with one click
indexion-skills
indexion-skills contains 10 collected skills from trkbt10, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
README construction — initialize template structure, generate per-package READMEs from doc comments, plan writing tasks, assemble root README from docs/ and package READMEs via doc.json config, and verify edits with `plan drift`.
Detect and review name/content drift in code using `indexion identity audit`, then plan verified renames, moves, folder changes, or splits.
Generate and use a pre-edit structure brief so coding agents learn likely owners, consumer surfaces, and unsafe edit locations before implementing.
Generate SDD requirements from RFCs/specs and quantitatively verify implementation conformance. spec draft → spec align → spec verify → automated validation loop with codex/claude. Operate spec-to-impl drift gates as CI checks.
Documentation analysis — assess coverage, detect code-to-doc drift with plan reconcile, visualize dependencies with doc graph. Answers "what needs docs?" and "are docs still accurate?"
Project wiki lifecycle — create pages, track source changes with ingest, update stale pages, lint structural integrity, detect code-to-doc drift with reconcile, and manage search indexes. A runbook for navigating and maintaining the wiki as an agent.
Debug and inspect KGF specs — view tokenization results, parse trees, and extracted edges from source files. Use when adding/fixing language support or when indexion's analysis output looks wrong.
After writing code, detect and clean up duplication at three levels — copy-paste blocks, cross-package shared code, unnecessary wrappers, and concept-level SoT violations. Detect with indexion, fix, and verify.
"Where is this function?" "Any O(n^2) hotspots?" "Which files are similar?" "Find code that does X" — pick the right indexion command for your search intent. Covers token patterns, structural queries, semantic similarity, file-level exploration, and cached index lifecycle.
Split text into contextual chunks for RAG/embedding pipelines. Document segmentation and section extraction using window, tfidf, punctuation, or hybrid strategies chosen by intent.