This skill handles first-time installation, digest verification, version checking, and missing runtime troubleshooting. Handoff with skills in the same package is by name; installing this skill alone is sufficient for use, and it does not read sibling directories. It invokes the fixed official effectcraft-cli and preserves native editing projects.
Inputs and Deliverables
Inputs are the user-confirmed task, assets, project or object, output directory, and scope of modification; when an existing project is needed, verify its digest first. Return the actual CLI results, the saved native project, any required derived outputs, and verification records. Report installation success, command directory existence, and creative task completion separately.
Default Managed Entry Point
Execution implementation converges on the built-in effectcraft-harness skill (installed bundled with the plugin; for standalone installation use npx skills add full-aigc-skills/effectcraft-skills --skill effectcraft-harness). Set HARNESS_DIR to the directory where that skill is actually loaded (absolute path); this skill's SKILL_DIR is used only to read its own examples/ and references/。
Set from the skill directory actually loaded by the host SKILL_DIR。Creative writing defaults to using launch.sh / launch.ps1, automatically preparing a fixed Python and EffectCraft within the user directory, without changing the global PATH. The raw Python/CLI examples below are retained for compatibility and diagnostic purposes and must not bypass the task recovery ledger. For the complete operating contract, see Task Control, Evaluation, and Revision。
/bin/sh "$HARNESS_DIR/scripts/launch.sh" plan --mode workflow --plan PLAN.json --output /absolute/new-result
/bin/sh "$HARNESS_DIR/scripts/launch.sh" run --mode workflow --plan PLAN.json --output /absolute/new-result
Windows PowerShell：& "$HARNESS_DIR/scripts/launch.ps1" run --mode workflow --plan PLAN.json --output "C:\Users\me\result". The native command plan appends --mode commands; for your own desktop session use --mode desktop. After delivery, you must review and actually view the media; report acceptable only when both technical verification and creative evaluation pass, and keep user acceptance status separately. When automatic revision is needed, declare it in the initial plan revisionScope; by default at most 2 rounds, with parent and child tasks sharing 30 minutes. For unknown tasks, only inspect/reconcile; do not redo with a different task ID.
First Use and Public Entry Point
Locate the real directory of the current SKILL.md. Native artifacts cover macOS arm64/x86_64, Windows x86/x64/arm64, and Linux x86_64/aarch64; no preinstalled Python is required; the fixed CLI is installed to the user data directory. When an existing task authorization covers the necessary dependencies, run this skill's installer directly without creating a separate approval process.
Set SKILL_DIR to the directory containing the actually loaded SKILL.md in the host (absolute path). User-level installations may be located at ~/.agents/skills/effectcraft-cli-setup, project-level ones may be located at .agents/skills/effectcraft-cli-setup, and plugins may be located in their skills/effectcraft-cli-setup or in the host cache directory; use the actual load path as the standard, do not guess based on the current working directory, and do not arbitrarily select a duplicate version after searching. The skill directory and the CLI user data installation directory are two separate locations.
: "${SKILL_DIR:?请先设置为本 SKILL.md 的实际所在目录}"
python3 -I -B "$HARNESS_DIR/scripts/bootstrap.py"
python3 -I -B "$HARNESS_DIR/scripts/cli.py" -- --version
python3 -I -B "$HARNESS_DIR/scripts/cli.py" -- commands --json
CLI argv follows -- ; the native subcommand must come first. Installation parameters go before the separator;--runtime-home can isolate the cache. Stop when locked artifact digest verification fails, the installation is corrupted, or the platform is unsupported; do not change PATH and do not perform floating upgrades. The native help entry point is --help; the launcher's own --help only explains startup parameters.
Scenario Operations
First read the system/architecture, Python version, and the user's existing authorization; run this skill's bootstrap.py. Verify the executable path, digest, and version in the JSON receipt; do not rely on shell PATH. Repeated calls reuse the fixed installation; on failure, stop and record the specific error.
commands --filter <关键词> --json verify the parameters; use props/get/set for property reads and writes, and for commands use exec <id> --params <JSON> or the paired run <id> <JSON> ...; use --save-as to preserve the new project.
Do not modify PATH or use sudo; if a version is corrupted, keep it and report an error, do not auto-upgrade.
Native composition and source project revision use the effectcraft-harness skill's scripts/workflow.py(reused internally by the managed launcher); read the workflow contract, the template is within this skill's examples. Modify only authorized targets, preserve native projects and dependency assets, read interchange reports。
Verification and recovery
A non-zero command exit does not count as completion; it is necessary to inspect the actual saved project, exports, dimensions, and media decoding. Timed-out results are marked unknown, check the original task/project first, and do not automatically replay edits. The existing native workflow supports save-as revision; refuse to overwrite when the corresponding project summary does not match.
On-demand reference and handoff
- Actual command evidence: fixed-version observations, used only as routing and parameter reference; real-time results take priority, disabled items are not executed.
- Workflow contract: composition operations, native saving, dependency collection, and revision.
- Hand off to effectcraft-cli-setupwhen installation/diagnostics are needed, hand off complete task routing to effectcraft-use; when the skill is missing use
npx skills add full-aigc-skills/effectcraft-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.
Full native command usage
The query examples below require an existing Python; if no interpreter is prepared, first diagnose with the managed launcher doctor . Write examples automatically prepare isolated dependencies via the launcher; on Windows use & "$HARNESS_DIR/scripts/launch.ps1" to replace /bin/sh "$HARNESS_DIR/scripts/launch.sh", keeping the same mode and parameters. The current skill includes a complete directory parameter description and same-session entry, not restricted by the creative template whitelist. Read the full usage guide, query on demand the command reference; each instruction has a skill route, prior observation, and acceptance status.
python3 -I -B "$HARNESS_DIR/scripts/commands.py" list --filter QUERY
python3 -I -B "$HARNESS_DIR/scripts/commands.py" describe COMMAND_ID
/bin/sh "$HARNESS_DIR/scripts/launch.sh" run --mode commands --plan "$SKILL_DIR/examples/commands-advanced.json" --output /absolute/new-command-result
/bin/sh "$HARNESS_DIR/scripts/launch.sh" run --mode desktop --plan "$SKILL_DIR/examples/desktop-first-use.json" --output /absolute/new-desktop-result
Before executing a new entry, check the real registry and current executable status, retain return value references and step-by-step receipts; semantic errors or timeouts must not be passed off as success. Directory coverage and direct native use do not mean all instructions, GUI, deliverables, or Art orchestration have been accepted.
For the full workflow command gateway see usage instructions. For the fixed CLI's version and artifact summary, refer to the effectcraft-harness skill's scripts/runtime.lock.json ; the skill package version is based on the corresponding release tag. Independent installation re-verification and full command-by-command acceptance are recorded separately, and release is not a substitute for acceptance.
Parent-child layers, property expressions, dynamic previews, and source project rework: use the current skill's expression parenting guide。
For GUI tasks, you can first use this skill's built-in fixed desktop installation; installation, launch, and actual GUI editing are verified separately.
Business tasks start from the scene operation manual , executed by input check, template adaptation, native delivery, local rework, and result verification.
When installation fails, read first-use diagnostics, and locate the current skill's own setup entry based on the receipt; handle installation failure and native invocation failure separately.
For related creative tasks read shot tracking scene, verify native parameters, object context, local rework, and delivery boundaries.
Same-target execution protection
Before invoking the public workflow, read this skill's execution registration and interruption handling. In cases of contention or unknown state, do not delete the registration, automatically replay, or switch targets to bypass verification.