src/autoskillit/skills_extended/migrate-recipes/SKILL.md
Apply versioned migration notes to an AutoSkillit recipe. Use when user confirms migration, called by agent or autoskillit migrate CLI, or invoked directly.
npx skillsauth add talont-org/autoskillit migrate-recipesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Apply versioned migration notes to an AutoSkillit recipe.
autoskillit migrate CLI command via run_skillThe orchestrator provides all context in the prompt:
script_path: Absolute path to the script filescript_content: Current raw YAML of the scriptmigration_notes: YAML block of all applicable migration notestarget_version: Version to stamp after successful migrationNEVER:
ALWAYS:
detect:
tool: Match steps with this tool valueskill_pattern: Match steps whose skill_command in with: contains this substringmissing_field: The field that should be added if absent/autoskillit:write-recipe in edit mode:
/autoskillit:write-recipe via the Skill toolinstruction text and before/after examplesvalidate_recipeautoskillit_version is set to the target_version{{AUTOSKILLIT_TEMP}}/migrations/{script_name}.yamlIf all 3 retry attempts are exhausted without a valid result, BEFORE declaring failure you MUST persist the failure record:
run_python: callable: autoskillit.migration.store.record_from_skill args: name: {recipe stem, e.g. "my-pipeline"} file_path: {absolute path received as script_path argument} file_type: recipe error: {description of last validation error} retries_attempted: 3
After recording, output a clear failure summary and stop.
development
Generate YAML recipes for .autoskillit/recipes/. Use when user says "make script skill", "generate script", "script a workflow", "write a script", "create a script", "new recipe", "write a pipeline", or when loaded by other skills for script formatting.
data-ai
Create Uncertainty Representation visualization planning spec showing error bar definitions, distribution-aware alternatives, and multi-seed variance protocols. Statistical lens answering "How is uncertainty honestly represented?"
data-ai
Create Temporal Dynamics visualization planning spec showing axis scaling (linear vs log), smoothing disclosure, epoch/step alignment, run aggregation (mean + variance bands), early-stopping markers, and wall-clock vs step-count x-axis. Temporal lens answering "Are training dynamics shown clearly and honestly?"
data-ai
Create Narrative Story Arc visualization planning spec showing visual consistency across the report (same color = same model everywhere), logical figure progression, redundant figure detection, and narrative dependency between figures. Narrative lens answering "Do the figures tell a coherent story across the report?"