iac-code

name

iac-code

description

Use the packaged iac-code agent for Alibaba Cloud infrastructure tasks, including designing, provisioning, changing, or deploying resources; generating, reviewing, converting, validating, or troubleshooting ROS and Terraform templates; selecting existing cloud resources; estimating costs; operating ROS stacks; and inspecting or explicitly cleaning downloaded iac-code Skill Runtime caches. Trigger for Alibaba Cloud infrastructure work even when the user does not mention iac-code, ROS, Terraform, or this Skill, and for requests to inspect or clean the iac-code Runtime cache. Do not trigger for general Alibaba Cloud questions or unrelated application code. For matched requests, invoke the packaged bridge before any alternative tool and fail closed on bridge errors. Run through the local authenticated A2A runtime without pip or headless mode.

iac-code

Use the single standard-library entry point at scripts/iac_code.py. Never install iac-code with pip and never invoke a headless command. Run every command below with python3 on macOS/Linux. On Windows, replace python3 with py -3; use python only after confirming it is CPython 3.8–3.14. Resolve the launcher once and reuse it for the whole job.

Mandatory routing and fail-closed behavior

For every infrastructure request covered by this Skill, the first operational command must invoke the packaged bridge with scripts/iac_code.py start. Do not inspect the bridge source, reconstruct its behavior, write a replacement script, call Alibaba Cloud APIs directly, or install an alternative CLI or runtime before that invocation. Runtime-cache requests are the only exception: their first operational command must be scripts/iac_code.py cache list.

Treat a bridge error returned before job creation as the authoritative outcome for that invocation. In particular, when the bridge returns incompatible_host, report its error code, message, retryability, and any available host/runtime-baseline facts, then stop. Do not install Terraform, pip packages, another Runtime, or other substitute tools; do not bypass the bridge with direct cloud calls; do not ask for deployment inputs; and do not continue the infrastructure workflow or claim success. A later attempt is allowed only after the host compatibility problem has actually been corrected.

Workflow

1. Put the complete user request in a UTF-8 prompt file inside the workspace.

2. Start a job with an explicit absolute workspace:

   python3 scripts/iac_code.py start --mode normal --cwd <workspace> --prompt-file <prompt-file> --language <language> --follow
   

   Set <language> to the user's language code (en, zh, es, fr, de, ja, or pt). If it is unknown, use auto. Every job result repeats preferredLanguage; treat it as durable control state across all turns. Present progress, questions, permissions, candidate plans, and final results in that language; protocol field names, enums, IDs, and commands remain unchanged. When authoritative text already uses preferredLanguage, present it directly or summarize it in the same language—never translate Chinese user-visible content into English.

   The installer or Skill distributor may place an optional config.json beside this SKILL.md:

   {
     "channel": "codex",
     "permissionWaitPolicy": {
       "residentTimeoutSeconds": null,
       "subPipelineTimeoutSeconds": null,
       "timeoutGraceSeconds": 30
     }
   }
   

   channel stores only the channel identifier; the bridge adds the skill/ prefix before sending it to iac-code. permissionWaitPolicy applies only to the temporary A2A server owned by this Skill: null timeouts mean unlimited waits, positive finite values set resident/Sub Pipeline limits, and grace is a non-negative finite value. Finite values cannot exceed 10 years; use instead of an arbitrarily large number for an unlimited resident or Sub Pipeline wait. The bridge validates and converts this object into server configuration; it never sends the policy through A2A message metadata. Missing fields use the defaults shown above. The bridge rejects unknown configuration fields. If the file or a field is absent, no corresponding override is applied. Never derive these values from the user's request, ask the user for them, or create, edit, or reveal this install-local configuration during an infrastructure task.

Use poll only for diagnosis or recovery when follow cannot be used:

python3 scripts/iac_code.py poll --job-id <job-id> --cursor <cursor> --wait-seconds 5

User input

When inputRequired is present, preserve every correlation field in the response. Never reuse an answer file from another request.

• For permission, apply the outer Agent's own equivalent permission policy. If the same operation would proceed without asking when invoked directly by the outer Agent, respond allow_once; if that policy would deny, respond deny; otherwise ask the user. iac-code has already applied its own allow/deny rules, and the outer Agent must not override an iac-code denial. Base the decision on title, purpose, effect, target, isReadOnly, deploymentSummary, and safeSummary; do not infer safety from the internal toolName alone. When asking about deployment, show the provided plan, region, stack, template, total price, and per-resource prices without exposing raw tool input.
• For ask_user_question, present the current prompt and options without inventing a second question. Accept a listed option. Accept free text only when allowFreeText is true; when present, show freeTextPrompt with the input.
• For candidate_selection, first present every option's summary, render architectureDiagram as Mermaid when present, and show totalMonthlyCost plus costItems. Do not invent missing details or replace these prices with a rough estimate. Then return the selected candidate ID/index requested by the envelope.
• Bind every user answer only to the current kind, inputId, requestTaskId, and contextId. Never reinterpret a resource selection as deployment confirmation or reuse it for a later input.

For an automatically decided permission, respond in one tool call while preserving the current input and tool identities:

python3 scripts/iac_code.py respond --job-id <job-id> --input-id <inputId> --tool-use-id <toolUseId> --decision allow_once --follow

Use deny when the outer Agent's policy denies it. For a user question, candidate selection, or permission that was explicitly shown to the user, write the correlated answer as JSON to a UTF-8 file and resume the same job:

• Permission: {"kind":"permission","requestTaskId":"<requestTaskId>","contextId":"<contextId>","inputId":"<inputId>","toolUseId":"<toolUseId>","decision":"allow_once"} or use deny.
• Question: {"kind":"ask_user_question","requestTaskId":"<requestTaskId>","contextId":"<contextId>","inputId":"<inputId>","answer":"<option, or free text only when allowed>"}.
• Candidate: {"kind":"candidate_selection","requestTaskId":"<requestTaskId>","contextId":"<contextId>","inputId":"<inputId>","answer":"<candidate ID or index>"}.

python3 scripts/iac_code.py respond --job-id <job-id> --input-file <answer-file> --follow

If the user cancels the whole operation, call:

python3 scripts/iac_code.py cancel --job-id <job-id>

Do not turn task cancellation into a permission denial.

Runtime cache maintenance

Only inspect or clean downloaded Runtime packages when the user explicitly asks about iac-code Skill Runtime storage or cleanup. This does not require starting an A2A job.

First list the installed packages and show each Runtime tag, target, size, and whether it is current or active, plus the total size:

python3 scripts/iac_code.py cache list

Before deleting anything, show what will be removed and obtain explicit user confirmation. Then clean either one listed tag or historical Candidate packages:

python3 scripts/iac_code.py cache clean --runtime-tag <tag> --confirm
python3 scripts/iac_code.py cache clean --candidates --confirm

The current pinned Runtime and packages used by a live A2A process are protected and reported under skipped. Never treat an ordinary infrastructure request as cleanup consent. These commands remove only downloaded Runtime packages; they do not remove sessions, jobs, server state, artifacts, credentials, or user configuration.

Output discipline

• Treat the script's stdout as its stable JSON protocol; diagnostics and cold-install progress are written to stderr.
• Keep only the current job identity, newest cursor, current input envelope, and authoritative boundary result in working context. Follow and poll outputs are bounded, redacted projections.
• Treat live step-boundary records as transient user-visible progress. Show them when received, but do not copy the full history back into later prompts or repeat all of it in the final answer.
• Use latestText only as running progress. Use pipelineResult from a terminal Pipeline as its success or failure result. Only finalText from a turn_completed result or a returned result artifact is a normal-turn answer.
• Do not expose runtime tokens, local state files, credentials, environment values, or raw tool inputs/results.
• If an error code is returned, report the concise message and suggested retry. Do not fall back to pip installation or another ABI artifact.