tilmon-engineering-claude-skills

Plugin tilmon-engineering-claude-skills from marketplace cascade-data-analytics in joshuarweaver/cascade-data-analytics. Commands read from the repo's manifest — 1 month ago.

Skills (32)

• analyze-branch

  Use when analyzing another branch's iteration journals to extract findings, decisions, and insights from divergent work

• branch-status

  Use when user wants detailed status report for single autonomy branch including iteration timeline and metrics progression

• checkpoint-iteration

  Use when saving current iteration progress mid-conversation, before context compaction, or at interim pause points

• compare-branches

  Use when user wants to compare two autonomy branches to see different approaches, metrics, and outcomes

• create-goal

  Use when setting up a new open-ended goal for autonomy tracking, before starting the first iteration

• end-iteration

  Use when concluding work on an open-ended goal to write iteration journal entry documenting work performed, decisions made, and state changes

• fork-iteration

  Use when user wants to create new autonomy branch from current commit or specific past iteration

• fork-worktree

  Use when user wants to create new autonomy branch with dedicated worktree for parallel agent workflows

• list-branches

  Use when user wants to inventory autonomy branches with custom sorting, grouping, or filtering

• list-worktrees

  Use when user wants to see all autonomy worktrees with their status

• remove-worktree

  Use when user wants to safely remove an autonomy worktree while preserving the branch

• review-progress

  Use when user wants to assess progress toward an open-ended goal by reading and summarizing all iteration journals

• slime

  Use when user wants to set up slime mold exploration strategy with parallel autonomy branches for genetic algorithm approach to problem-solving

• start-iteration

  Use when beginning a new conversation to work on an open-ended goal, loading context from previous iterations through iteration journals

• conway-method

  Use when working in a project that has a `.agents/` directory or when the user asks about Conway Architecture, the conway-architecture plugin, domain agents, owned_paths enforcement, or how to coordinate a persistent subagent team that shadows the application's architecture

• cleaning-data

  Systematic data quality remediation - detect duplicates/outliers/inconsistencies, design cleaning strategy, execute transformations, verify results (component skill for DataPeeker analysis sessions)

• comparative-analysis

  Systematic comparison of segments, cohorts, or time periods - ensure fair apples-to-apples comparisons, identify meaningful differences, explain WHY differences exist

• creating-visualizations

  Component skill for creating effective visualizations (terminal-based and image-based) in DataPeeker analysis sessions

• detect-foreign-keys

  Identify foreign key relationships between tables using heuristics, value overlap analysis, and referential integrity checks

• exploratory-analysis

  Systematic exploratory data analysis process - discover patterns in unfamiliar data, identify meaningful insights, formulate specific questions for deeper investigation

• guided-investigation

  Systematic process for investigating open-ended questions - decompose vague questions into specific sub-questions, map to data, investigate incrementally, synthesize findings

• hypothesis-testing

  Rigorous hypothesis testing process for data analysis - formulate hypotheses before looking at data, design tests, analyze systematically, interpret with skepticism

• importing-data

  Systematic CSV import process - discover structure, design schema, standardize formats, import to database, detect quality issues (component skill for DataPeeker analysis sessions)

• interpreting-results

  Component skill for systematic result interpretation with intellectual honesty in DataPeeker analysis sessions

• marketing-experimentation

  Systematic marketing experimentation process - discover concepts, generate hypotheses, coordinate multiple experiments, synthesize results, generate next-iteration ideas through rigorous validation cycles

• presenting-data

  Component skill for creating compelling data-driven presentations and whitepapers using marp and pandoc with proper citations and reproducibility

• qualitative-research

  Use when conducting customer discovery interviews, user research, surveys, focus groups, or observational research requiring rigorous analysis - provides systematic 6-phase framework with mandatory bias prevention (reflexivity, intercoder reliability, disconfirming evidence search) and reproducible

• understanding-data

  Component skill for systematic data profiling and exploration in DataPeeker analysis sessions

• using-sqlite

  Use when working with SQLite databases in DataPeeker analysis sessions - querying data, importing CSVs, exploring schemas, formatting output, or optimizing performance. Provides task-oriented guidance for effective SQLite CLI usage in data analysis workflows.

• writing-queries

  Component skill for systematic SQL query development in DataPeeker analysis sessions

• using-ost-framework

  Use when reading or writing OST (Outcome / Strategy / Tactic) graph data in the `agents` TypeDB database - covers the falsifiability rubric, the three-layer discipline, ID conventions, lifecycle transitions, and the structured Task fields that replace generic descriptions

• using-typedb

  Use when interacting with a TypeDB 3.x database via the typedb MCP tools (typedb-query, typedb-database_schema, etc.) - covers schema-first workflow, transaction types, TypeQL 3.x syntax (which differs materially from 2.x), and the most common failure modes

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