A skill compiled once can be safely reused across tenants
Common flows — log in, search, paginate, fill a form — get compiled once and shared through a sanitized corpus, so your agents start ahead.
x-twin-skill-source: corpusWhat cross-tenant skill corpus does
Most browser tasks are not unique. A login on a popular SaaS, a checkout on a major store, a search on a public site — thousands of teams automate the same surfaces. Twin compiles those flows once and, after stripping anything tenant-specific, makes them reusable across tenants. The savings compound across the whole network, not just your own history.
Sanitized by construction
Corpus skills carry only the action structure. Credentials, inputs, and tenant data never enter the shared corpus.
Warm start on common surfaces
Your first run against a widely-automated site can dispatch from a corpus skill instead of paying a cold compile.
Network effect on cost
Every compile improves the corpus, so the marginal cost of automating popular surfaces keeps falling for everyone.
Opt-in and disclosed
Corpus reuse is explicit. You choose whether a tenant draws from and contributes to the shared corpus, and responses disclose the source.
From a goal to deterministic action
- 1Compile locallyA successful run compiles into a tenant skill first, scoped to your workspace.
- 2SanitizeA sanitizer strips inputs, secrets, and identifiers, leaving only the reusable action structure.
- 3Promote to the corpusGeneric, broadly-useful flows are promoted into the shared corpus with the source disclosed.
- 4Dispatch across tenantsOther tenants matching the same goal can dispatch from the corpus skill — a warm start instead of a cold compile.
See it on a real call
A first-time goal on a widely-automated surface dispatches from the corpus — no cold compile.
const res = await twin.agents.run({
goal: "Log in and export the last 30 days",
url: "https://dashboard.popular-saas.com",
corpus: true, // draw from the shared corpus
});
// → x-twin-cache: hit
// → x-twin-skill-source: corpus
// → x-twin-llm-calls: 0 (warm start)- Compile locallydone
- Sanitizerunning
- Promote to the corpusqueued
- Dispatch across tenantsqueued
What cross-tenant skill corpus is
The facts — how it works, what it costs, and the signal you get back on every call.
| Property | Twin Browser |
|---|---|
| Shared content | Action structure only |
| Never shared | Secrets, inputs, tenant data |
| Participation | Opt-in per tenant |
| Disclosure | x-twin-skill-source header |
| Isolation | Default-deny RLS per tenant |
| Benefit | Warm start on common flows |
Cross-tenant skill corpus — common questions
Could my data leak into another tenant through the corpus?
Do I have to participate?
How do I know when a corpus skill was used?
The rest of the platform
Semantic dispatch cache
Re-phrased goals fuzzy-match a skill you already compiled — so the second request and every one after it skips the LLM entirely.
Credential vault
Per-tenant encrypted secrets are injected into a run when a step needs them — and never enter the model, the logs, or the skill corpus.
Agent & skill library
Every compiled skill is stored, versioned, and reusable — browse them, run them directly, and share them across your agents.
Make every run cheaper than the last.
Start free, compile your first skill, and watch the marginal cost per run trend toward zero as your agents reuse what they have already learned.