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 CodeInfinity1/Stram --skill openai-api-developmentgit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/codeinfinity1/stram/openai-api-development)<a href="https://agentmods.dev/skills/codeinfinity1/stram/openai-api-development"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/openai-api-development/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/codeinfinity1/stram/openai-api-development"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/openai-api-development.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00039 | $0.00481 |
| Opus 5.5 | $0.00016 | $0.00192 |
| Sonnet 5.5 | $0.00008 | $0.00096 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
openai-api-development 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 1mo 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAI API Development
Purpose
Implement robust OpenAI and OpenAI-compatible integrations. This skill supports OpenAI, Groq-compatible endpoints, Ollama local OpenAI-compatible endpoints, and other configured clients through generalized adapters.
When To Use
Use for model client bugs, Responses/chat completions, tool calling, JSON schema outputs, streaming, embeddings, provider fallback, Groq/Ollama/OpenAI-compatible setup, and smoke tests.
Inputs And Evidence
- Provider config, env keys, model, base URL, error output, request/response logs, and current code.
- Tool schemas, prompt requirements, and verification case.
Tool Map
read_filesearch_workspacerun_shell_commandpython_interpretersystem_statuscapability_surface
Workflow
- Inspect existing provider abstraction and environment loading.
- Use official docs when OpenAI API details are current/unstable.
- Keep clients generalized around base URL, API key, model, timeout, and schema.
- Preserve full prompts when required; do not over-compress task-critical prompts.
- Add tests for request shape, parsing, errors, and provider selection.
- Run mocked or approved live smoke and report exact provider/model.
Native Implementation Boundaries
- Implement clients in Stram or the target project.
- Do not import upstream provider wrappers as implementation.
- Avoid regex/keyword routing for provider choice or user intent.
Safety And Approval
- Redact API keys.
- Live calls may cost money and require user intent.
- Do not log private prompts unnecessarily.
Verification
- Provider smoke should prove request reached the intended endpoint when possible.
- 401/403/network errors should be reported with code and likely boundary, not hidden.
- Tests should cover parser behavior.
Failure Modes
- Treating OpenAI, Groq, and Ollama as identical beyond compatible request shape.
- Swallowing provider error details.
- Hardcoding one model across all tasks.
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.
- 1mo ago First seen · 67 lines · 39 tokens per session scan A 44763614f8d2
openai-api-development is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 481 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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