Borrowing it
Nothing to install: this file belongs to xberg-io/liter-llm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xberg-io/liter-llm/main/.agents/skills/mcp/SKILL.mdgit clone --depth 1 https://github.com/xberg-io/liter-llmWrote 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/xberg-io/liter-llm/mcp)<a href="https://agentmods.dev/skills/xberg-io/liter-llm/mcp"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/mcp/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/xberg-io/liter-llm/mcp"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/mcp.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 | $0.00013 | $0.00405 |
| Opus 5 | $0.00006 | $0.00202 |
| Sonnet 5 | $0.00003 | $0.00081 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
mcp 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 9d 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
liter-llm MCP Reference
Use this skill when integrating liter-llm through Model Context Protocol tools, prompts, or resources.
cancel_batch: Cancel an in-progress batch processing jobcancel_response: Cancel an in-progress response (Responses API)chat: Send a chat completion request to an LLMcreate_batch: Create a new batch processing jobcreate_file: Upload a file to the LLM providercreate_response: Create a new response (Responses API)delete_file: Delete an uploaded fileembed: Generate text embeddings for the given inputfile_content: Retrieve the raw content of an uploaded filegenerate_image: Generate images from a text promptlist_batches: List batch processing jobslist_files: List uploaded fileslist_models: List available models from configured providersmoderate: Check content against moderation policiesocr: Extract text from an image or document via OCRrerank: Rerank documents by relevance to a queryretrieve_batch: Retrieve a batch processing job by IDretrieve_file: Retrieve metadata for an uploaded fileretrieve_response: Retrieve a response by ID (Responses API)search: Perform a web or document searchspeech: Generate speech audio from text (text-to-speech)transcribe: Transcribe audio to text (speech-to-text)
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.
- 9d ago First seen · 37 lines · 13 tokens per session scan A 146c585d52be
mcp is a skill published in the GitHub repository xberg-io/liter-llm (252 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 405 once invoked, about $0.0001 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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