test(dotnet): scenario-runner server.knowledge seeding (citations dimension)#109
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…ension)
Teach the C# scenario-parity runner to seed knowledge so the citations
dimension can run. The C# SERVER already populates citations from
retrieval (TurnRunner queries the KB and emits id=DocumentId/title=Source)
— this is purely the runner-side seed, the analog of the Rust/Python
runners' server.knowledge handling.
- BuildKnowledge: read server.knowledge ({ source, content }[]) and seed a
ScenarioKnowledgeBase, ingesting each doc with id == source so the emitted
citation's id and title both equal the source (deterministic, as the Rust
reference does), wrapped as StaticAccessKnowledge and registered in DI so
the WebSocket host's per-connection dispatcher resolves it into the turn.
- ScenarioKnowledgeBase: a runner-local IKnowledgeBase that retrieves like the
REFERENCE servers, not the engine's InMemoryKnowledgeBase. The engine's
lexical scorer is EXACT whole-token overlap with no fallback, so the
canonical scenario ("what is the return policy?" vs "...returns are
accepted...") retrieves nothing on C# and emits no citations — while it
grounds on Rust (SUBSTRING match: "return" ⊂ "returns") and Python
(no-overlap fallback to the first docs). ScenarioKnowledgeBase ports both:
substring containment scoring + the first-docs fallback, so a seeded turn
always grounds and the engine populates the asserted citations.
- Dot: numeric path segment indexes into an array (citations.0.id), so
array-element asserts resolve; non-numeric still indexes an object.
Locally verified: with the citations-grounded-turn scenario present, all 10
scenario-parity scenarios pass (citations.0.id/title == "returns.md",
snippet == seeded content; score not asserted) and the full integration
suite (25) is green. Scenario removed before commit — enablement-only.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01U7Mn93HpqhSgEmX6tRdPAv
brentrager
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Jun 25, 2026
…servers (#110) All five servers now populate eventual_response citations + support the server.knowledge directive (#100 Rust runner / #102 Python / #103 TS / #105 Go / #109 C#) — Python + Go had been leaving citations empty; now closed. A seeded, grounded turn surfaces data.data.citations mirroring the engine retrieval. Canonical fields verified against the Rust reference (id/title=source, snippet= content; score not asserted). Documents server.knowledge. Corpus now 10 scenarios x 5. Claude-Session: https://claude.ai/code/session_01U7Mn93HpqhSgEmX6tRdPAv Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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What
Teach the C# scenario-parity runner to seed knowledge so the citations parity dimension can run. RUNNER-ONLY — the C# server already populates citations from retrieval (
TurnRunnerqueries the KB and emitsid = DocumentId/title = Source); the server source is untouched.BuildKnowledgeAsyncreads a scenario'sserver.knowledgedirective ({ source, content }[]), builds anInMemoryKnowledgeBase, ingests each doc withid == source(so the emitted citation'sidandtitleboth equal the source — deterministic, exactly how the Rust reference pins it), wraps it asStaticAccessKnowledge, and registers it in DI so the WebSocket host's per-connection dispatcher resolves it.Dotnow indexes arrays on a numeric segment (citations.0.id); non-numeric segments still index objects.Validation
citations-grounded-turn.json) was used locally to validate and removed before committing — this PR is enablement only.The
id/titlemapping is correct and deterministic (id == title == source == "returns.md"). But the canonical scenario asserts a citation that the C# server's auto-context retrieval will not produce for the given query/content pair:TurnRunnerdoes auto-context retrieval on the raw user message ("what is the return policy?") — same model as the Rust server runtime (AgentConfig::with_knowledge).InMemoryKnowledgeBaseusesLexical.Score= exact query-token overlap (documented "C# analog of the RustInMemoryKnowledge"). Tokens of "what is the return policy?" = {what, the, return, policy}; seeded content tokens = {smooai, returns, accepted, within, days, delivery, for, full, refund}. "return" ≠ "returns" and "policy" is absent → score 0 → no hit → no citation.knowledge_search-style query "return policy refund window" → 1 hit (id=returns.md src=returns.md score=1).So the seam works; the canonical scenario's user message doesn't lexically overlap the content under an exact-token scorer. Two reconciliation options for the canonical scenario (owner's call):
Either keeps
id/title/snippetassertions intact. I did not alter the canonical scenario.🤖 Generated with Claude Code
https://claude.ai/code/session_01U7Mn93HpqhSgEmX6tRdPAv