Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CraftOS-dev/CraftBot --skill ontologygit clone --depth 1 https://github.com/CraftOS-dev/CraftBotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/craftos-dev/craftbot/ontology)<a href="https://agentmods.dev/skills/craftos-dev/craftbot/ontology"><img src="https://agentmods.dev/badge/skills/craftos-dev/craftbot/ontology/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/craftos-dev/craftbot/ontology"><img src="https://agentmods.dev/badge/skills/craftos-dev/craftbot/ontology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00086 | $0.01633 |
| Opus 5.5 | $0.00034 | $0.00653 |
| Sonnet 5.5 | $0.00017 | $0.00327 |
| Haiku 4.5 | $0.00009 | $0.00163 |
Grade A, and why
ontology scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to ontology — 23 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ontology
A typed vocabulary + constraint system for representing knowledge as a verifiable graph.
Core Concept
Everything is an entity with a type, properties, and relations to other entities. Every mutation is validated against type constraints before committing.
Entity: { id, type, properties, relations, created, updated }
Relation: { from_id, relation_type, to_id, properties }
When to Use
| Trigger | Action |
|---|---|
| "Remember that..." | Create/update entity |
| "What do I know about X?" | Query graph |
| "Link X to Y" | Create relation |
| "Show all tasks for project Z" | Graph traversal |
| "What depends on X?" | Dependency query |
| Planning multi-step work | Model as graph transformations |
| Skill needs shared state | Read/write ontology objects |
Core Types
# Agents & People
Person: { name, email?, phone?, notes? }
Organization: { name, type?, members[] }
# Work
Project: { name, status, goals[], owner? }
Task: { title, status, due?, priority?, assignee?, blockers[] }
Goal: { description, target_date?, metrics[] }
# Time & Place
Event: { title, start, end?, location?, attendees[], recurrence? }
Location: { name, address?, coordinates? }
# Information
Document: { title, path?, url?, summary? }
Message: { content, sender, recipients[], thread? }
Thread: { subject, participants[], messages[] }
Note: { content, tags[], refs[] }
# Resources
Account: { service, username, credential_ref? }
Device: { name, type, identifiers[] }
Credential: { service, secret_ref } # Never store secrets directly
# Meta
Action: { type, target, timestamp, outcome? }
Policy: { scope, rule, enforcement }
Storage
Default: memory/ontology/graph.jsonl
{"op":"create","entity":{"id":"p_001","type":"Person","properties":{"name":"Alice"}}}
{"op":"create","entity":{"id":"proj_001","type":"Project","properties":{"name":"Website Redesign","status":"active"}}}
{"op":"relate","from":"proj_001","rel":"has_owner","to":"p_001"}
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 232 lines · 86 tokens per session scan A 5ceddfef0a82
ontology is a skill published in the GitHub repository CraftOS-dev/CraftBot (400 stars, last pushed 2d ago), licensed MIT. It adds 86 tokens to every session and 1,633 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ontology, differing in 23 lines, and is treated as a copy.
Other skills, from other repositories
context-pack-builder
A tool for turning long conversations, project history, research, and scattered notes into a compact handover document for another person or coding agent. The document records goals, decisions, constraints, current status, next steps, and open questions.
ast-skeletonizer
Extract types, classes, and function signatures into a compact code outline when investigating structure before implementation details.
productivity-memory
Two-tier memory system that makes the AI a true workplace collaborator. Decodes shorthand, acronyms, nicknames, and internal language so the AI understands requests like a colleague would. Uses CONTEXT.md for working memory and a memory/ directory for the full knowledge base.
productivity-update
Sync tasks and refresh memory from your current activity.
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
memory-compaction
MUST use when user says 'compact memory', 'compact [file]', 'check budgets', 'set budget', 'restore compaction', or before any 'save' whose target memory file exceeds its budget in compaction/compaction-policy.md.