AUTO-INVOKE when user mentions knowledge base, wiki, KB, semantic memory, llm-wiki, knowledge ingest, document corpus. Knowledge-base framework quick reference — discovery phrases for KB ingest/health, semantic-memory kernel skills, llm-wiki profiles.
Scanned 9/3/2026
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npx -y skills add jmagly/aiwg --skill knowledge-base-quickref --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: knowledge-base-quickref
namespace: aiwg
platforms: [all]
kernel: true
description: AUTO-INVOKE when user mentions knowledge base, wiki, KB, semantic memory, llm-wiki, knowledge ingest, document corpus. Knowledge-base framework quick reference — discovery phrases for KB ingest/health, semantic-memory kernel skills, llm-wiki profiles.
---
# Knowledge Base Framework — Quick Reference
This is your always-loaded directory for the AIWG **knowledge-base** framework. It does **not** list every skill. Most heavy lifting comes from the **semantic-memory kernel** in `aiwg-utils` (`memory-ingest`, `memory-lint`, etc.) — this framework is a thin topology on top.
## Canonical access pattern: discover → show
When you find a candidate via `aiwg discover`, fetch its body with `aiwg show <type> <name>`. **Never** use `find`, `ls`, `Glob`, or direct `Read` on `<provider>/skills/` paths — those reflect the kernel-pivot deploy state, not the full surface.
```bash
aiwg discover "<phrase>" # find — returns ranked candidates
aiwg show skill <name> # fetch — streams the SKILL.md body
```
If your platform's Skill tool errors on a non-kernel skill (expected — most aren't kernel), the fallback is `aiwg show`, never filesystem browsing. Last-resort if `aiwg` itself is broken: read directly from `$AIWG_ROOT/agentic/code/...` (the canonical corpus, always present).
## How to use this quickref
1. Identify the **capability domain** the user's need belongs to
2. Pick a **curated phrase** from that domain
3. Run `aiwg discover "<phrase>"` and surface the top match to the user
**Do not enumerate skills from memory.** Discovery is the lookup surface.
## What this framework is for
A **thin topology** on top of AIWG's semantic-memory kernel — turning any project's `.aiwg/kb/` into a queryable knowledge base. Sources get ingested into structured pages (entities, concepts, summaries, syntheses) with cross-references, deduplication, and lint coverage. Pairs naturally with the `llm-wiki` addon for Obsidian-compatible profiles (book-companion / personal / research-deep-dive / business-team / generic).
## Capability domains
| Domain | Covers |
|---|---|
| **KB lifecycle** | Ingest sources, health-check the KB |
| **Semantic memory kernel** (in aiwg-utils) | Generic ingest/lint/log/query primitives any consumer can declare a topology against |
| **LLM-wiki profiles** | Topology profiles that shape how `kb-ingest` derives pages |
| **Cross-ref traversal** | Graph-native via `aiwg index neighbors --graph kb` |
## Curated discovery phrases
### KB lifecycle
```bash
aiwg discover "kb-ingest" # → kb-ingest (score 1.00)
aiwg discover "ingest source into knowledge base" # → kb-ingest
aiwg discover "kb-health" # → kb-health (score 1.00)
aiwg discover "knowledge base lint" # → kb-health
```
### Semantic memory kernel (aiwg-utils)
```bash
aiwg discover "memory ingest" # → memory-ingest
aiwg discover "memory lint" # → memory-lint
aiwg discover "memory log append" # → memory-log-append
aiwg discover "memory log render" # → memory-log-render
aiwg discover "memory query capture" # → memory-query-capture
```
### LLM-wiki profiles (in the llm-wiki addon)
```bash
aiwg discover "llm wiki profile" # → llm-wiki addon entries
aiwg discover "book companion knowledge base" # → llm-wiki book-companion profile
aiwg discover "research deep dive wiki" # → llm-wiki research-deep-dive profile
```
### Cross-ref traversal (uses the artifact index, not a skill)
```bash
aiwg index neighbors --graph kb --node <slug> # traverse the KB graph
```
## Fortemi Core Migration Note
KB ingest and health operations continue to use `resolveStorage('kb')` and the
semantic-memory topology. Fortemi storage routing, when configured through
`.aiwg/storage.config`, is separate from the default Fortemi Core index/search
backend. During the migration preview, use `--backend local` for legacy fallback only on
artifact graph commands such as `aiwg index neighbors --graph kb` after
`aiwg index sync`; do not treat `kb-ingest` or
`kb-health` as Fortemi Core ingest commands.
## How knowledge-base composes with semantic-memory
```
kb-ingest ─────┐ ┌──── memory-ingest (kernel)
├── declares topology ──┤
kb-health ─────┘ └──── memory-lint (kernel)
memory-query-capture
memory-log-append / render
```
Every KB entry is a semantic-memory entry with a KB-specific topology (page types, cross-ref style, derived-pages config). The kernel handles ingest mechanics; this framework declares *what shape* the KB takes.
## Page types
When ingesting via `kb-ingest`, the topology produces:
- **Entity pages** — people / orgs / products / works (one per noun)
- **Concept pages** — ideas / methods / principles
- **Source summaries** — per-source distillation (one per ingested URL/file)
- **Synthesis pages** — composite views across multiple sources
Cross-references between these are graph-native (visible to `aiwg index neighbors`).
## Profile selection (via `llm-wiki` addon)
| Profile | Use for |
|---|---|
| `book-companion` | Reading a book, building a structured companion |
| `personal` | Personal knowledge / journal-of-ideas |
| `research-deep-dive` | Academic research project (uses research-corpus conventions) |
| `business-team` | Team-shared business KB |
| `generic` | No profile chosen — vanilla semantic-memory shape |
The discoverable `llm-wiki` driver explains profile selection and activation.
Its canonical operation is `aiwg use llm-wiki --profile <name>`. The profile
shapes how `kb-ingest` derives pages.
## Artifact directory layout
```
.aiwg/kb/
├── entities/ # Entity pages (PROF-* compatible if research-corpus also installed)
├── concepts/ # Concept pages
├── summaries/ # Per-source distillation
├── syntheses/ # Composite views
└── log.jsonl # Semantic-memory event log
```
## When the curated phrases don't fit
```bash
aiwg discover "<your need, paraphrased>" --limit 5
```
## Anti-pattern: don't enumerate
If a user asks "what KB skills are available?", **do not list from this skill**. Run:
```bash
aiwg discover --type skill --limit 20 "<their interest area>"
```
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