This skill is responsible for replacing a logo or specified assets, modifying a native subproject, and updating downstream. It hands off to skills in the same package by name, can be used when installed on its own, and does not read sibling directories. Use this project's local orchestration CLI; the upstream ArtCraft is a Tauri application, and you must not install or impersonate an official CLI with the same name.
Execution and implementation converge in the built-in artcraft-harness skill (installed bundled with the plugin; for standalone installation use npx skills add full-aigc-skills/artcraft-skills --skill artcraft-harness). Set HARNESS_DIR to the directory where that skill is actually loaded (absolute path); this skill's SKILL_DIR is only used to read its own examples/ and references/, and all script execution paths use $HARNESS_DIR/scripts/。
Input and Delivery
The inputs are the user-confirmed task, materials, project or object, output directory, and scope of modification; when an existing project is needed, verify the summary first. Return the actual CLI results, the saved native project, the required derived outputs, and the verification records. Report installation success, the existence of the command directory, and completion of the creative task separately.
First-Time Use and Public Entry Point
Locate the real directory of the current SKILL.md. Currently supports macOS arm64 and Python 3.11+; the base entry point installs the pinned Node and orchestration package; workflow.py installs the required domain skill sources and native CLI according to the task graph, and does not require global Node. When existing task authorization covers the necessary dependencies, run this skill's installer directly and do not create a separate approval process.
Set SKILL_DIR to the directory (absolute path) where this SKILL.md actually loaded by the host is located. User-level installations may be at ~/.agents/skills/artcraft-cli-revise, project-level may be at .agents/skills/artcraft-cli-revise, and plugins may be in its skills/artcraft-cli-revise or the host cache directory; use the actual load path as the standard, do not guess based on the current working directory, and do not randomly choose among duplicate versions after searching. The skill directory and the CLI's user-data installation directory are two separate locations.
: "${SKILL_DIR:?请先设置为本 SKILL.md 的实际所在目录}"
python3 -I -B "$HARNESS_DIR/scripts/bootstrap.py" --runtime-only
python3 -I -B "$HARNESS_DIR/scripts/cli.py" -- --version
python3 -I -B "$HARNESS_DIR/scripts/cli.py" -- --help
CLI argv is after -- , and the native subcommand must come first. Installation parameters go before the separator;--runtime-home can isolate the cache. Stop when locking the artifact digest fails, the installation is corrupted, or the platform is unsupported; do not modify PATH and do not perform floating upgrades. The native help entry point is --help; the launcher's own --help only explains the launch parameters.
Scenario Operations
Verify this scenario's inputs, native project, target object, version, and output boundaries. Follow the scenario guide to select the current command, save an independent checkpoint, then execute; after completion, reopen the native project and check the actual outputs and non-target content.
This project's --help defines run/status/cancel/package/verify-package; semantic planning goes through workflow.py, and the upstream Tauri's account/vendor methods must not be treated as orchestration CLI commands.
Use a new revision and register the source project digest; keep old deliveries and unrelated nodes, and do not increase the original authorization budget.
Native composition and source project revisions use the artcraft-harness skill's scripts/workflow.py; read the workflow contract, and the templates are in this skill's examples. Modify only authorized objects; keep the native project and dependent materials, and for derived-format loss read the exchange report。
Verification and Recovery
A non-zero command exit does not count as completion; the actual saved project, export, dimensions, and media decoding need to be checked. Mark timeout results as unknown, check the original task/project first, and do not automatically replay edits. Perform recovery and packaging according to this skill's references/recovery.md and references/project-package.md respectively; review_ready only indicates technical readiness.
On-demand references and handoff
- Actual command evidence: fixed-version observations, used only as routing and parameter references; real-time results take precedence, and disabled items are not executed.
- Workflow contract: combined operations, native saving, dependency collection, and revision.
- When installation/diagnostics are needed, hand off to artcraft-cli-setup, and hand off full task routing to artcraft-use; when a skill is missing, use
npx skills add full-aigc-skills/artcraft-skills --skill <skill-name>. Do not load other skills via adjacent file paths.
This skill does not provide a fictional login interface; local headless does not require a cloud account. Full GUI, cross-editor fidelity, and creative quality are stated according to actual evidence.
When a finished video needs to be verified through the existing Video Factory, read this skill's public verification handoff. This adaptation preserves NOT_RUN and does not replace creative review or the native project.
Review-driven continuous revision
When continuous rework is needed based on review issues, read the controlled revision guide, use this skill's revision.py to freeze the target/authorization and node command scope, then execute explicit patches. The current package, review, and policy summaries all use previously trusted receipts; do not fabricate human acceptance or observations. The entry point automatically preserves the original project, updates affected nodes, and packages; stop on rounds/budget/stagnation. If the result is unknown, check the original task first, and only explicitly recover the same step.
python3 -I -B "$HARNESS_DIR/scripts/revision.py" step --project "$PROJECT_ROOT" --package "$PACKAGE_ROOT" --package-sha "$PACKAGE_SHA" --review "$REVIEW_ROOT" --review-sha "$REVIEW_SHA" --policy "$REVISION_POLICY" --policy-sha "$POLICY_SHA" --request "$REVISION_REQUEST"
python3 -I -B "$HARNESS_DIR/scripts/revision.py" status --project "$PROJECT_ROOT"
Brand palette mixed rework
This skill includes a five-node example of brand graphics/poster/opening/finished video and standalone icons. Follow this skill's brand palette guide to execute and verify the affected artifacts; the domains required for first-time installation are determined by the fixed dependency lock.
Dynamic transparent sequence handoff
When a mixed task requires transparent animation, full-frame handoff, or downstream updates after a Logo change, use this skill'sdynamic sequence guideand examples/dynamic-brand-campaign.json. Verify all frames, time base, native references, and local rework according to actual receipts; do not substitute the first frame or ordinary JSON for the sequence.
When the result is unknown after saving, follow this skill's references/recovery.md to verify failure.json, the original temporary project, and stop evidence; do not replay the same task, and a failed temporary save is not a successful delivery.
Full domain command handoff
When native operations beyond the templates are needed, read this skill'sfull domain command component, use the included domain_commands.py to query 2646 commands, actual MCP parameters, and hand off the selected domain. Each skill includes four-domain creation/rework examples; unknown is not replayed, and component receipts do not replace DAG native delivery and acceptance.
Native gradients, multiple fills, and source project color-change rework: use the current skill's Vector appearance guide。
Native parenting, transparency expressions, and source project rework: use the current skill's Effect expression guide。
For Photo native adjustment layers, selection masks, and trusted source rework, see local adjustment guide。
When domain GUI commands need to be launched independently, see own desktop handoff。
Mixed task reference Business Scenario Manual, first confirm dependencies and input versions, then execute sub-projects, local rework, and delivery verification.
When installation fails, read First-Use Diagnostics, and use the receipt to locate the setup entry point of the current skill itself; handle installation failures and native invocation failures separately.
For real voiceover recognition and mixed subtitle tasks, read this skill's Mixed ASR Guide / Mixed ASR guide, and execute according to the fixed domain dispatch and persistent model directory; retain dependencies, native projects, and execution evidence separately for planning, rework, and acceptance.
For task identity and rejection details, read according to Task Receipt Instructions ; node summaries do not replace actual execution receipts.
Before reworking mixed posters, covers, and source projects, read Photo Complete Delivery, and distinguish between host-independent plugins and Art-internal fixed dependencies.
For cross-artifact observation with fixed brand and subject references, see this skill's Consistency Review Contract; report acceptance of source candidates and published fixed versions separately.
Runtime Upgrades and Legacy Ledgers
When encountering runtime_upgrade_busy , retain the old runtime, original project, and ledger; do not delete leases or forcibly modify state. First complete or reliably stop the task with the old version, then migrate according to the new version; the old budget marker of read-only status indicates historically untracked. See this skill'sUpgrade Guide。
For validation and mode boundaries of native command execution, see Command Contract Boundaries。
For classification, parameter differences, and rejection boundaries of mode directory candidates, seeMode Directory Usage; Vector desktop/bridge duplicate commands have not yet completed execution qualification and cannot fall back according to the headless directory.