Agent-Assisted SDLC is a sample software development pipeline in which an AI coding assistant reads an issue, changes a codebase, and opens a pull request through Amazon Bedrock AgentCore. Developers use it to automate work from an issue to a proposed code change, with a shared orchestration process and repository-specific guidance. The catalogue entries provide the skills, agents, plugin, hook, and instruction used by this workflow.
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 aws-samples/sample-agent-assisted-sdlc --skill formattinggit clone --depth 1 https://github.com/aws-samples/sample-agent-assisted-sdlcWrote 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-agent-assisted-sdlc/formatting)<a href="https://agentmods.dev/skills/aws-samples/sample-agent-assisted-sdlc/formatting"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agent-assisted-sdlc/formatting/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-agent-assisted-sdlc/formatting"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agent-assisted-sdlc/formatting.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 | $0.00021 | $0.00231 |
| Opus 5.5 | $0.00008 | $0.00092 |
| Sonnet 5.5 | $0.00004 | $0.00046 |
| Haiku 4.5 | $0.00002 | $0.00023 |
Grade A, and why
formatting 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 5d 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 to all .md files you write AND every issue/PR comment you post.
Ignore for code blocks, tables, and bulleted lists.
- Do NOT hard-wrap paragraphs at a column limit (no 70- or 80-char wraps). Write one paragraph per line and let the renderer wrap. Hard wrapping makes diffs noisy and future edits painful.
- Use ATX-style headings (
#,##,###). Don't stack equivalent headings. - Match the existing project's heading hierarchy and bullet style.
- Issue comments: prefix with the designated
### Reportheading. Do NOT add#or##inside the body — start subsections at###or lower. - The PR body starts at
##(What / Why / How / Testing) — no#H1. - Refer to critique findings as "Finding N", NOT "Issue #N" or "#N". NEVER write a bare "#N" — GitHub auto-links to unrelated issues.
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.
- 5d ago First seen · 15 lines · 21 tokens per session scan A 141981224e89
formatting is a skill published in the GitHub repository aws-samples/sample-agent-assisted-sdlc (47 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 231 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 2026-10-20.
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