Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jfrog/ai-agent-examplesnpx agentmods add skills/jfrog/ai-agent-examples/jfrog-onemodelWrote 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/jfrog/ai-agent-examples/jfrog-onemodel)<a href="https://agentmods.dev/skills/jfrog/ai-agent-examples/jfrog-onemodel"><img src="https://agentmods.dev/badge/skills/jfrog/ai-agent-examples/jfrog-onemodel.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 5.1 | $0.00184 | $0.05534 |
| Opus 5 | $0.00092 | $0.02767 |
| Sonnet 5 | $0.00037 | $0.01107 |
| Haiku 4.5 | $0.00018 | $0.00553 |
Grade A, and why
jfrog-onemodel scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> **API transport:** Prefer **`jf api`** (JFrog CLI 2.100.0+). See [jf-api-patterns.md](../jfrog-cli/jf-api-patterns.md) (path-only URLs; auth from `jf config`). Examples using **`curl`** with `$JFROG_URL` + bearer token How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API transport: Prefer
jf api(JFrog CLI 2.100.0+). See jf-api-patterns.md (path-only URLs; auth fromjf config). Examples usingcurlwith$JFROG_URL+ bearer token are fallback when the CLI is missing or below 2.100.0.
JFrog OneModel
Run OneModel GraphQL queries against the JFrog Platform to fetch information about applications, release bundles, artifacts, builds, evidence, packages, and more through the unified OneModel endpoint.
Prerequisites
- "jfrog-cli" skill — this skill depends on the sibling "jfrog-cli" skill for CLI installation and server configuration. Ensure it is installed.
- JFrog CLI (
jf) configured with at least one server — needed to resolve the JFrog Platform URL and access token. - Artifactory 7.104.1+ — OneModel GraphQL requires this minimum version.
- Access token with wildcard audience (
*@*) — the token must be scoped to the content being queried.
Workflow
Follow these steps in order. Skipping the schema fetch (step 2) is the most common source of errors — queries built from assumptions or cached knowledge will fail on servers whose schema differs from what you expect.
- Resolve credentials — get JFrog URL and access token
- Fetch the schema — always fetch the supergraph schema from the server
- Understand the query intent — map the user's request to available domains and types
- Construct the GraphQL query — build the query based on the resolved schema
- Validate the query against the schema — verify every field and type before executing
- Execute the query — POST to the OneModel endpoint
- Handle the response — paginate if needed, present results clearly
1. Resolve Credentials
Get the JFrog Platform URL and access token from the JFrog CLI configuration.
First, identify the server ID to use. List configured servers with:
jf config show
If the user did not specify a server, use the one marked Default: true.
If no server is configured, refer to the "jfrog-cli" skill's login flow.
What ships with it
3 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.
- 8d ago First seen · 361 lines · 184 tokens per session scan A 35e1236a0d49
jfrog-onemodel is a skill published in the GitHub repository jfrog/ai-agent-examples (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 184 tokens to every session and 5,534 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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