Update Provider Deps
mondoohq/mql
Upgrade an mql provider's vendored SDKs (all providers or a named subset), audit the new versions for breaking changes and fix call sites while keeping shipped MQL fields backwards-compatible, check…
Onboard a new GitHub repository to the ABCA platform so the agent can target it.
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repo --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .claude/skills/onboard-repo && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .claude/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repoType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repo --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .agents/skills/onboard-repo && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .agents/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repo --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .cursor/skills/onboard-repo && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .cursor/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git --path docs/abca-plugin/skills/onboard-repo--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repo --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .gemini/skills/onboard-repo && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .gemini/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repoInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .github/skills/onboard-repo && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .github/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws-samples/sample-autonomous-cloud-coding-agents onboard-repo --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-autonomous-cloud-coding-agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/docs/abca-plugin/skills/onboard-repo .opencode/skills/onboard-repo && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "onboard-repo" agent skill from https://github.com/aws-samples/sample-autonomous-cloud-coding-agents/tree/main/docs/abca-plugin/skills/onboard-repo into .opencode/skills/onboard-repo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "onboard-repo", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
onboard-repoOnboard a new GitHub repository to the ABCA platform so the agent can target it.
Onboard Repo is an agent skill from aws-samples/sample-autonomous-cloud-coding-agents, published by the product's own GitHub organization. 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.
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud. It works with GitHub and Amazon Web Services. The repository describes itself as: Autonomous background coding agents on AWS. Turn tasks into pull requests via isolated runtimes, with built-in orchestration, observability, and governance. The licence is MIT-0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit dfcde8d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
miseawsFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
docs.aws.amazon.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Onboard Repo loads about 2.8k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 1,274 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from aws-samples/sample-autonomous-cloud-coding-agents at commit dfcde8d, republished under its MIT-0 licence (© aws-samples). 1,274 words, ~2,827 tokens.
.claude/skills/onboard-repo/SKILL.md (or your agent's skills folder).You are helping an operator register a GitHub repository with their running ABCA deployment so tasks can target it.
There are two paths.
Prefer the CLI operator path (Path A) when the repo can run on the platform/default-blueprint setup — the default GitHub token secret, a model already granted to the runtime, and the default egress allowlist. It's a single runtime command against the deployed stack: no code change, no redeploy.
Use the CDK Blueprint path (Path B) when the repo needs its own config that the CLI can't provision at runtime — a per-repo GitHub token, a model not yet granted to the runtime, custom egress domains, Cedar HITL policies, or system-prompt overrides. These are baked into infrastructure and require a redeploy (with the correct permissions). When in doubt, start with Path A; if a task later fails on a missing token / model grant / blocked egress, promote the repo to a Blueprint.
This is an operation, not a contribution. Onboarding a repo into your own deployment writes a record to the platform's RepoTable — it is not a change to the
aws-samplescodebase, so the ADR-003 contribution flow (GitHub issue → approval → feature branch) does not apply. Only invoke ADR-003 if the user is actually changing the platform source (e.g. wiring a brand-new Bedrock model into the stack — see "Model not yet wired into the runtime" below).
Use AskUserQuestion to collect (only the repository is required — the rest fall back to platform defaults):
owner/repo. Must match exactly what's passed to bgagent submit --repo later.agentcore (default) or ecs.global.) must match the deployment's bedrockGeoRegion; bgagent repo onboard rejects a mismatch at the CLI rather than letting the task fail at turn 0. If overriding, it must be a model already granted to the runtime (see "Model not yet wired into the runtime"), specified as a cross-Region inference-profile ID (e.g. global.anthropic.claude-opus-5), not a raw anthropic.* foundation-model ID.Per-task cost limits aren't set here.
max_budget/max_turnsper task are flags onbgagent submit(thesubmit-taskskill), not repo-onboarding fields. Onboarding sets only the per-repo defaultmax_turns.
If the repo needs config the CLI can't provision (per-repo egress, Cedar policies, system-prompt overrides, or a not-yet-granted model), use Path B instead.
bgagent repo onboard writes (or re-activates) the repository's RepoConfig row in
the deployed RepoTable directly. It takes effect immediately — no agent.ts edit,
no cdk deploy.
bgagent repo onboard <owner/repo>
# common overrides:
# --model <inference-profile-id> e.g. global.anthropic.claude-opus-5 (must be runtime-granted)
# --compute-type <agentcore|ecs>
# --max-turns <n> per-repo default turn limit
# --token-secret-arn <arn> per-repo GitHub token (else platform default)
# --runtime-arn <arn> override AgentCore runtime ARN (agentcore only)
# --poll-interval <ms> agent completion poll intervalThen confirm it landed:
bgagent repo list # status should be "active"
bgagent repo show <owner/repo> # full resolved config (secret ARNs redacted)That's it — the repo is onboarded. Submit a task with the submit-task skill.
Pick a model that is already wired into the runtime. With no --model, the repo
uses the platform default — read it from the stack's BedrockGeoRegion +
BedrockModelIds outputs rather than a literal here. If you pass --model, use a cross-Region
inference profile ID (e.g. global.anthropic.claude-opus-5), not a raw
anthropic.* foundation-model ID. Only models the stack has granted the runtime can
be invoked — see "Model not yet wired into the runtime" before choosing a model the
deployment doesn't already support.
Use this when the operator wants the repo committed to infrastructure-as-code (so a fresh deploy re-creates it) rather than set as a runtime record. This does require editing the stack and redeploying.
Read cdk/src/stacks/agent.ts to find where Blueprint constructs are defined and
the repoTable reference.
Add a construct following the existing pattern:
new Blueprint(this, 'MyRepoBlueprint', {
repo: 'owner/repo',
repoTable: repoTable.table,
// Optional overrides:
// computeType: 'agentcore',
// modelId: 'global.anthropic.claude-opus-5',
// maxTurns: 100,
// maxBudgetUsd: 50,
// githubTokenSecretArn: 'arn:aws:secretsmanager:...',
});Redeploy: mise //cdk:compile → mise //cdk:diff (show the diff) → mise //cdk:deploy -- --require-approval never.
Sample-repo shortcut: the stack's AgentPlugins blueprint resolves its
repofromBLUEPRINT_REPO(env) → CDK contextblueprintRepo→ defaultawslabs/agent-plugins. To target a fork of the sample without adding a construct, setexport BLUEPRINT_REPO=owner/repo(orcdk.jsoncontext) and redeploy.
A repo can only use a model the runtime IAM role has grantInvoke for. The granted
set is DEFAULT_BEDROCK_MODEL_IDS in
cdk/src/handlers/shared/bedrock-model-constants.ts — Sonnet 4.6,
Opus 4.8, Opus 5, and Haiku 4.5 — and a deployed stack publishes it as the
BedrockModelIds output, so read that rather than trusting this list to stay current:
aws cloudformation describe-stacks --stack-name <stack> \
--query "Stacks[0].Outputs[?OutputKey=='BedrockModelIds'].OutputValue" --output textOnboarding a repo pinned to any other model fails at invoke with a 403 — the CLI
onboard succeeds, but tasks can't run. bgagent repo onboard --model checks the value
against that output and rejects an ungranted model up front.
Pin the geo-prefixed inference-profile form, matching the stack's BedrockGeoRegion
output (e.g. global.anthropic.claude-opus-4-8), not the bare id — Bedrock refuses bare
ids for on-demand invocation, and the IAM grant is scoped to one geography's profile ARNs.
Granting a new model is a deploy-time change, not a construct edit: the list is overridable via CDK context, either on the command line or in cdk.json. Both forms behave identically — the resolver JSON-parses the string -c delivers.
cdk deploy -c bedrockModels='["anthropic.claude-opus-5","anthropic.claude-haiku-4-5-20251001-v1:0","anthropic.claude-sonnet-4-6"]'The override REPLACES the default list rather than adding to it, so it must include the two models the stack injects as ANTHROPIC_MODEL and ANTHROPIC_DEFAULT_HAIKU_MODEL — Opus 5 and Haiku 4.5. Omitting either fails at synth, naming the missing model, because every substrate is told to invoke them regardless of this list. (--context-file does not work for this: it is accepted and silently ignored.)
For a persistent setting, put the same array in the context block of cdk.json:
// cdk.json — this REPLACES the default list, so include the platform defaults
// (Opus 5 + Haiku 4.5) or the stack's own defaults are ungranted
"context": {
"bedrockModels": [
"anthropic.claude-opus-5",
"anthropic.claude-haiku-4-5-20251001-v1:0",
"anthropic.claude-sonnet-4-6"
]
}Three constraints on the value. Entries are bare ids — the geo prefix is derived from
bedrockGeoRegion, and a prefixed entry is rejected. Patterns are rejected too: these ids
become the resource half of the IAM grant, so a * would grant every inference profile in
the account. And each entry must have a live cross-Region inference profile:
aws bedrock get-inference-profile --inference-profile-identifier <geo>.<model>A granted model with no profile is the trap — it passes the CLI's --model check and
workflow admission (both read the grant list) and only fails at turn 0.
bgagent platform doctor checks the whole granted set for exactly this and names any
model that does not resolve.
Account-level Bedrock model access is separate from IAM: the account must have the model enabled for the Region — complete model access prerequisites (Marketplace actions / Anthropic first-time use where applicable). For cross-Region profiles, IAM and SCPs must allow Bedrock in source and destination Regions.
If the user just wants the agent working now, leave model_id unset so the repo takes the
platform default, and treat "add model X" as a separate, later change.
| Setting | Purpose | Default |
|---|---|---|
compute_type | Execution strategy | agentcore |
runtime_arn | AgentCore runtime override | Platform default |
model_id | AI model for tasks (inference profile ID) | Platform default (Opus 5, as <BedrockGeoRegion>.anthropic.claude-opus-5) |
max_turns | Turn limit per task | 100 |
max_budget_usd | Cost ceiling per task | Unlimited |
system_prompt_overrides | Custom system instructions | None |
github_token_secret_arn | Repo-specific GitHub token | Platform default |
poll_interval_ms | Completion polling frequency | 30000ms |
Task-level parameters override per-repo defaults; if neither specifies a value, platform defaults apply.
REPO_NOT_ONBOARDED / 422 — the repo isn't registered. Run bgagent repo onboard <owner/repo> (Path A). Confirm the owner/repo matches exactly what you pass to bgagent submit --repo.--token-secret-arn.model_id is a raw foundation-model ID; use the inference-profile ID (e.g. global.anthropic.claude-opus-5).© aws-samples, MIT-0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in docs/abca-plugin/skills/onboard-repo of aws-samples/sample-autonomous-cloud-coding-agents.
Open the folder on GitHubat commit dfcde8d
Onboard Repo next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Onboard Repo this skillaws-samples/sample-autonomous-cloud-coding-agents | 158 | — | ~2.8k | Automated safety check: Pass | MIT-0 | |
| Update Provider Depsmondoohq/mql | 412 | — | ~4.5k | Automated safety check: Pass | Custom licence | |
| Secrets Managementdavila7/claude-code-templates | 33k | 12 repos | ~2k | Automated safety check: Pass | MIT | |
| Phase 9 Deploymentww-w-ai/bkit-claude-code | 601 | — | ~2.7k | Automated safety check: Notes | Apache-2.0 | |
| AWS Cost Optimizegithub/awesome-copilot | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| AWS Well Architected Reviewgithub/awesome-copilot | 40k | — | ~1.9k | Automated safety check: Pass | MIT |
mondoohq/mql
Upgrade an mql provider's vendored SDKs (all providers or a named subset), audit the new versions for breaking changes and fix call sites while keeping shipped MQL fields backwards-compatible, check…
davila7/claude-code-templates
Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools.
ww-w-ai/bkit-claude-code
Deploy to production — CI/CD pipelines, environment config, deployment strategies.
github/awesome-copilot
Analyze AWS resources used in the app (IaC files and/or resources in a target account/region) and optimize costs - creating GitHub issues for identified optimizations.
github/awesome-copilot
Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.
mizchi/skills
OpenTofu/Terraform pattern for GitHub Actions OIDC trust with AWS IAM.
aws-samples/sample-autonomous-cloud-coding-agents
Deploy, diff, or destroy the ABCA CDK stack. An agent skill from aws-samples/sample-autonomous-cloud-coding-agents.
aws-samples/sample-autonomous-cloud-coding-agents
Guided installation and first-time setup for ABCA. An agent skill from aws-samples/sample-autonomous-cloud-coding-agents.
aws-samples/sample-autonomous-cloud-coding-agents
Submit a coding task to the ABCA platform via CLI or REST API.
aws-samples/sample-autonomous-cloud-coding-agents
Diagnose and fix common ABCA issues: deployment failures, preflight errors, authentication problems, agent failures, and build issues.
aws-samples/sample-autonomous-cloud-coding-agents
Check ABCA platform status — stack health, running tasks, and recent task history.
Works with
Categories
Onboard a new GitHub repository to the ABCA platform so the agent can target it. Onboard Repo is an agent skill from aws-samples/sample-autonomous-cloud-coding-agents, published by the product's own GitHub organization. Onboard a new GitHub repository to the ABCA platform so the agent can target it.
Onboard Repo fits situations like: the user says onboard a repo; add a repository; register a repo; gets a REPONOTONBOARDED / 422 error about an unregistered repository.
Run `npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a claude-code`. Or copy the skill folder (docs/abca-plugin/skills/onboard-repo in aws-samples/sample-autonomous-cloud-coding-agents) into .claude/skills/onboard-repo in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a codex`. Or copy the skill folder (docs/abca-plugin/skills/onboard-repo in aws-samples/sample-autonomous-cloud-coding-agents) into .agents/skills/onboard-repo in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws-samples/sample-autonomous-cloud-coding-agents --skill onboard-repo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/onboard-repo, .gemini/skills/onboard-repo, .github/skills/onboard-repo and .opencode/skills/onboard-repo in your project.
Going by SKILL.md and its folder, Onboard Repo needs the command-line tools its instructions call (mise and aws).
SKILL.md names 1 domain. As links in the text: docs.aws.amazon.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Onboard Repo is published under the MIT-0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Onboard Repo: Update Provider Deps (mondoohq/mql, 412 stars), Secrets Management (davila7/claude-code-templates, 33k stars), Phase 9 Deployment (ww-w-ai/bkit-claude-code, 601 stars) and AWS Cost Optimize (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aws-samples (a GitHub organization, an official publisher) maintains it in aws-samples/sample-autonomous-cloud-coding-agents, which has 158 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 10, 2026.
Source: aws-samples/sample-autonomous-cloud-coding-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.