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 agentmods add skills/aallan/vera/docsnpx skills add aallan/vera --skill docsgit clone --depth 1 https://github.com/aallan/veraWhat 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 | $0.00061 | $0.32997 |
| Opus 5 | $0.00030 | $0.16498 |
| Sonnet 5 | $0.00012 | $0.06599 |
| Haiku 4.5 | $0.00006 | $0.03300 |
Grade A, and why
vera-language 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 2d 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 — 2,471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vera Language Reference
Vera is a programming language designed for LLMs to write. It uses typed slot references instead of variable names, requires contracts on every function, and makes all effects explicit.
Installation
Vera requires Python 3.11 or later. Node.js 22+ is optional (only needed for vera compile --target browser and browser parity tests).
Recommended — install from the GitHub source checkout. The checkout is the full environment this file teaches from: alongside the compiler and the vera CLI it carries the bundled examples/, the conformance suite in tests/conformance/ (minimal working programs for every language feature), and the specification in spec/:
git clone https://github.com/aallan/vera.git && cd vera
python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate
python -m pip install -e .
For an editable source install with the language server, use python -m pip install -e ".[lsp]" — see LSP_SERVER.md. Verify the install end to end with the bundled example:
vera check examples/hello_world.vera # should print "OK: examples/hello_world.vera"
vera run examples/hello_world.vera # should print "Hello, World!"
Toolchain only — install the released veralang distribution from PyPI. This installs the vera command and all runtime dependencies (Lark parser, Z3 solver, wasmtime), but not the examples, conformance programs, or specification — those exist only in the checkout:
python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate
python -m pip install veralang
vera version
For the language server on this route, install python -m pip install "veralang[lsp]".
If you are working on the compiler itself, install development dependencies too:
python -m pip install -e ".[dev]"
Platform support: Vera is tested in CI on macOS 15+ (Apple Silicon), Ubuntu 24.04 LTS (x86_64), and Windows Server 2022, against Python 3.11–3.13. macOS 14 (Sonoma) and earlier, and Ubuntu 22.04 LTS aarch64, are out of scope — install will fail at dependency resolution. See README §Supported platforms for the full matrix, workarounds, and the data behind the baseline.
For agents running in a sandbox (Claude.ai, Code Interpreter, container-based execution environments, etc.): the steps above work. Sandboxes typically have Python,
git,pip, and outbound network access — that's all Vera needs. Run the install commands and verify withvera run examples/hello_world.verabefore concluding that Vera "isn't available." Don't assume the sandbox lacks the toolchain — try it.One caveat:
pip install verainstalls a different package from PyPI (an ERAV citizen-science library — unrelated to this Vera). Use theveralangdistribution or the GitHub source clone shown above; both install theveracommand.
What ships with it
19 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.
- .nojekyll 0 B
- .well-known/ai-plugin.json 951 B
- apple-touch-icon.png 13 KB
- CNAME 13 B
- favicon-192.png 14 KB
- favicon-32.png 1.2 KB
- favicon.ico 575 B
- github.svg 966 B
- implementation-status.md 5.2 KB
- index.html 56 KB
- index.md 20 KB
- llms-full.txt 213 KB
- llms.txt 6.4 KB
- loop-web.svg 3.3 KB
- robots.txt 188 B
- sitemap.xml 1.1 KB
- vera-bench-meerkat-only.png 48 KB
- vera-hero.jpg 82 KB
- verabench-delta-chart.png 137 KB
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.
- 2d ago First seen · 2,471 lines · 61 tokens per session scan A b9d5903395d5
vera-language is a skill published in the GitHub repository aallan/vera (411 stars, last pushed 7d ago), licensed MIT. It adds 61 tokens to every session and 32,997 once invoked, about $0.0003 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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