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 Omni-Scientist/OmniScientist --skill omniscigit clone --depth 1 https://github.com/Omni-Scientist/OmniScientistWrote 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/omni-scientist/omniscientist/omnisci)<a href="https://agentmods.dev/skills/omni-scientist/omniscientist/omnisci"><img src="https://agentmods.dev/badge/skills/omni-scientist/omniscientist/omnisci/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/omni-scientist/omniscientist/omnisci"><img src="https://agentmods.dev/badge/skills/omni-scientist/omniscientist/omnisci.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 | $0.00145 | $0.04873 |
| Opus 5 | $0.00072 | $0.02436 |
| Sonnet 5 | $0.00029 | $0.00975 |
| Haiku 4.5 | $0.00015 | $0.00487 |
Grade A, and why
omnisci scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.
omnisci: DeepSeek is the scientist, the CLIs are the instruments
Do the science in the current CLI session. The python here does only what a model must not do by hand: render
raw data into something viewable, run analysis code, fetch real references, assemble LaTeX, and enforce the
gates. These CLIs never call another model API. DeepSeek V4 Flash remains the scientist and author. Because the
official DeepSeek endpoint accepts text only, the CLI's view_image sends pixels to its fixed, vision-capable
sidecar and returns only the factual observation to DeepSeek. This follows OmniScientist's own text-backbone
plus VISION_SIDECAR design.
Where the commands live
The CLIs ship inside this skill and the launcher sets OMNISCI. Confirm it once and use it in every command:
test -n "$OMNISCI" && test -f "$OMNISCI/evidence_cli.py"
python3 $OMNISCI/evidence_cli.py --help # confirm before going further
--task takes a case directory (absolute paths always work), or a bare name that resolves under
$OMNISCI_CASES or the engine's bundled examples/. Every other path you pass (a script, a figure, a .tex,
a sections.json) is resolved relative to the case directory.
Every command echoes the case it resolved. Check it on your first call. A bare name can land on a bundled
example that already holds someone else's recorded runs, and the gate would then happily ground your paper's
numbers against their ledger. When the case is the user's own folder, pass its absolute path.
Three state-changing steps are OmniScientist tools, not shell commands: omnisci_record, omnisci_bib, and
omnisci_compile. Call them through the tool protocol. They run the packaged CLIs with argument arrays and
return receipts that the final delivery verifier binds to the current files. A bash call to the same Python
CLI may help diagnose a failure, but it cannot satisfy final delivery.
Before the loop: is there a case?
A case is a directory holding a series.json. Bundled demos have one. A real user almost never does: they
have a folder of images, recordings or volumes, and a question. Build the case first, from their folder:
What ships with it
16 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.
- bin/case_cli.py 6.0 KB runs code
- bin/evidence_cli.py 2.5 KB runs code
- bin/gate_cli.py 17 KB runs code
- bin/hostbridge.py 13 KB runs code
- bin/lit_cli.py 8.1 KB runs code
- bin/paper_cli.py 32 KB runs code
- bin/vendor/agentic.py 211 KB runs code
- bin/vendor/evidence.py 59 KB runs code
- bin/vendor/figtools.py 12 KB runs code
- bin/vendor/paper_specs.py 17 KB runs code
- bin/vendor/paper.py 32 KB runs code
- bin/vendor/paperlint.py 34 KB runs code
- bin/vendor/paradigms.py 9.0 KB runs code
- bin/vendor/venue_styles.py 8.0 KB runs code
- bin/vendor/writer.py 66 KB runs code
- requirements.txt 496 B
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.
- 7d ago Changed · +31 lines a422f8204c6d
- 12d ago First seen · 278 lines · 145 tokens per session scan A e6590e40ffb7
omnisci is a skill published in the GitHub repository Omni-Scientist/OmniScientist (153 stars, last pushed 9d ago), licensed MIT. It adds 145 tokens to every session and 4,873 once invoked, about $0.0007 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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