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/landing-ai/ade-cli/verifynpx skills add landing-ai/ade-cli --skill verifygit clone --depth 1 https://github.com/landing-ai/ade-cliWhat 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 | $0.00025 | $0.00402 |
| Opus 5 | $0.00013 | $0.00201 |
| Sonnet 5 | $0.00005 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
verify 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 3d 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
Verifying ade
Build/run: uv sync, then uv run ade …. Tests are offline (fake
transport); verification means driving the real CLI against a real store.
Seeding a parsed doc without the network
parse needs the API, so seed the store directly — write what parse
would have written (see parse.py::write_artifacts for the exact set):
parse.json (raw ParseResponse), parse.md, elements.json
({"job_id", "elements": elements.project(response)}), meta.json
(state: "parsed", job_id matching parse.json's metadata.job_id —
the generation gate in refs.live_parse rejects mismatches).
A ready-made seeder that also draws a matching invoice PNG (so boxes
visibly align) was used for the view verification — pattern: build
markdown piecewise so every element's range is exact, reuse
tests/parse_fixtures.py shapes.
Point the CLI at the seeded store with ADE_HOME=<dir>.
Driving view.html
The in-app browser refuses file:// — serve the doc dir instead:
python3 -m http.server 8742 --bind 127.0.0.1 in
$ADE_HOME/docs/<doc-id>/, then browse http://127.0.0.1:8742/view.html.
Deep links: append #element=<id>. Selection state is inspectable via
JS: document.querySelectorAll('.sel') (both panes share data-id).
Rebuilds are fingerprint-gated — --json reports built: true|false;
touching the source or changing --dpi forces a rebuild.
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.
- 3d ago First seen · 36 lines · 25 tokens per session scan A d6334fe1b80b
verify is a skill published in the GitHub repository landing-ai/ade-cli (2,410 stars, last pushed 14d ago), licensed Apache-2.0. It adds 25 tokens to every session and 402 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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