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 0xatd/cheaptokens-skills --skill venice-chatgit clone --depth 1 https://github.com/0xatd/cheaptokens-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/0xatd/cheaptokens-skills/venice-chat)<a href="https://agentmods.dev/skills/0xatd/cheaptokens-skills/venice-chat"><img src="https://agentmods.dev/badge/skills/0xatd/cheaptokens-skills/venice-chat/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/0xatd/cheaptokens-skills/venice-chat"><img src="https://agentmods.dev/badge/skills/0xatd/cheaptokens-skills/venice-chat.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 | $0.00071 | $0.03376 |
| Opus 5.5 | $0.00028 | $0.01350 |
| Sonnet 5.5 | $0.00014 | $0.00675 |
| Haiku 4.5 | $0.00007 | $0.00338 |
Grade A, and why
venice-chat 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 2mo 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.
curl https://api.venice.ai/api/v1/chat/completions \ This is a copy
89% identical to venice-chat — 303 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Venice Chat Completions
POST /api/v1/chat/completions is Venice's main text endpoint. It's OpenAI-compatible, plus a venice_parameters object for Venice-only features.
Use when
- You need LLM text generation, with or without tools, with or without streaming.
- You want multimodal inputs (images, audio, video) to a vision/audio-capable model.
- You want Venice-specific features: web search, E2EE, characters, xAI X/Twitter search, strip-thinking, web scraping.
- You need prompt caching for large system prompts or long documents.
- You need structured (
json_schema) output.
For the newer Alpha Responses API, see venice-responses.
Minimal request
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "zai-org-glm-5-1",
"messages": [{"role": "user", "content": "Why is the sky blue?"}]
}'
Response shape is the standard OpenAI chat.completion object (id, object: "chat.completion", choices[].message, usage). With stream: true, responses come as SSE data: lines in chat.completion.chunk format.
The request body
Core fields (OpenAI-compatible)
| Field | Notes |
|---|---|
model |
string — model ID, trait name, or compatibility mapping. Suffixes allowed (see below). Required. |
messages |
array of system / developer / user / assistant / tool messages. Required, min 1. |
temperature, top_p, top_k, min_p, min_temp, max_temp |
sampling controls |
repetition_penalty, frequency_penalty, presence_penalty |
repetition controls |
max_tokens (deprecated) / max_completion_tokens |
upper bound on output tokens |
n |
number of choices (keep 1 to minimize cost) |
seed |
integer for reproducibility |
stop / stop_token_ids |
up to 4 strings, or raw token IDs |
stream, stream_options.include_usage |
SSE streaming + include usage in the final chunk |
response_format |
{type:"json_schema", json_schema:{...}} (preferred), {type:"json_object"}, or {type:"text"} |
tools, tool_choice, parallel_tool_calls |
function calling / built-in tools |
logprobs, top_logprobs |
return token log-probabilities |
reasoning.effort / reasoning_effort |
none | minimal | low | medium | high | xhigh | max |
reasoning.summary |
auto | concise | detailed |
prompt_cache_key, prompt_cache_retention (default/extended/24h) |
prompt caching hints |
text.verbosity |
low/medium/high/auto |
metadata |
key/value strings for tracking |
user, store |
accepted but ignored (OpenAI compat) |
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.
- 2mo ago First seen · 278 lines · 71 tokens per session scan A 565d639d9df5
venice-chat is a skill published in the GitHub repository 0xatd/cheaptokens-skills (2 stars, last pushed 13d ago), licensed MIT. It adds 71 tokens to every session and 3,376 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 89% identical to venice-chat, differing in 303 lines, and is treated as a copy.
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