose.
troubleshoot
Diagnose and fix common ABCA issues: deployment failures, preflight errors, authentication problems, agent failures, and build issues. Use when the user says "troubleshoot", "debug", "not working", "error", "failed", "help me fix", "preflightfailed", "task failed", "deploy failed", "auth error", "401", "422", "503"…
onboard-repo
Onboard a new GitHub repository to the ABCA platform so the agent can target it. Use when the user says "onboard a repo", "add a repository", "register a repo", "new repo", or gets a REPONOTONBOARDED / 422 error about an unregistered repository.
deploy
Deploy, diff, or destroy the ABCA CDK stack. Handles pre-deployment validation, synthesis, and post-deployment verification. Use when the user says "deploy", "cdk deploy", "deploy the stack", "destroy", "cdk diff", "what changed", "redeploy", or "update the stack".