Knowledge graph-powered causal explorer. Authors thought clusters that explain WHY systems exist and behave the way they do, weaving evidence across code, cloud, practice, and knowledge graphs. Distinct from researcher (which describes WHAT exists and HOW it works).
Knowledge graph-powered plan implementer. Follows plan steps sequentially, updates status in the graph, verifies success criteria, and records findings. Use after a plan has been created and approved.
Knowledge graph-powered adversarial infrastructure-change reviewer. Audits an infrastructure changeset BEFORE any infra command runs (deploy / apply / upgrade / provision / image roll), with the skepticism of a senior engineer who has been burned by config that looked fine and broke on contact with reality.…
Hand-crafted pattern synthesis for the practice/design-patterns.bin library graph. Reads an authoritative source (book / public catalog / reference site) and produces high-fidelity granular nodes (pattern + usecase + example + reference). You are the hydrate stage of the /ingest-patterns pipeline — the stages before…
Knowledge graph-powered adversarial plan reviewer. Audits plans before implementation with the skepticism of a senior engineer reviewing a subordinate's work. Walks every step, verifies every claim, classifies every proposed unit, and surfaces flaws across reuse, architecture, performance, can-kicking…
Knowledge graph-powered implementation planner. Researches the codebase and existing decisions first, then creates structured phased plans with success criteria. Use when starting a new feature, refactor, or multi-step task.
Knowledge graph-powered researcher. Uses semantic search, code graph traversal, and knowledge nodes (decisions, findings, plans) to deeply investigate topics. Faster and more thorough than grep/glob.
Knowledge graph-powered test plan designer. Researches what needs testing, discusses scope and criteria interactively, then creates structured test plans. Use when defining what to test and how.
Knowledge graph-powered test executor. Runs test plans step by step, executes test commands, and records pass/fail/skip results. Read-only — reports results without fixing failures.
Interactive exploration and requirements discovery using the knowledge store. Searches existing decisions, findings, and code before exploring new ideas. Records discoveries as research, findings, and decisions. Use when exploring options, discussing architecture, or investigating before planning.
Build live causal context about a repo. Authors non-trivial thoughts that answer WHY systems exist and behave the way they do, weaving evidence across code, cloud, practice, and knowledge graphs. Distinct from /research (which describes WHAT) — /explore answers why.
Join a hive as a worker (claim work, do it, report the result) or act as a coordinator (dispatch role-targeted work and read the outcomes). A hive is a cloud work-queue for coordinating multiple agents across machines. Use when you want agents on different machines to pass work to each other by capability/role instead…
Execute an implementation plan from the knowledge graph step by step. Updates status, verifies criteria, records thoughts about what you encounter, and charges thoughts when evidence arrives. Use after a plan has been created and approved.
Deep, research-driven review of an infrastructure changeset BEFORE any infra command runs (deploy, apply, helm upgrade, terraform apply, provision, image roll). Grounds every claim in four authorities — provider docs (web-verified), current source, the LIVE cloud graph (actual deployed state), and runtime log graphs …
Ingest design patterns from an authoritative source (book, public catalog, reference site) into the practice/design-patterns.bin library graph. Four stages — collect the source once into a raw graph, extract from it interactively with zero LLM spend, freeze a good extraction as a saved recipe when it is worth…
Orchestration discipline. Defines the team hierarchy, your role as Engineering Manager, signal routing, drift detection, and the failure modes that make you a bad manager. Loads at the brainstorm-to-execute boundary and persists through ticket execution.
Create an implementation plan in the knowledge store. Researches the codebase first, then creates a structured phased plan with success criteria. Use when starting a new feature, refactor, or multi-step task.
Propose net-new projects — new features or gap-fills in existing features — by mining past tickets and thoughts, walking the target repo for feature seams that stop short, and running web research including market/competitor analysis. Mostly non-interactive; presents 3-5 evidence-backed proposals and offers…
Record an architectural or design decision in the knowledge graph with full rationale. Use after making a significant choice that future developers should know about.
Introspect on your thought graph — examine personality, influence, tensions, blind spots, and reasoning patterns. Use for metacognition sessions, debugging reasoning, or understanding how your thinking has evolved.
Research a topic using the knowledge store. Searches code, knowledge nodes, and existing decisions to build understanding. Use when investigating how something works, exploring options, or gathering context before implementation.
Capture the session feedback loop after work is verified for real — record a reproduction/interaction guide, charge the session's reasoning with the real-world evidence, record findings, and close the ticket. Use AFTER a feature is smoke-tested and confirmed working, or an investigation is remediated — never before.
Design a test plan collaboratively. Researches what needs testing, discusses scope and criteria interactively, then creates a structured test plan with steps and pass/fail criteria.