12,528 skills found · Page 157 of 418
Ar9av / hermes-history-ingestIngest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining ~/.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.
Ar9av / openclaw-history-ingestIngest OpenClaw session/history data into Obsidian as distilled knowledge. Use for importing or mining ~/.openclaw sessions, memory files, or logs; use wiki-agent for targeted topic-only cross-agent recall.
Ar9av / tag-taxonomyApply and maintain the wiki's controlled tag vocabulary. Use for choosing, normalizing, auditing, or extending tags when creating or updating wiki pages; consult the taxonomy before assigning tags.
Ar9av / wiki-digestProduce a day/week/month knowledge digest summarizing what was learned, updated, and connected in the wiki. Use for readable recent-learning summaries; wiki-status reports source and ingestion state instead.
Ar9av / wiki-rebuildArchive and rebuild wiki knowledge from source, or restore a prior archive. Use for full restart/recovery when incremental repair is inappropriate; this is broader and more destructive than ordinary update or lint.
Ar9av / wiki-stage-commitReview staged wiki writes and promote accepted pages to final locations when WIKI_STAGED_WRITES is enabled. Use for staging approval/commit; rejected pages return to _raw/ for editing.
Ar9av / wiki-synthesizeFind recurring concept combinations across the wiki that lack an explicit synthesis page, then create cross-cutting synthesis pages. Use for knowledge synthesis after the vault has accumulated enough material.
Ar9av / wiki-exportExport the Obsidian wiki graph to JSON, GraphML, Neo4j Cypher, Postgres/SQL, HTML, or OKF bundles
Ar9av / wiki-updateSync knowledge from the current project into the Obsidian wiki
Ar9av / memory-bridgeBrowse or compare wiki knowledge by originating AI tool. Use for cross-tool memory questions, tool-specific knowledge, or gap/diff analysis between Codex, Claude, Hermes, and other agents.
Ar9av / obsidian-layout-adjustmentAdjust the user's Obsidian visual layout with CSS snippets. Use for restyling tabs, sidebars, note surfaces, properties, backlinks, graph or file-explorer UI, or diagnosing CSS changes that did not take effect.
Ar9av / wiki-narrateTurn a wiki topic into a cited Markdown briefing, plain-language explanation, or progressive lecture. Use this skill for topic-based briefing, explanation, and lecture requests that must stay within the evidence compiled in an Obsidian vault.
Ar9av / impl-validatorIndependently check whether an implementation matches its stated goal and return PASS/WARN/FAIL with actionable issues. Use for second-opinion validation of an implementation or generated output.
Ar9av / session-brainBuild or refresh a browser-viewable topic graph over Claude session history using local clustering. Use for mapping or clustering sessions, recent or stale topic analysis, or rebuilding/showing the session graph. Unlike wiki-history-ingest, it indexes raw sessions and never writes to the vault.
Ar9av / session-searchSearch the session-brain graph for a past agent session by topic and load the winning transcript into the current conversation. Use for finding which session handled X, when Y was last worked on, or whether this was done before. Read-only; requires a session-brain graph.
Ar9av / cross-linkerFind and add missing cross-references between wiki pages
Ar9av / code-understandMap the load-bearing files, symbols, callers, and dependencies of an unfamiliar codebase before making changes. Use for architecture orientation, impact analysis, what-would-break questions, or finding callers. Uses CodeGraph when available and a dependency-free builtin fallback.
Ar9av / vault-skill-factoryCreate a reviewable Agent Skill package from mature curated wiki pages
Ar9av / llm-wikiExplain and apply the foundational LLM Wiki architecture and knowledge-management strategy. Use for setup, architecture, schema, or organization decisions; operational ingest/query/lint work uses dedicated skills.
Ar9av / wiki-context-packProduce a token-bounded, citation-ready context slice from an existing Obsidian vault for a downstream agent or task. Use for "/wiki-context-pack", "use my vault as context", "context slice for X", "pack the wiki for my agent", or "bounded context for Y".
Ar9av / wiki-switchList, create, or switch named Obsidian wiki vault profiles under the global config directory
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling, prediction, training, classification, regression, clustering, deep learning, neural network, model evaluation, feature engineering, hyperparameter tuni…
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design
Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence.
Comprehensive citation management for academic research. Resolve bibliographic identifiers, extract accurate metadata, validate citations, deduplicate references, and generate properly formatted BibTeX entries.
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms).
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
Access ClinPGx pharmacogenomics data (successor to PharmGKB). Query gene-drug interactions, CPIC guidelines, allele functions, for precision medicine and genotype-guided dosing decisions.
Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.