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/seqra/opentaint/run-scannpx skills add seqra/opentaint --skill run-scangit clone --depth 1 https://github.com/seqra/opentaintWhat 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 | $0.00032 | $0.01066 |
| Opus 5 | $0.00016 | $0.00533 |
| Sonnet 5 | $0.00006 | $0.00213 |
| Haiku 4.5 | $0.00003 | $0.00107 |
Grade A, and why
run-scan 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Run Scan
Run an OpenTaint scan over the project model and collect its findings
Inputs
Provided by the caller, fall back to the default value when omitted. Ask back only when a required input is missing and has no sensible default
project-root(optional) — root of the target project. Opentaint keeps all analysis artifacts under the fixed<project-root>/.opentaint/directory, so every.opentaint/...path below resolves there. Default: current directoryrule-ids(optional) — full rule IDs to restrict the scan tomax-memory(optional) — a--max-memoryvalue to run scan with. Default: unset (engine default8G)
Workflow
1. Run the scan
Scan the pre-built model at .opentaint/project. Write the report to .opentaint/results/report.sarif and load both the built-in ruleset and the project's own rules under .opentaint/rules:
opentaint scan --project-model .opentaint/project \
-o .opentaint/results/report.sarif \
--ruleset builtin --ruleset .opentaint/rules \
--track-external-methods
--rule-id <full-id>— restrict to specific rules (repeatable, one per input rule ID); every unnamed rule is dropped, including libraryrefs, so list every id the restricted rules depend on. Omit to run all loaded rules--passthrough-approximations .opentaint/pass-through— add when that directory exists: passThrough configs override built-ins at the rule level, a provided rule overriding a built-in only when it matches one--dataflow-approximations .opentaint/dataflow— add when that directory exists: code-based approximations (sources auto-compiled; pre-compiled.classdirs passed through as-is)
Both approximation-dir flags walk their trees recursively; pass each parent directory once, not every package or batch separately.
The scan is long — run it in the background and wait for it to finish. Leave --timeout at the engine default (900s); the CLI ends the analysis itself and writes whatever SARIF it has.
2. Retry once on out-of-memory
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 · 73 lines · 32 tokens per session scan A b27a839e0a19
run-scan is a skill published in the GitHub repository seqra/opentaint (149 stars, last pushed 4d ago), licensed Apache-2.0. It adds 32 tokens to every session and 1,066 once invoked, about $0.0002 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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