What is adios-build-deploy?

A workflow for building, previewing, checking, and deploying projects through the hosted Adios service. It also covers importing workspaces, editing files, and creating the service's configuration file.

Use it to create or find an Adios workspace, change project files, check configuration, run lint and build checks, inspect logs, start a preview, and deploy after approval.

It gives an agent a defined path from source files to a checked preview and an approved deployment, while requiring inspection and validation along the way.

adios-build-deploy — Skill by adiosdotdev

Install

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.

agentmods

npx agentmods add skills/adiosdotdev/mcp/adios-build-deploy

Any agent

npx skills add adiosdotdev/mcp --skill adios-build-deploy

Clone the repo

git clone --depth 1 https://github.com/adiosdotdev/mcp

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 634 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00071	$0.00634
Opus 5	$0.00036	$0.00317
Sonnet 5	$0.00014	$0.00127
Haiku 4.5	$0.00007	$0.00063

Measured yesterday against content hash 80f64d47be3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

adios-build-deploy 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 yesterday.

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.

plugins/adios-mcp/skills/adios-build-deploy/SKILL.md · 33 lines

How it starts

The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build and Deploy with Adios

Use the adios MCP server to move source code through an inspectable workspace, preview, and deployment flow. Preserve the user's existing source and stop for explicit approval before production or destructive actions.

Workflow

Call auth_me and retain the returned team_id. If more than one team is possible and the request does not identify one, ask the user to choose.
Resolve the workspace with get_workspace or list_workspaces. Create a new workspace only when the user requests one or no suitable workspace exists.
Inspect before changing existing source with list_workspace_files, read_workspace_file, and get_workspace_git_status.
Write the smallest coherent change. Prefer write_workspace_files for a related batch and write_workspace_adios_yaml for a new manifest. Never place credentials in source or adios.yaml; use Adios secrets.
Run check_workspace_adios_yaml before a build or deploy. Address exposed secrets and risky command findings before continuing.
Use lint_workspace and build_workspace_dev for queued validation. Poll get_workspace_command_status and read get_workspace_command_logs until each command reaches a terminal state. Do not create duplicate commands while one is running.
Start or update a preview with prepare_workspace_preview or start_workspace_run, then verify with get_workspace_run_status and get_workspace_logs.
Summarize the verified revision, checks, preview URL, and remaining risks. Ask for explicit approval before deploy_workspace or deploy_workload; pass approved=true only after that approval.
After deployment, inspect get_workload_logs when a workload ID is available and report the release result.

Guardrails

Treat delete_workspace_file, stop_workspace_run, deploy_workspace, and deploy_workload as approval-sensitive. Never infer approval from a broad request to investigate, fix, preview, or build.
Do not overwrite unrelated files. Read an existing file before replacing it unless its full content was supplied by the user in the current task.
Keep team_id, workspace_id, command_id, build_id, and workload_id from tool results; do not guess IDs.
A successful tool call is not enough: verify queued commands, runtime readiness, and post-deploy logs.
If OAuth or team authorization fails, stop and ask the user to authenticate or select an authorized team. Do not seek broader credentials.

Read the full file on GitHub · 33 lines

Files

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.

agents/openai.yaml 463 B

Changes

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.

yesterday First seen · 33 lines · 71 tokens per session scan A 80f64d47be3a

Subscribe to this mod's changes

adios-build-deploy is a skill published in the GitHub repository adiosdotdev/mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 634 once invoked, about $0.0004 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 2026-08-31.

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