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lumerical-fdtd

Use when connecting Codex to Ansys Lumerical FDTD, probing lumapi or fdtd-solutions.exe, normalizing FDTD solver environments, running LSF CLI sentinels, scripting FDTD object creation, reading monitor or Qanalysis results, handling sampled materials, or repairing FDTD automation failures.

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name lumerical-fdtd description Use when connecting Codex to Ansys Lumerical FDTD, probing lumapi or fdtd-solutions.exe, normalizing FDTD solver environments, running LSF CLI sentinels, scripting FDTD object creation, reading monitor or Qanalysis results, handling sampled materials, or repairing FDTD automation failures. Lumerical FDTD Overview Use this skill to operate Ansys Lumerical FDTD through local Python API sessions or the fdtd-solutions.exe LSF command-line fallback. Keep the scope to solver connection, environment setup, object creation, monitor/source/analysis scripting, result extraction, material data handling, and failure repair. Workflow Detect the operating system first: On Windows PowerShell, run the Python probe directly with py -3 or a chosen Python. On Git Bash for Windows, use scripts/probe_lumerical.sh ; it detects MINGW/MSYS/CYGWIN and chooses py -3 when available. On Linux, use scripts/probe_lumerical.sh ; it chooses python3 and searches Linux FDTD install roots. Decide whether to use Python API or CLI LSF: Prefer Python API when lumapi imports and an FDTD session starts. Use CLI LSF when Python API startup is blocked but fdtd-solutions.exe can run scripts. Load only the needed reference: FDTD Python API, LSF, object creation, monitors, Qanalysis, data extraction, far-field projection, or materials: references/lumerical-fdtd-automation.md . Example profile structure: references/solver-profiles.json . Probe before real work unless the same profile already passed in the current session. Normalize the local solver environment before launching binaries. Run the smallest viable operation first: import check, executable check, session start, or CLI sentinel. Store raw stdout/stderr, generated scripts, result files, and probe JSON near the caller's job artifacts, not inside this skill. If a solver call fails, classify the signature, propose the smallest patch, retry once when safe, then report the exact command and artifacts. Quick Commands $skill = "C:\path\to\lumerical-fdtd" $out = ".\solver_probe_out\lumerical" py -3 "$skill\scripts\probe_lumerical.py" --dry-run --out-dir "$out" py -3 "$skill\scripts\probe_lumerical.py" --deep --out-dir "$out" py -3 "$skill\scripts\probe_lumerical.py" --cli --deep --out-dir "$out-cli" If py -3 is not the right interpreter, use a user-selected Python environment: conda run -n <env> python "$skill\scripts\probe_lumerical.py" --dry-run --out-dir "$out" Git Bash or Linux: skill= "/path/to/lumerical-fdtd" out= "./solver_probe_out/lumerical" bash " $skill /scripts/probe_lumerical.sh" --dry-run --out-dir " $out " bash " $skill /scripts/probe_lumerical.sh" --deep --out-dir " $out " bash " $skill /scripts/probe_lumerical.sh" --cli --deep --out-dir " $out -cli" Defaults Prefer lumapi.FDTD() after adding the local api/python directory to sys.path . Set ANSYSLMD_LICENSE_FILE when session startup fails with license/session errors. Prepend the FDTD bin and licensingclient/winx64 directories to PATH . Keep fdtd-solutions.exe -run <script.lsf> as a CLI fallback. Use .txt as the safe LSF sentinel/export extension, then convert to JSON in Python if needed. Common Mistakes Do not edit files inside the solver installation directory. Do not assume a normal python command exists on Windows; prefer the discovered or user-specified Python. Do not trust old solver syntax without a local probe. Do not treat a solver exit code as enough; verify the expected sentinel, monitor data, or exported file exists. Do not add unrelated solver-family guidance to this FDTD-only skill.
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
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exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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