Borrowing it
Nothing to install: this file belongs to aget-framework/aget. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aget-framework/aget/main/.claude/skills/aget-analyze-ontology/SKILL.mdgit clone --depth 1 https://github.com/aget-framework/agetWrote 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/aget-framework/aget/aget-analyze-ontology)<a href="https://agentmods.dev/skills/aget-framework/aget/aget-analyze-ontology"><img src="https://agentmods.dev/badge/skills/aget-framework/aget/aget-analyze-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/aget-framework/aget/aget-analyze-ontology"><img src="https://agentmods.dev/badge/skills/aget-framework/aget/aget-analyze-ontology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.01854 |
| Opus 5 | $0.00015 | $0.00927 |
| Sonnet 5 | $0.00006 | $0.00371 |
| Haiku 4.5 | $0.00003 | $0.00185 |
Grade A, and why
aget-analyze-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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- aget-analyze-ontology — 91% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aget-analyze-ontology
Analyze the health and coverage of AGET ontology artifacts across all controlled vocabularies.
Purpose
Provide deep analysis of ontology health for agents managing vocabularies and specifications. Goes beyond file counts to assess semantic completeness, cross-vocabulary consistency, and actual usage coverage.
Verb convention (check- vs analyze-):
check-*= Lightweight monitoring. Threshold pass/fail, health status, ~5 seconds. (e.g.,aget-check-kb,aget-check-health)analyze-*= Deep qualitative analysis. Cross-references, coverage percentages, recommendations, ~30 seconds. (e.g.,aget-analyze-kb,aget-analyze-ontology)
KB has aget-check-kb (quick health); a deep-quality aget-analyze-kb does not exist. Ontology currently has only analyze-. If fleet ontology adoption grows beyond 2 operational agents, consider splitting:
aget-check-ontology= Steps 7-8 only (tier compliance + ratio check)aget-analyze-ontology= Steps 1-8 (full vocabulary analysis)
Execution
When invoked, perform these analyses:
1. Vocabulary Discovery
# Find all vocabulary files
VOCABS=(
".aget/specs/skills/SKILL_VOCABULARY.md"
".aget/specs/AGET_CONTROLLED_VOCABULARY.md"
".aget/evolution/CONTROLLED_VOCABULARY.md"
)
for vocab in "${VOCABS[@]}"; do
test -f "$vocab" && echo "Found: $vocab" || echo "Missing: $vocab"
done
2. Term Extraction
Extract defined terms from each vocabulary:
- Parse markdown headers and definition tables
- Count terms per vocabulary
- Build unified term registry
3. Completeness Check
Scan specifications for term usage:
# Find terms used in specs
grep -oh '\b[A-Z][a-z]*_[A-Z][a-z]*\b' .aget/specs/skills/*.yaml | sort -u
# Compare against vocabulary definitions
# Report undefined terms
4. Consistency Check
Compare term definitions across vocabularies:
- Same term should have same definition
- Flag conflicts with both definitions
- Suggest canonical source
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.
- 11d ago First seen · 216 lines · 30 tokens per session scan A 26407b432781
aget-analyze-ontology is a skill published in the GitHub repository aget-framework/aget (11 stars, last pushed 2d ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,854 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 2026-08-30.
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