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 neutree-ai/openapi-to-skills --skill inline-body-apigit clone --depth 1 https://github.com/neutree-ai/openapi-to-skillsWrote 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/neutree-ai/openapi-to-skills/inline-body-api)<a href="https://agentmods.dev/skills/neutree-ai/openapi-to-skills/inline-body-api"><img src="https://agentmods.dev/badge/skills/neutree-ai/openapi-to-skills/inline-body-api/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/neutree-ai/openapi-to-skills/inline-body-api"><img src="https://agentmods.dev/badge/skills/neutree-ai/openapi-to-skills/inline-body-api.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 | $0.00036 | $0.00245 |
| Opus 5 | $0.00018 | $0.00122 |
| Sonnet 5 | $0.00007 | $0.00049 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
inline-body-api scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Inline Body API
Exercises inline (non-$ref) request/response object schemas.
How to Use This Skill
This API documentation is split into multiple files for on-demand loading.
Directory structure:
references/
├── resources/ # 1 resource index files
├── operations/ # 1 operation detail files
└── schemas/ # 0 schema groups, 0 schema files
Navigation flow:
- Find the resource you need in the list below
- Read
references/resources/<resource>.mdto see available operations - Read
references/operations/<operation>.mdfor full details - If an operation references a schema, read
references/schemas/<prefix>/<schema>.md
Resources
- files →
references/resources/files.md(1 ops)
What ships with it
2 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.
- 10d ago First seen · 34 lines · 36 tokens per session scan A b3b6e35e5ec2
inline-body-api is a skill published in the GitHub repository neutree-ai/openapi-to-skills (340 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 245 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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