This skill is responsible for creating or modifying cameras, lights, and materials in an existing composition, and for verifying layer 3D switches and view prerequisites. 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.
Inputs and Deliverables
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, any required derived outputs, and verification records. Report installation success, command directory existence, and creative task completion separately.
Default Managed Entry Point
Execution implementation is converged into 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 writes default to using launch.sh / launch.ps1, automatically preparing the 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 operation 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：& "$HARNESS_DIR/scripts/launch.ps1" run --mode workflow --plan PLAN.json --output "C:\Users\me\result".
Native command plan append --mode commands, own desktop session uses --mode desktop. After delivery, you must review and actually view the media; only report as acceptable when both technical verification and creative evaluation pass, and the user acceptance status is retained independently. When automatic revision is needed, declare revisionScopein the initial plan; by default, at most 2 rounds, with parent and child tasks sharing 30 minutes. For unknown tasks, only inspect/reconcile; do not redo with a different task ID.
First Use and Public Entry Point
Locate the real directory of the current SKILL.md. Native artifacts cover macOS arm64/x86_64, Windows x86/x64/arm64, and Linux x86_64/aarch64; no preinstalled Python is required; the fixed CLI is installed to the user data directory. When existing task authorization covers the necessary dependencies, execute this skill's installer directly without creating a separate approval process.
Set SKILL_DIR to the directory (absolute path) containing this SKILL.md actually loaded by the host. User-level installations may be located in ~/.agents/skills/effectcraft-cli-camera, project-level ones may be located in .agents/skills/effectcraft-cli-camera, and plugins may be located in their skills/effectcraft-cli-camera or the host cache directory; rely on the actual load path, do not guess based on the current working directory, and do not search and then arbitrarily choose a duplicate version. The skill directory and the CLI user data installation directory are two independent locations.
: "${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
In CLI argv, after -- , the native subcommand must come first. Installation arguments go before the delimiter;--runtime-home can isolate the cache. Stop when locked artifact digest verification 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 startup arguments.
Scene Operations
First read this skill's camera scene guide, and select shots, lights, materials, and views by command category; self-contained plans are within this skill's examples.
Verify the input, native project, target objects, version, and output boundaries for this scenario. 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 output and non-target content.
commands --filter <关键词> --json verify the parameters; use props/get/set for property reads and writes, and use exec <id> --params <JSON> or the paired run <id> <JSON> ...for commands; use --save-as to preserve a new project.
First verify the layer 3D toggle, camera view, and the corresponding render support; the mere existence of a parameter does not prove a visual result.
For native composition and source project revisions, use the effectcraft-harness skill's scripts/workflow.py(reused internally by the managed launcher); read the workflow contract, and the templates are in this skill's examples. Modify only authorized objects, preserve the native project and dependency assets, and for derivative format loss read the exchange report。
Verification and Recovery
A non-zero command exit does not count as completion; real saved projects, exports, dimensions, and media decoding need to be inspected. Mark timeout results as unknown, first check the original task/project, and do not automatically replay edits. Existing native workflows support save-as revisions; refuse to overwrite when the corresponding project summary does not match.
On-demand References and Handoff
- Actual command evidence: fixed-version observations, used only as routing and parameter references; live results take precedence, and disabled items are not executed.
- Workflow contract: composition operations, native save, dependency collection, and revisions.
- When installation/diagnostics are needed, hand off to effectcraft-cli-setup, and for full task routing hand off 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. State full GUI, cross-editor fidelity, and creative quality according to actual evidence.
Full Native Command Usage
The query examples below require an existing Python; if no interpreter is prepared, first use the managed launcher doctor to diagnose. The write examples automatically prepare isolated dependencies via the launcher; on Windows use & "$HARNESS_DIR/scripts/launch.ps1" instead of /bin/sh "$HARNESS_DIR/scripts/launch.sh", keeping the same mode and parameters. The current skill includes full catalog parameter descriptions and same-session entry points, and is not limited by the creative template whitelist. Read the full usage guide, and query the command referenceas needed; each instruction has a skill route, prerequisite observations, and acceptance status.
python3 -I -B "$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 actual registry and current executable status, and retain return value references and step-by-step receipts; do not pass off semantic errors or timeouts as success. Catalog coverage and direct native usage do not mean all instructions, GUI, delivery, or Art orchestration have been accepted.
For the full workflow command gateway, see Usage Instructions. The version and artifact digests of the fixed CLI are subject to the effectcraft-harness skill's scripts/runtime.lock.json ; the skill package version is subject to the corresponding release tag. Independent installation re-verification and full command-by-command acceptance are recorded separately, and 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。
For GUI tasks, you can first use this skill's built-in 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, each item's parameters can be viewed through this skill's commands.py describe ; the general CLI manifest also retains all commands not assigned to specialized skills.
Business tasks start from Scenario Operation Manual , and are executed in the order of input checking, template adaptation, native delivery, partial rework, and result verification.
When installation fails, read First-Use Diagnostics, and use the receipt to locate the current skill's own setup entry point; handle installation failures and native invocation failures separately.
For related creation tasks, read Shot Tracking Scenario, and verify native parameters, object context, partial rework, and delivery boundaries.
Same-Target Execution Protection
Before invoking a public workflow, read this skill's Execution Registration and Interruption Handling. In cases of contention or unknown status, do not delete the registration, automatically replay, or switch targets to bypass verification.