بنقرة واحدة
llm-self-model-capstone
يحتوي llm-self-model-capstone على 17 من skills المجمعة من codewizard-dt، مع تغطية مهنية على مستوى المستودع وصفحات skill داخل الموقع.
Skills في هذا المستودع
Update the ai-sdd framework binary + skills to the latest release — an apply-on-confirm wrapper that runs `ai-sdd update --check`, surfaces the current-to-latest version transition, and (only on explicit confirmation) runs `ai-sdd update` and lands a standalone reseed commit. Agent-agnostic (claude-code or codex). Use when a teammate wants to update / upgrade ai-sdd, sees the update-available notice, or invokes `/ai-sdd-update`.
Stand up (or refresh) an ai-sdd factory for a repository so any coding agent — claude-code, codex, … — can drive it. Discovers the repo's conventions, scaffolds the .ai-sdd/ home, authors worker skills + schemas, compiles the deterministic gates, and wires provider-neutral skill surfacing (AGENTS.md + per-agent symlinks). Use when onboarding a repo to ai-sdd or re-bootstrapping after the codebase/conventions drift.
Drive a software-factory run by dispatching a sub-agent per worker — the deterministic `ai-sdd` engine plans (next), a fresh sub-agent does each worker's work via its skill, the engine gates and advances (submit), and each completed slice is committed. Agent-agnostic (claude-code or codex). Use when asked to run, drive, continue, or advance a factory run / pipeline / orchestration, or when the user mentions `ai-sdd next` / `ai-sdd submit`.
Print the diagram-driven ai-sdd workflow cheatsheet — the canonical command sequence (bootstrap → plan → run, validate/next/submit/status) that travels with the binary. Use when a user forgets which command comes next, asks "how do I drive a run / what's the workflow", or needs the command reference without leaving the repo.
Turn a complete PROGRAM brief into a runnable master plan — a decision-closed program requirements doc and a master orchestration graph whose nodes are whole sub-features (kind:pipeline) sequenced by milestone validation gates with owners. The program tier above ai-sdd-plan. Requires a real program brief (refuses a one-liner) and human approval of the program requirements draft before emitting the graph. Use when planning a multi-feature, multi-person project in a bootstrapped repo (run ai-sdd-bootstrap first); each sub-feature is then planned with ai-sdd-plan. Re-run on an existing program to amend it in place (create-vs-amend is auto-detected from disk): append sub-features/milestones and rewire pending nodes; a started node (completed or in-flight) is immutable and corrected forward with a downstream `<node>-revert` node.
Turn a complete feature brief into a runnable plan for a bootstrapped repo — a decision-closed requirements doc and an orchestration graph (slices + depends_on) the engine executes. Requires a real brief (refuses a bare one-liner — asks for one) and human approval of the requirements draft before generating slices. The planning layer between an idea and ai-sdd-run. Use when starting a new feature in a repo that already has a .ai-sdd/ (run ai-sdd-bootstrap first). Re-run on an existing feature to amend it in place (create-vs-amend is auto-detected from disk): append slices and rewire pending ones; a started slice (completed or in-flight) is immutable and corrected forward with a downstream `<slice>-revert` slice.
Implement an ai-sdd feature plan within this repo's conventions and record the acceptance ids covered.
Produce a decision-closed ai-sdd feature plan with a verifiable acceptance checklist, grounded in this repo's conventions and the frozen contracts.
Review an ai-sdd changeset against the feature plan and this repo's conventions, and emit a blocking verdict artifact.
Compile a factory Schema (.ai-sdd/schemas/*.schema.yaml) into the deterministic CheckSpecs the engine runs, and wire them onto the worker that produces that schema. Bootstrap-time authoring — the output is committed and frozen, not regenerated per run. Use when a schema is added or changed, or while bootstrapping a repo's factory.
Deep research on a topic using codebase analysis, library docs, and web search — writes the report plus its primary sources to raw/research/<slug>/
Cleanup tool — sweep for work items with terminal status that were not auto-archived by their originating skill, and move them to archive/
Process a source from raw/ into the wiki — write a summary page, update affected entity and concept pages, and record the ingest in the index and log
Health-check the wiki — find contradictions, stale claims, orphan pages, missing concept pages, missing cross-references, and never-ingested raw sources; fix only with approval
Answer a question from the wiki — locate pages via the index, synthesize a cited answer, and offer to file valuable answers back as new wiki pages
Rotate wiki/log.md into a timestamped archive file when it grows past ~500 lines; create a fresh log.md with an archive-pointer header
One-shot wiki cleanup — runs lint, archives terminal items across all families, and rotates the log if overgrown, in sequence with user confirmation at each phase