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# End-to-end examples
Each example is self-contained. Artifacts land under
`<target>/.openultrasast/runs/<scan-id>/` and `.openultrasast/` is gitignored.
## 1. Quick scan a local repo (deterministic, no keys)
```bash
uv run ousast scan /path/to/code --mode quick
run = /path/to/code/.openultrasast/runs/<scan-id>
cat " $run /report.md" # findings + evidence (secrets redacted)
jq . " $run /score.json" # 0– 100 project score + gate verdict
" $run /report.sarif" # SARIF for code-scanning / IDEs
```
## 2. CI gate
```bash
# Fail the build on any evidence-verified finding:
uv run ousast scan . --mode quick --fail-on verified
# The hard detection gate (>=90% recall, <10% FP), score-independent:
uv run python -m openultrasast.gate
```
## 3. Benchmark a known-vulnerable corpus
```bash
uv run ousast benchmark benchmarks/manifests/python-vulnerable.toml --mode quick
# -> expected / matched / missed counts + a per-rule recommendation delta
```
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## 4. Vuln vs fixed pair eval (efficiency, not cheat-sheet recall)
```bash
uv run ousast pairs # local fixtures + vendored GitHub VFCs
uv run ousast pairs --slice github --json # honesty dashboard as JSON
uv run ousast pairs --slice sast # OWASP Benchmark + Juliet Youden (TPR-FPR)
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uv run ousast pairs --slice vibe-py --pointers # nightly: pointer pairs via the local cache (network)
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uv run ousast mechanisms export --slice vibe-py # maintainer: seed mechanism candidates from trusted pairs (offline)
uv run ousast improve bench.toml --pair-catalog benchmarks/pairs/catalog.toml # the mechanisms lever admits candidates the holdout pairs prove; the scan then searches them
uv run ousast pairs --slice vibe-py --loo # leave-one-out: the corpus's own detection rate (reports/loo.json)
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uv run python -m openultrasast.pair_gate # CI: local pairs must all pass
```
Each case is two isolated trees (vuln file vs patched file, same relative path).
`pair_correct` means the harness fired on the vuln side and stayed silent on the
fix. Misses and fix-side leaks become `miss` /`fp` signals for `ousast improve` .
The catalog and public dataset pointers live in `benchmarks/pairs/` .
## 5. Self-improve the ruleset from benchmark feedback
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```bash
uv run ousast improve benchmarks/manifests/java-spring-boot-vulnerable.toml --dry-run # preview
uv run ousast improve benchmarks/manifests/java-spring-boot-vulnerable.toml # apply
# Accepted edits land in <target>/.openultrasast/calibration/rule_policy.json,
# which the next scan/benchmark of that target loads automatically.
```
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## 6. Standard mode with the HarnessX agentic plane (OpenAI)
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```bash
uv sync --extra harnessx
export OPENAI_API_KEY = sk-...
cat > openultrasast.toml <<'TOML'
[models]
hunter = "gpt-4o"
verifier = "gpt-4o"
[harnessx]
provider = "openai"
max_cost_usd = 2.0
token_threshold = 120000
[fusion]
panel_model = "gpt-4o" # two-panel adjudication on triggered findings
[hardening]
redact_secrets = true
max_findings = 0
TOML
uv run ousast scan /path/to/code --mode standard --config openultrasast.toml
jq '.degradations' " $run /manifest.json" # null = HarnessX ran; entries = it fell back
jq '.fusion' " $run /manifest.json" # per-finding dispositions
```
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## 7. Drive it from an MCP client (OpenCode / IDE)
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```jsonc
{ "command" : "uv" , "args" : [ "run" , "ousast" , "mcp" ] }
```
Then: `openultrasast.scan {path}` → `run_dir` → `openultrasast.findings {run_dir}` →
`openultrasast.explain {run_dir, finding_id}` . See the README "MCP server" section.