Capstone: research bot with citations
Measure groundedness and citation validity
Executable checks prove claim without evidence → abstain or drop claim; no orphan sentences on fixtures — including the known misshape behind CAP-RESEARCH-FAKE-ID-3.
1Learn the idea
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Schema and policy checks
Add executable validation at the trust boundaries of citation-first research assistant that maps every claim to evidence IDs. Reject unknown fields where they matter, bound string sizes, and coerce only after auth/signature checks when raw bytes are security-relevant. Invariant under test: claim without evidence → abstain or drop claim; no orphan sentences. A TypeScript type or Python annotation is not runtime validation — pair them with parsers.
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Golden and adversarial fixtures
Automate the fixtures from setup, including a recreation of CAP-RESEARCH-FAKE-ID-3. Assert both the visible error and the absence of side effects (no provider call, no queue write, no flag flip). Where metrics matter, assert label enums stay bounded.
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Implementation artifact
assert fabricated_id_rate(brief, CORPUS) == 0
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Gate semantics
Document which failures are client mistakes (4xx) versus operator/config mistakes (5xx/503). Oracle still stands: brief on fixture corpus: ≥ 0.95 claims cited; fabricated ID rate 0. Validation should make accidental “success with empty body” impossible for analyst compiling a brief on bike-share policy from a fixed corpus.
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Stage depth
Property ideas: shuffled field order, Unicode edges, maximum-length strings, and replayed timestamps. Where money, identity, or citations matter, assertion messages should cite the field name. Do not snapshot entire provider payloads in tests; assert semantically. If validation fails open “to keep the demo working,” you have inverted the lab. Tie at least one CI job to the CAP-RESEARCH-FAKE-ID-3 fixture so main cannot regress silently. Re-read claim without evidence → abstain or drop claim; no orphan sentences after each new parser — convenience helpers love to bypass it.
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Field notes for `capstone-research-bot` / `validation`
Table-drive status codes and error codes so reviewers see coverage at a glance. Include a Unicode normalization case if user text is accepted. Verify that oversized bodies fail before CPU-heavy work. Where digests or versions are pinned, assert mismatch behavior. Keep golden files small enough to read in review. CI should fail on skipped tests that mark the incident fixture as xfail without a ticket link. In this chapter the product is citation-first research assistant that maps every claim to evidence IDs, the human stakeholder is analyst compiling a brief on bike-share policy from a fixed corpus, and the incident id you design against is CAP-RESEARCH-FAKE-ID-3. Re-state the oracle in your notes — brief on fixture corpus: ≥ 0.95 claims cited; fabricated ID rate 0 — and keep the invariant visible: claim without evidence → abstain or drop claim; no orphan sentences. Track claim_citation_coverage and fabricated_id_rate as the scoreboard. Surface under change control: POST /v1/research/brief. If you only have forty minutes, finish the fixture for model invents kb://minutes-2099 citation before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.
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Why this matters
List three fixtures: one golden success, one schema/auth reject, and one regression for CAP-RESEARCH-FAKE-ID-3. For each, write the exact assertion (status, code, metric, or citation) that must turn red if broken.
Capstone gold tests stay versioned beside the app so brief on fixture corpus: ≥ 0.95 claims cited; fabricated ID rate 0 remains reproducible.
In the wild
See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.
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