This skill is responsible for importing images, videos, vectors, or PSD assets and registering dependencies. It hands off to skills in the same package by name, can be used when installed alone, and does not read sibling directories. It invokes the fixed official effectcraft-cli and preserves the native editing project.
Input and Delivery
The inputs are the user-confirmed task, assets, project or object, output directory, and modification scope; when an existing project is needed, verify the summary first. Return the actual CLI results, the saved native project, required derived outputs, and verification records. Report installation success, command directory existence, and creative task completion separately.
Default Managed Entry Point
Execution implementation converges in 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 only used to read its own examples/ and references/。
Set SKILL_DIR。from the skill directory actually loaded by the host. Creative writing uses launch.sh / launch.ps1by default, 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 diagnostics and must not bypass the task recovery ledger. See the complete operation contract in 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：& "$HARNESS_DIR/scripts/launch.ps1" run --mode workflow --plan PLAN.json --output "C:\Users\me\result".
The native command plan appends --mode commands; own desktop sessions use --mode desktop. After delivery, you must review and actually view the media; only report acceptance-ready when both technical validation and creative evaluation pass; user acceptance status is kept separately. When automatic revision is needed, declare it in the first plan: revisionScope; by default a maximum of 2 rounds, with parent and child tasks sharing 30 minutes. Unknown tasks are only inspected/reconciled; do not redo with a changed task ID.
First Use and Public Entry Point
Locate the real directory of the current SKILL.md. Native artifacts cover macOS arm64/x86_64, Windows x86/x64/arm64, and Linux x86_64/aarch64; no preinstalled Python is required; the fixed CLI installs into the user data directory. When an existing task authorization covers the necessary dependencies, directly execute this skill's installer without creating a separate approval process.
Set SKILL_DIR to the directory (absolute path) where this SKILL.md actually loaded by the host is located. User-level installations may be in ~/.agents/skills/effectcraft-cli-footage, project-level ones may be in .agents/skills/effectcraft-cli-footage, and plugins may be in their skills/effectcraft-cli-footage or host cache directory; use the actual loaded path as the standard, do not guess based on the current working directory, and do not search and arbitrarily choose a duplicate version. The skill directory and the CLI's user data installation directory are two independent locations.
: "${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
After the CLI argv is -- , 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 change PATH and do not perform floating upgrades. The native help entry is --help; the launcher's own --help only explains startup parameters.
Scenario Operations
Verify this scenario's inputs, native project, target object, version, and output boundaries. Select the current command according to Scenario Guide , save an independent checkpoint, then execute; after completion, reopen the native project and check the actual outputs and non-target content.
commands --filter <关键词> --json to verify parameters; use props/get/set for property reading and writing, and use exec <id> --params <JSON> or paired run <id> <JSON> ...; use --save-as to preserve the new project.
Inspect the actual imported structure; PSD/SVG layer, font, and effect fidelity must be verified separately.
Native compositing and source project revision use the effectcraft-harness skill's scripts/workflow.py(reused internally by the managed launcher); read workflow contract, with templates in this skill's examples. Modify only authorized objects, preserve the native project and dependency assets, and read the derived-format loss exchange report。
Verification and recovery
A non-zero command exit does not count as completion; the real saved project, exports, dimensions, and media decoding must be inspected. Timeout results are marked unknown; check the original task/project first, and do not automatically replay edits. The existing native workflow supports saving revisions; refuse to overwrite when the corresponding project summary does not match.
On-demand references and handoff
- Actual command evidence: fixed-version observations, for routing and parameter reference only; real-time results take precedence, and disabled items are not executed.
- Workflow contract: compositing operations, native saving, dependency collection, and revisions.
- Hand off to effectcraft-cli-setupwhen installation/diagnostics are needed, and hand off full 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" instead of /bin/sh "$HARNESS_DIR/scripts/launch.sh", keeping the same mode and parameters. The current skill includes full directory parameter descriptions and same-session entry points, and is not limited by the creative template whitelist. Read full usage guide, and query as needed command reference; each instruction has a skill route, prerequisite observations, and acceptance status.
python3 -I -B "$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 point, check the real registry and current executable status, and 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 commands, GUI, delivery, or Art orchestration have been accepted.
See usage instructionsfor the full workflow command gateway. For the fixed CLI's version and artifact digests, 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; a release does not replace acceptance.
For parent-child layers, property expressions, dynamic previews, and source project rework: use the current skill's expression parenting guide。
GUI tasks can first use this skill's bundled fixed desktop installation; installation, startup, and actual GUI editing are verified separately.
Full attribution commands are listed by command family in the categorized usage list, and each item can be viewed via this skill's commands.py describe ; the general CLI list also retains all commands not assigned to specialized skills.
Start business tasks from the scenario operations manual and execute by input checks, template adaptation, native delivery, local rework, and result verification.
If installation fails, read first-use diagnostics, locate the setup entry point of the current skill itself based on the receipt; handle installation failures and native call failures separately.
The relevant authoring task reads shot tracking scenario, and verifies native parameters, object context, local rework, and delivery boundaries.
Same-target execution protection
Before calling a public workflow, read this skill's execution registration and interruption handling. In case of contention or an unknown state, do not delete the registration, automatically replay, or switch targets to bypass verification.