alibabacloud-iac-code

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.

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:

   text

   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:

   json

   {
     "channel": "codex",
     "pipelineName": "selling_solution_first",
     "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. pipelineName selects the implementation used only after Pipeline mode is chosen: selling_solution_first is the default, while the legacy selling flow is used only when this install-local file explicitly selects it. 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 null 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. The bridge rejects unknown configuration fields and invalid Pipeline names. If config.json or pipelineName is absent, Pipeline mode uses selling_solution_first; other absent fields keep their existing defaults. 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.

   Normal is the overall default, including concrete resource queries/changes, template work, troubleshooting, and deployment of a clear target. Use --mode pipeline only when the user explicitly requests it or the request genuinely needs the candidate-architecture, cost-comparison, plan-confirmation, and deployment flow. Pipeline mode uses solution-first unless the installed configuration explicitly selects legacy selling. Questions, permissions, tool use, or deployment alone do not select Pipeline. When uncertain, use normal. Start performs a non-secret configuration preflight through the Runtime. An incomplete LLM provider/API Key returns llm_not_configured and stops before creating a job. Both supported Pipelines require complete Alibaba Cloud credentials and otherwise return cloud_credentials_not_configured. Normal mode may continue without cloud credentials for work that does not call cloud APIs; report its preflight warning rather than claiming cloud operations are available.

3. --follow consumes the event stream until the next parent/candidate step boundary, permission, user question, candidate selection, turn_completed, or terminal state. It writes every parent step_started/step_completed/step_failed and candidate candidate_step_started/candidate_step_completed/candidate_step_failed boundary plus low-frequency bounded heartbeats to stderr; stdout contains one bounded JSON result. A boundary result sets boundaryReached: true, presentationRequired: true, and provides ready-to-display localized strings in userUpdates. Before invoking another tool, emit every userUpdates string in a user-visible assistant text block, including the Step 1/2 conclusion already embedded in completed-step updates. Never leave these updates only in reasoning, Bash output, a tool description, or the final summary. After that visible text block, immediately call follow again with the returned cursor. Do not treat boundaryReached as completion. Do not expand this into raw tool-event or token-delta output. While it is running, do not independently answer the infrastructure task or ask a parallel business question. Only ask the user when the current result contains inputRequired.

4. If follow reaches its bounded wait window, call the diagnostic follow command again with the returned cursor:

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   python3 scripts/iac_code.py follow --job-id <job-id> --cursor <cursor> --wait-seconds 60
   

   The recommended wait is 60 seconds and the bridge enforces a 120-second maximum even if a larger value is supplied. If a result says state: input-required but does not contain inputRequired, there is no user boundary to answer. Report its latestText or error, keep the same job unchanged, and stop. Never call continue, repeat respond, call cancel, or start a replacement job unless the user explicitly requests that action.

5. When state is turn_completed, treat finalText and artifacts as the authoritative normal-turn result. When a Pipeline reaches any terminal state, including completed, failed, canceled, or rejected, treat pipelineResult and artifacts as its authoritative result and present its success or failure details directly. If rollback cleanup is pending, the bridge automatically runs a cleanup-only normal task in the same context before returning the Pipeline result; keep following it and handle any returned permission normally. If cleanup is failed or unavailable, report that manual inspection or retry is required and do not claim it succeeded. Never send a synthetic cleanup prompt or a follow-up merely to retrieve or summarize an existing result. Never recover an answer from Session files, spool files, logs, or raw tool-result files.

6. To send the next natural-language message in the same normal conversation, or after a completed Pipeline has handed the same conversation to normal mode, write it to another workspace prompt file and continue the existing job:

   text

   python3 scripts/iac_code.py continue --job-id <job-id> --prompt-file <prompt-file> --follow
   

   Keep the same jobId and contextId. A new taskId per normal turn is expected. Never call start --mode normal to continue a completed Pipeline, and never call start merely because a normal turn completed.

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

text

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

User input

Treat every inputRequired as a hard user-interaction boundary. Present it through the outer Agent's native user-question or approval UI and stop until the user explicitly answers that specific boundary. If no native UI is available, ask in a visible assistant turn and stop. Never infer, recommend-and-select, or submit an answer from the original infrastructure request, a prior answer, an outer tool-execution approval, a default, or the fact that only one option is available. Do not write an answer file or invoke respond before the user's answer arrives. Preserve every correlation field in the response, and never reuse an answer file from another request.

• For permission, always ask the user to choose one of the returned actions, including for read-only or apparently safe operations. The original request and the outer Agent's permission policy do not authorize an iac-code permission boundary. iac-code has already applied its own allow/deny rules, and the outer Agent must not override an iac-code denial. Present title, purpose, effect, target, isReadOnly, deploymentSummary, and safeSummary; do not expose raw tool input or infer safety from the internal toolName alone.
• For ask_user_question, present the current prompt and options without inventing a second question, then wait for the answer. Accept a listed option. Accept free text only when allowFreeText is true; when present, show freeTextPrompt with the input.
• For candidate_selection, present every option's summary, render architectureDiagram as Mermaid when present, and show totalMonthlyCost plus costItems, then ask the user to select one. Ask even when there is only one candidate. Do not invent missing details, replace these prices with a rough estimate, or choose on the user's behalf. Return only the candidate ID/index selected by the user.
• For deployment_confirmation, present solutionSummary, templateUrl, the quote or explicit quote failure in cost, effectiveDeploymentParameters, parameterOverrides, previewReadyForCreate, and exactly the actions returned in options, then ask the user to select an action. A request to create or deploy infrastructure is not confirmation for this boundary. The bridge derives this bounded display projection directly from the Runtime's existing A2A Pipeline confirmation event; never supplement it from local Session, journal, template, spool, or tool-result files. Never confirm, adjust, reselect, or cancel on the user's behalf, including after a failed quote or Preview.
• 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.

After the user answers, 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>"}.
• Deployment confirmation: {"kind":"deployment_confirmation","requestTaskId":"<requestTaskId>","contextId":"<contextId>","inputId":"<inputId>","action":"<action selected by the user>","parameterOverrides":{"<parameter selected by the user>":"<value selected by the user>"}}. Allowed actions are confirm, adjust, reselect, and cancel; omit parameterOverrides when the user did not request an adjustment.

text

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

If the user cancels the whole operation, call:

text

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:

text

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:

text

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.

Input/output examples

Input: "Create and validate a ROS template for a VPC and two subnets in cn-hangzhou."

Expected output: the bridge returns the authoritative iac-code result, including the generated or validated template, progress boundaries, any permission request, and actionable errors without inventing cloud state.

Edge cases

If the packaged Runtime cannot be downloaded or verified, stop and report the verification error; never install an unverified fallback. If credentials are incomplete, report the preflight result and do not claim that cloud operations ran. Continue an existing job with its job ID instead of starting a replacement job.

RAM permissions

Before a task that reads or changes Alibaba Cloud resources, read references/ram-policies.md. Grant only the exact actions required by the selected workflow; template-only and Runtime-cache workflows require no Alibaba Cloud RAM permission.

Observability

All outbound HTTP requests made by this AgentHub Skill carry this User-Agent template:

text

AlibabaCloud-Agent-Skills/alibabacloud-iac-code/{session-id}

• alibabacloud-iac-code is the fixed AgentHub Skill identifier and matches the frontmatter name.
• The session ID must be a 32-character lowercase hexadecimal string generated exactly once per session. It must be reused unchanged for every outbound HTTP request in that session. The bridge reads SKILL_SESSION_ID after validation; if it is absent or invalid, the bridge generates the session ID with uuid.uuid4().hex and stores it for that session.