ontology-manager

ontology-manager is an agent for coding agents from modeled-information-format/MIF. It costs 35 tokens per session (997 once invoked), scanned A, original, MIT.

An agent for managing MIF ontology definition files, which describe domain entities, traits, relationships, and discovery patterns.

In plain words
What is it for?
Creating ontology templates, validating files, inspecting their contents, and converting ontology data between supported formats.
Why use it?
It provides a guided way to create and check these files against the MIF JSON Schema, a formal list of allowed fields and rules.

Agent

Install

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.

agentmods
npx agentmods add agents/modeled-information-format/mif/ontology-manager
Clone the repo
git clone --depth 1 https://github.com/modeled-information-format/MIF

Wrote 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.

agentmods badge for ontology-manager

README.md
[![agentmods](https://agentmods.dev/badge/agents/modeled-information-format/mif/ontology-manager.svg)](https://agentmods.dev/agents/modeled-information-format/mif/ontology-manager)
Your own site
<a href="https://agentmods.dev/agents/modeled-information-format/mif/ontology-manager"><img src="https://agentmods.dev/badge/agents/modeled-information-format/mif/ontology-manager.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 997 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.00997
Opus 5 $0.00017 $0.00498
Sonnet 5 $0.00007 $0.00199
Haiku 4.5 $0.00003 $0.00100

Measured 4d ago against content hash a24830f3f842, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ontology-manager 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 4d 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.

.github/agents/ontology-manager.agent.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MIF Ontology Manager

Manage MIF ontology definition files. All operations are validated against schema/ontology/ontology.schema.json.

Prerequisites

Ensure yq and jq are available. For JSON Schema validation, python3 with jsonschema is preferred.

Available Scripts

Scripts are located at .claude/skills/ontology-manager/scripts/.

Create a New Ontology

Every ontology, base and domain, is authored in the modeled-information-format/ontologies repo, not here — run this from a checkout of that repo, writing into its ontologies/ directory:

bash <path-to-MIF-checkout>/.claude/skills/ontology-manager/scripts/scaffold_ontology.sh \
  <id> <version> [--extends mif-base,shared-traits] \
  > ontologies/<id>.ontology.yaml
  • id: lowercase, hyphens only (e.g. my-domain)
  • version: semver (e.g. 0.1.0)
  • --extends: comma-separated parent ontology IDs

Validate an Ontology

bash .claude/skills/ontology-manager/scripts/validate_ontology.sh \
  <file.yaml> [schema/ontology/ontology.schema.json]

Checks: YAML syntax, required fields, ID format, semver, base types, entity names, trait references, discovery regex, JSON Schema compliance.

Inspect an Ontology

bash .claude/skills/ontology-manager/scripts/inspect_ontology.sh \
  <file.yaml> [--section entities|namespaces|traits|relationships|discovery] [--json]

Convert Between Formats

bash .claude/skills/ontology-manager/scripts/convert_format.sh \
  <yaml2json|json2yaml|yaml2jsonld> <input> [output]

Ontology Structure

Every .ontology.yaml file has this structure:

ontology:
  id: my-domain         # REQUIRED: ^[a-z][a-z0-9-]*$
  version: "0.1.0"      # REQUIRED: semver
  description: "..."
  schema_url: https://mif-spec.dev/schema/ontology/ontology.schema.json
  extends: [mif-base]   # optional parent ontologies

namespaces:              # cognitive triad hierarchy
  _semantic:             # facts, concepts, relationships
  _episodic:             # events, experiences, timelines
  _procedural:           # step-by-step processes

entity_types:            # array of entity definitions
  - name: my-entity     # ^[a-z][a-z0-9-]*$
    base: semantic       # semantic|episodic|procedural
    traits: [timestamped]
    schema:
      required: [name]
      properties:
        name: {type: string}

traits:                  # reusable mixins
  my-trait:
    fields:
      my_field: {type: string}

relationships:           # typed connections
  my-rel:
    from: [entity-a]
    to: [entity-b]
    symmetric: false

discovery:               # auto-detection patterns
  enabled: true
  confidence_threshold: 0.8
  content_patterns:
    - pattern: "\\bkeyword\\b"
      namespace: _semantic/knowledge
  file_patterns:
    - pattern: "auth|login"
      namespaces: [_semantic/knowledge]

Read the full file on GitHub · 133 lines

Changes

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.

  1. 4d ago First seen · 133 lines · 35 tokens per session scan A a24830f3f842

Subscribe to this mod's changes

ontology-manager is an agent published in the GitHub repository modeled-information-format/MIF (12 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 997 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

gke-cluster-runner

Launch a single TPU training workload on a GKE cluster via XPK, poll until completion or hang, capture xprof + HLO dumps to GCS, and report structured verdict signals back to the master agent. Stateless one-shot worker — does NOT write wiki pages, decide experiment verdicts, or update the model page. Use for every…

vlasenkoalexey/tpu_performance_autoresearch_wiki · 100 tokens

engram:memory-review

Review and curate memory suggestions from Engram's review queue.

joshuaswarren/remnic · 17 tokens

markdown-accessibility-specialist

Use this agent when you need to audit and improve the accessibility of existing markdown documentation, including README files, tutorials, guides, and any .md content. This agent applies GitHub's five accessibility best practices (descriptive links, alt text, heading hierarchy, plain language, list structure) and…

timothywarner-org/context-engineering · 392 tokens

Azure Principal Architect mode instructions

Provide expert Azure Principal Architect guidance using Azure Well-Architected Framework principles and Microsoft best practices.

timothywarner-org/context-engineering · 25 tokens

007-knowledge-graph-integration

Integrate context hierarchy with Plan 0042's knowledge graph.

paulbreuler/limps · 0 tokens

azure-architect

Expert Azure architecture guidance grounded in the Well-Architected Framework and current Microsoft docs. Use for designing new Azure solutions, reviewing existing architectures, service-selection trade-offs across reliability/security/cost/performance/operations, and multi-region or zero-trust topologies.

timothywarner-org/context-engineering · 56 tokens