Your Domain Name Skill
SkillDev toolsBrief description of what this skill does
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Your Domain Name Skill skill
What this skill tells your AI
The instructions your AI receives, as published by sciknow-io/skillful-alhazen in skills/_template/SKILL.md and read by ahel’s review.
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]", ...]
Prerequisites
- TypeDB must be running:
make db-start - Dependencies installed:
uv sync --all-extras(from project root) - Schema loaded: run
make build-dbafter adding yourschema.tql
Environment Variables
TYPEDB_HOST: TypeDB server (default: localhost)TYPEDB_PORT: TypeDB port (default: 1729)TYPEDB_DATABASE: Database name (default: alhazen_notebook)
Quick Start
uv run python .claude/skills/<your-domain>/<your-domain>.py list-entities
Schema Gap Recognition
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:
- Complete as much as possible with the current schema (partial knowledge > none)
- Immediately file a gap issue:
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:
- A paper has a methodology section but there's no
methodologyattribute onscilit-paper - A job posting mentions a work arrangement type that isn't in the schema
- A disease has a phenotype frequency that can't be attached to the current relation
Use --dry-run first to review the issue before filing it.
Command Output Pattern
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.
Signals
- GitHub stars
- 21
- Forks
- 3
- Last commit
- Aug 2026
ahel review
K6info
bundled executables the agent is told to runK1binfo
installs-packages (in template.py)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
your-domain-name- Source
- github.com/sciknow-io/skillful-alhazen