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aitask-refresh-code-models
Research latest AI code agent models via web and update models_*.json configuration files.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Research latest AI code agent models via web and update models_*.json configuration files.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Create, refresh, or show an implementation trail — a durable, wave-structured, evidence-backed task-sequencing artifact stored via ait artifact.
Create, refresh, or show an implementation trail — a durable, wave-structured, evidence-backed task-sequencing artifact stored via ait artifact.
Shadow companion for a followed coding agent — reads its captured terminal output and, in one instruction-driven flow, explains it, helps answer an AskUserQuestion, or critically interrogates a plan. Advisory-only. Spawned by minimonitor; not a task-implementation command.
Draft a manager-facing work report from selected board columns.
Pick and implement a task in remote/non-interactive mode. All decisions from execution profile - no AskUserQuestion calls.
Pick and implement a task on Claude Code Web. Zero interactive prompts. No cross-branch operations — stores task data locally in .aitask-data-updated/.
| name | aitask-refresh-code-models |
| description | Research latest AI code agent models via web and update models_*.json configuration files. |
Read all model config files and the project defaults:
Glob to find all aitasks/metadata/models_*.json filesaitasks/metadata/codeagent_config.json to identify which models are configured as defaults for each operation (these will be marked "IN USE" in the change report)Extract the agent name from each filename: models_claudecode.json → claudecode, models_codex.json → codex, etc.
Present the discovered agents to the user for selection.
Use AskUserQuestion (multiSelect):
If "All agents" is selected, process all discovered agents. Otherwise, process only the selected agents.
Process each selected agent sequentially. For each agent:
--model or -m flag)If a WebFetch URL fails (404, redirect to different content), fall back to WebSearch results. If WebSearch also returns no relevant results for an agent, report "No updates found for <agent>" and continue to the next agent.
OpenCode special handling: OpenCode models are discovered exclusively via CLI — web research is NOT used. If opencode is selected:
opencode binary is available: command -v opencodebash .aitask-scripts/aitask_opencode_models.shaitasks/metadata/models_opencode.json"status": "unavailable" (never deleted, verified scores preserved)opencode is NOT installed, inform the user: "OpenCode binary not found — cannot refresh OpenCode models. Install OpenCode first." and skip OpenCode.Use generic terms — do NOT hardcode year references:
"Anthropic Claude models API model IDs latest""OpenAI Codex CLI models latest"For each selected agent, compare the current models_*.json content against the web research results. Categorize each model:
NEW: Discovered in web research but not present in current config (match by cli_id). Generate:
name: following the naming convention (see Model Naming Convention below)cli_id: exact API/CLI model ID from documentationnotes: brief description from documentationverified: { "pick": 0, "explain": 0, "batch-review": 0 }verifiedstats: {}UPDATED: Model exists in config but notes/status changed significantly (e.g., moved from preview to stable, description updated). Propose updated notes field.
DEPRECATED?: Model exists in config but was NOT found in current documentation. Flag as potentially deprecated — do NOT automatically remove.
UNCHANGED: Model exists in both config and documentation with no significant changes.
Display a structured change report. For each selected agent:
### <Agent Name>
- NEW: <cli_id> (<proposed_name>) — "<notes>"
- UPDATED: <cli_id> (<name>) — notes changed: "<old>" → "<new>"
- DEPRECATED?: <cli_id> (<name>) — not found in current docs
- UNCHANGED: <cli_id> (<name>) [IN USE: pick, explain]
Mark models as [IN USE: <operations>] if they appear in codeagent_config.json defaults.
If no changes were found for any agent, inform the user and end the workflow.
Use AskUserQuestion:
If "Apply selectively": For each agent that has changes, use AskUserQuestion (multiSelect) to let the user pick which specific changes to apply.
If "Abort": End the workflow.
For each agent with approved changes:
aitasks/metadata/models_<agent>.jsonmodels arraynotes field for updated modelsverified scores and verifiedstats data for unchanged and updated modelsaitasks/metadata/models_<agent>.json
status, verified, and verifiedstatsFor new models, initialize both verified and verifiedstats even if no feedback has been recorded yet.
Seed sync (conditional):
seed/ directory exists in the repository rootmodels_<agent>.json to seed/models_<agent>.jsonseed/ does not exist, skip this stepAfter updating model files, verify that the research URLs listed in this SKILL.md are still reachable.
For each URL in the Research URLs section:
WebFetch with prompt: "Is this page accessible? Return the page title and a one-line summary."This step is informational only — do not automatically edit the SKILL.md. The user should manually review and update URLs if needed.
Stage and commit the changes using the appropriate git commands:
Metadata files (task data branch):
./ait git add aitasks/metadata/models_claudecode.json aitasks/metadata/models_codex.json aitasks/metadata/models_opencode.json
./ait git commit -m "ait: Refresh code agent model configurations"
Only include files that were actually modified — skip unchanged agent files.
Seed files (main branch, only if seed/ exists and files were updated):
git add seed/models_claudecode.json seed/models_codex.json seed/models_opencode.json
git commit -m "ait: Sync refreshed models to seed templates"
Display summary: "Model configurations updated. N new models added, M models updated, K models flagged as deprecated."
Execute the Satisfaction Feedback Procedure (see .claude/skills/task-workflow/satisfaction-feedback.md) with skill_name = "refresh-code-models".
When generating name fields for new models, follow these rules:
opus4_6)3_1, 2.5 → 2_5)cli_id)_preview for preview models, _max for max-context variants, _flash for flash/fast variantsExamples:
| Display Name | name | cli_id |
|---|---|---|
| Claude Opus 4.6 | opus4_6 | claude-opus-4-6 |
| GPT-5.3 Codex Spark | gpt5_3codex_spark | gpt-5.3-codex-spark |
| Kimi K2.5 | kimi_k2_5 | kimi-k2.5 |
These URLs are used during the web research phase (Step 3). They are checked for validity in Step 7 and should be updated if they become stale.
--model flag. Prefer explicit versioned IDs (e.g., claude-opus-4-6) over aliases (opus).-m flag. Models are GPT-based codex variants.--model flag. Provider-based model IDs from multiple AI providers.WebSearch and WebFetch tools — no external scripts neededverified scores and verifiedstats history are always preserved — only new models get all-zero scores and empty stats objectsaitasks/metadata/ (via ./ait git) and seed/ (via plain git) are updated when applicable