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 xberg-io/liter-llm --skill e2e-fixturesgit 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/e2e-fixtures)<a href="https://agentmods.dev/skills/xberg-io/liter-llm/e2e-fixtures"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/e2e-fixtures/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/e2e-fixtures"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/e2e-fixtures.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 | $0.00045 | $0.00503 |
| Opus 5.5 | $0.00018 | $0.00201 |
| Sonnet 5.5 | $0.00009 | $0.00101 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
e2e-fixtures 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 yesterday.
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 E2E Fixtures
- One fixture object per file,
fixtures/<category>/<id>.json.fixtures/schema.jsonstill requires anapifield that no fixture carries; the generator readscall, so follow existing fixtures, not the schema. - Categories match the directory (
smoke,chat,streaming,error-handling,proxy,files,batches,rerank,embed, ...); the exception isproviders/, whose fixtures carry the test kind ascategory(smoke,error-handling,streaming,tool-calling), not the directory. - Fields:
id,description,category,docs {topic, stem, title},tags,call,input,mock_response {status, body},assertions, and optionallyenv,skip {languages, reason},requirements. callnames an API:chatis the default; named calls includechat_stream,embed,rerank,image_generate,list_models,moderate,search,create_response,speech,transcribe,ocr,create_batch(full set inalef.toml).inputis the request body.- Assertion types in use:
equals,not_error,error,count_equals,count_min,not_empty,is_true,greater_than,contains.errortakes the error kind asvalue(for exampleAuthentication); assert the HTTP status withfield: error.status_code. - Loop:
task e2e:generatethentask e2e:test(aliases of the:alltasks); full pipelinetask e2e:verify:all(aliastask test:e2e).
What ships with it
1 file 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.
- yesterday First seen · 23 lines · 45 tokens per session scan A eea069132fcc
e2e-fixtures is a skill published in the GitHub repository xberg-io/liter-llm (263 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 503 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 2026-10-28.
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