skills/ground/SKILL.md
Grounding / assumption-check: pull deeper context from brain + bus when uncertain, before acting. Use when: getting mixed signals from the codebase, about to commit to a non-obvious decision, prior decisions might exist for this exact problem, or you want to verify an assumption before action ("am I sure about this?", "have we decided this before?"). Returns relevant brain memories, recent bus events, and linked priors ranked by relevance — not a wall of text. Aliases: grounding, sanity-check, verify-assumption. NOT for: routine "what does this code do" questions (use Read or Grep), broad codebase exploration (use Agent(Explore)), or fetching specific symbols (use wicked-brain:search directly).
npx skillsauth add mikeparcewski/wicked-garden wicked-garden-groundInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are uncertain. Pull what's known into focus.
question argument (free text from the user / Claude's internal state)wicked-brain:query — conceptual grounding ("what do we know about X")wicked-brain:search — specific decisions, patterns, gotchas (top 5 results)wicked-bus:query — recent bus events matching the question (last 50, filter by
relevance to question terms)brain/memory, brain/wiki, brain/chunk, or bus/eventwicked-brain:read {path} depth=2){most relevant path}, use
wicked-brain:read {path} depth=2"When invoked with a question:
Step 1 — Decompose the question into 3–5 search terms. Extract noun phrases,
named entities, and technical terms. Example: "v8 daemon projection model" →
["daemon", "projection", "v8 architecture", "state machine"].
Step 2 — Parallel execution. Invoke all three in a single parallel batch:
# Brain conceptual query
Skill(wicked-brain:query, question="{question}", session_id="{session}")
# Brain symbol/decision search (repeat per term if ≥2 terms)
Skill(wicked-brain:search, query="{term1}", limit=5, session_id="{session}")
Skill(wicked-brain:search, query="{term2}", limit=5, session_id="{session}")
# Bus recent events
Skill(wicked-bus:query, query="{question}", limit=50)
Step 3 — Rank and dedupe. Collect all results. Score by:
Keep the top 5–10 unique signals. Drop results where two sources say the same thing — keep the higher-priority source.
Step 4 — Format output. Use this shape:
## Grounding: {question}
### What the brain knows
1. [brain/memory] {one-line relevance} — `{path}` → suggest: wicked-brain:read {path}
2. [brain/wiki] {one-line relevance} — `{path}`
3. [brain/chunk] {one-line relevance} — `{path}`
### Recent bus activity
4. [bus/event] {event_type} @ {timestamp} — {one-line relevance}
5. [bus/event] {event_type} @ {timestamp} — {one-line relevance}
### If you need more depth
`wicked-brain:read {most relevant path} depth=2`
Step 5 — If zero results from both brain and bus, say so explicitly:
"No prior decisions or recent events found for this question. Proceeding without
grounding — consider storing the decision you reach with wicked-brain:memory."
Never block progress. Ground is a focusing tool — absence of prior context is itself a useful signal.
If you reach a decision that others should know about:
wicked-brain:memory (store mode)wicked-bus:emit with the relevant event typeThe value of grounding compounds when decisions are written back.
development
Pattern-conformance agent-half: evaluates a produced artifact or diff against a set of architectural/design pattern rules from the conformance-rule store (wicked_governance schema). Returns structured findings with rule ID, severity, and rationale — the deterministic half (mechanical rule recall) is done by the guard pipeline; this is the semantic evaluation step. Triggered by: the guard_pipeline `outgov_pattern` check (session-close), or explicitly by an engineering review when WICKED_OUTGOV_RULES_DIR is populated. NOT a replacement for the full `engineering` review skill — focuses only on conformance to stored Pattern rules; architecture and code-quality checks live in the `engineering` skill. Semantic evaluation reuses `wicked-garden-qe-semantic-reviewer` as the designated agent-half evaluator (per garden#983 spec). This skill is the orchestrating wrapper that loads applicable Pattern rules and delegates the per-rule semantic judgment to qe-semantic-reviewer.
tools
The FOUNDATIONAL domain-model capability: extract a codebase's domain — testable business rules (with confidence + provenance), entities, requirements — as a schema-conformant model on the estate graph. The workers annotate the store; wicked-core reads it and builds the requirements graph, coverage-gating fail-closed. Steers three fork workers. A shared substrate, not a modernization tool. The `modernize` archetype DERIVES from it; build / migrate / review / specify / explore consume the SAME domain model — none OWN it. Understanding a codebase's domain is upstream of almost everything else garden does. Use when: "extract the business rules / domain model from this codebase", "build a requirements graph from the code", "what does this system actually require", "reverse-engineer the domain before we build/port/migrate". Works on ANY codebase (modern or legacy) — the value is the domain model, not the porting. NOT the code transform itself (that is the archetype consuming this model). This skill produces the DOMAIN MODEL, not new code.
development
Domain-graph fork worker for the modernize archetype. Groups the estate's Louvain communities into business domains, attaches each requirement to its cluster (advisory cluster_id provenance), and invokes wicked-core's domain-graph build (which reads the annotated estate store, recomputes coverage fail-closed, and builds the requirements graph) — then validates core's output against the vendored schema. Use when: dispatched by wicked-garden-domain after rule extraction to turn a flat rule set into cluster-keyed domains; "group these into domains", "build the requirements graph", "translate clusters into a domain model". NOT for mining the rules themselves (that is domain-extractor) or threat-modeling (that is domain-coverage).
tools
Rule-extraction fork worker for the FOUNDATIONAL domain-model capability. Mines testable business rules from a codebase — each with a numeric confidence and a provenance{source, ref, source_kinds} — and annotates them into the estate store so wicked-core can build the domain-model requirements graph (coverage-gated). This is a substrate, not a modernization tool: the `modernize` archetype DERIVES from it, and build / migrate / review / specify / explore can consume the same domain model — none OWN it. Use when: dispatched by wicked-garden-domain to mine the business_rules of a codebase (or a module); "extract the domain rules", "what does this system require", building the requirements half of a domain model. NOT for grouping into domains (that is domain-modeler) or judging coverage (that is domain-coverage — a seat-distinct evaluator).