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 agentmods add skills/hashgraph-online/awesome-codex-plugins/ontoly-software-graphnpx skills add hashgraph-online/awesome-codex-plugins --skill ontoly-software-graphgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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/hashgraph-online/awesome-codex-plugins/ontoly-software-graph)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/ontoly-software-graph"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/ontoly-software-graph.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00612 |
| Opus 5 | $0.00023 | $0.00306 |
| Sonnet 5 | $0.00009 | $0.00122 |
| Haiku 4.5 | $0.00005 | $0.00061 |
Grade A, and why
ontoly-software-graph 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ontoly Software Graph
Use this skill when the user asks Codex to understand a TypeScript repository's architecture, dependency graph, request flow, service ownership, configuration usage, impact radius, package topology, or security-sensitive code paths.
Ontoly is a deterministic Software Graph compiler. It does not answer questions with AI. It builds graph evidence that Codex can query before falling back to source search.
Workflow
-
Check whether
.ontoly/SoftwareGraph.jsonexists. -
If the graph is missing or stale, ask before installing dependencies or writing generated graph files. Then run:
pnpm add -D @0xsarwagya/ontoly-cli pnpm ontoly build . -
Inspect graph quality before answering:
pnpm ontoly coverage . pnpm ontoly stats . -
Prefer Ontoly graph queries before repository-wide source search:
pnpm ontoly architecture --json pnpm ontoly report dependencies --format markdown pnpm ontoly report routes --format markdown pnpm ontoly query impact <node-id> pnpm ontoly trace <node-id-or-name> -
Start Ontoly MCP when the environment supports MCP-backed tools:
pnpm ontoly mcp -
Use source files only when the graph is missing, stale, low confidence, or insufficient for the question.
Common Questions
- "Explain this repository."
- "Which service owns authentication?"
- "Trace the login flow."
- "What breaks if I remove this repository/service/function?"
- "Which packages depend on this module?"
- "Where is this environment variable read?"
- "Which routes are protected by auth?"
Evidence Rules
When answering, cite graph evidence:
- graph hash
- node ids
- relationship types
- source spans when available
- diagnostics or confidence warnings
- fallback reason if source files were inspected
Never claim certainty beyond Ontoly evidence. If graph coverage is incomplete, say exactly which part is inferred or unresolved.
Official Ontoly Skills
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.
- 4d ago First seen · 82 lines · 47 tokens per session scan A 19feb860e384
ontoly-software-graph is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (859 stars, last pushed 6d ago), licensed Apache-2.0. It adds 47 tokens to every session and 612 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.
Other skills, from other repositories
search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
sprr
Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".
similar-resources
Given a Japanese NLP GitHub repo or Hugging Face model/dataset (URL / owner/repo / tool name), find repositories or models/datasets that do the same or related processing. Mines the bundled dataset for content-similar items, then expands via web research across both GitHub and Hugging Face, then merges and re-ranks.
bprr
Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.
auditing-aws-s3-bucket-permissions
Systematically audit AWS S3 bucket permissions to identify publicly accessible buckets, overly permissive ACLs, misconfigured bucket policies, and missing encryption settings using AWS CLI, S3audit, and Prowler to enforce least-privilege data access controls.
collecting-indicators-of-compromise
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for…