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Brief description of what this skill does
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TypeDB-backed ontological memory with schema-driven retrieval. Introspects the live knowledge graph schema, composes TypeQL queries dynamically, and combines graph traversal with embedding-based semantic search for three-stage retrieval (plan, execute, organize with provenance).
Store and retrieve knowledge in the Alhazen TypeDB knowledge graph - remember, recall, organize papers and notes
REQUIRED FIRST — starts TypeDB + dashboard via Docker, loads the Alhazen base schema. Must install before any other Alhazen skill.
Design and implement TypeDB-backed curation skills using the Skillful Alhazen methodology
Search the web using SearXNG (self-hosted metasearch - no API key needed)
| name | your-domain-name |
| description | Brief description of what this skill does |
Use this skill to [describe primary use case]. Claude acts as [describe Claude's role in this domain].
When to use: [Triggers: "ingest [item]", "analyze [item]", "show [entity]", ...]
make db-startuv sync --all-extras (from project root)make build-db after adding your schema.tqlTYPEDB_HOST: TypeDB server (default: localhost)TYPEDB_PORT: TypeDB port (default: 1729)TYPEDB_DATABASE: Database name (default: alhazen_notebook)uv run python .claude/skills/<your-domain>/<your-domain>.py list-entities
During sensemaking, if you encounter a concept, relationship, or entity type that has no place in the current TypeDB schema, that is a schema gap — a signal for schema evolution, not a failure.
When you notice a schema gap:
gh issue create --repo <owner/name> \
--title "Gap [moderate][entity-schema]: <one-sentence summary>" \
--body $'## What was missing\n<the concept you tried to represent>\n\n## What broke\n<which TypeDB entity/relation/attribute is absent>\n\n## Suggested fix\n<proposed TypeQL addition, or unknown>' \
--label "gap:open"
Examples of schema gaps:
methodology attribute on scilit-paperUse --dry-run first to review the issue before filing it.
uv run emits a VIRTUAL_ENV warning to stderr. Always use 2>/dev/null when piping output to a JSON parser — never 2>&1, which merges the warning into stdout and breaks JSON parsing.
Before executing any commands, read USAGE.md in this directory for the complete command reference, workflows, and data model.