Quality
Each correction of yours is a confirmed error of the system. Golden questions guard against regression when changing prompts, models or schema.
Value: what it costs and what reaches the LLMs
Honest cost, from the measurement method (docs/measuring-value.md). Maintain = having the knowledge (ingestion, synthesis, sweep); serve = delivering it (the push); measure = golden questions. Database queries only, no LLM.
{% for mo in val.months %}{% if mo.total > 0 %}| Source | Cost to maintain | Current claims | Reached an LLM | Cost per claim that reached | |||
|---|---|---|---|---|---|---|---|
| {{ s.label }} | US${{ '%.2f'|format(s.usd) }} | {% if s.shared %}serves all sources; not divided by claim | {% else %}{{ s.living }} | {{ s.delivered }}{% if s.living %} ({{ '%.0f'|format(100 * s.delivered / s.living) }}%){% endif %} push {{ s.by_push }} · MCP {{ s.by_mcp }} | {{ ('US$%.3f'|format(s.usd_per_delivered)) if s.usd_per_delivered is not none else '—' }} | {% endif %}||
By role
| {{ r.role }} | {{ r.bucket }} | US${{ '%.2f'|format(r.usd) }} | {{ r.calls }} calls |
What these numbers do not count
- {% for c in mo.coverage %}
- {{ c }} {% endfor %}
This is a floor: it counts only when the assistant cites the ID (of the page or of a claim it cited) or opens the reference through the MCP after the push. When it uses the content without citing it, it does not show up here; that is measured by the judge of step 0.4.
{% else %}Could not read the Claude Code transcripts.
{% endif %}Judge: {% if rx.agreement.n %}agrees with you on {{ '%.0f'|format(100 * rx.agreement.agree) }}% of {{ rx.agreement.n }} messages{% if rx.agreement.kappa is not none %} (kappa {{ '%.2f'|format(rx.agreement.kappa) }}){% endif %}{% else %}not validated yet{% endif %} · validate (label ~30 messages). Until it is validated, treat the numbers as provisional.
By session
| Start | Chat | Messages | Assert | In the push | Not delivered | New | Tokens until edit | Exploration until edit |
|---|---|---|---|---|---|---|---|---|
| {{ s.started_at|dt }} | {{ s.chat_title or '—' }} | {{ s.user_messages }} | {{ s.asserts }} | {{ s.avoidable_delivered }} | {{ s.avoidable_not_delivered }} | {{ s.new_context }} | {{ ('%.0fk'|format(s.tokens_until_edit / 1000)) if s.tokens_until_edit else '—' }} | {{ s.explore_until_edit if s.explore_until_edit is not none else '—' }} |
Not measured yet.
{% endif %}Spend per day (last 14 days; no projection, because backfills are one-off spends)
| Day | Maintain | Serve | Measure | Total |
|---|---|---|---|---|
| {{ d.day.strftime('%m/%d') }} | US${{ '%.2f'|format(d.maintain) }} | US${{ '%.2f'|format(d.serve) }} | US${{ '%.2f'|format(d.measure) }} | US${{ '%.2f'|format(d.total) }} |
{{ m.verdicts_reverted }} of {{ m.verdicts_total }} automatic verdicts reverted or overridden
Conflict and drift detectors
Whoever accuses is not whoever judges: of each suspicion raised, how many the adjudicator confirmed.
| Detector | Suspicions | Judged | Confirmed | Precision | Verdicts reverted by you |
|---|---|---|---|---|---|
| {{ d.label }} | {{ d.total }} | {{ d.judged }} | {{ d.confirmed }} | {% if d.precision is not none %}{{ '%.0f%%'|format(d.precision * 100) }} (95% CI: {{ '%.0f'|format(d.low * 100) }}–{{ '%.0f'|format(d.high * 100) }}%{% if d.few %}; few cases, n={{ d.judged }}{% endif %}){% else %}—{% endif %} | {{ d.reverted }} |
| No suspicion yet. | |||||
Sweep: latest reviews
| When | Entity | Suspicions | Investigated | Conclusion | Cost |
|---|---|---|---|---|---|
| {{ r.reviewed_at|dt }} | {{ r.name }} ({{ r.type }}) | {{ r.suspicions }} | {{ r.investigated }} | {% if r.inconclusive %}Inconclusive: {{ r.failed|length }} read(s) failed ({{ r.failed[0].failed }}); back in the rotation tomorrow. {% endif %}{{ r.summary or '—' }} | {{ r.cost_usd|money }} |
| The sweep has not run yet. | |||||
Golden questions
Written from the text of the sources (never from what Pythia extracted), by kind, with half sealed (it only decides; nothing is tuned by looking at it). The battery runs Pythia {{ repeats }} times (mean and range), a baseline without Pythia (an LLM with text search over the sources) and checks that the judge fails plausible wrong answers. Prompt or model changes run Pythia only once.
Latest battery · {{ b.runs[0].started_at|dt }} {% if not b.done %}in progress{% endif %}
| Kind | Questions | Pythia (mean, range) | Without Pythia | Evidence recall |
|---|---|---|---|---|
| {{ k.label }} | {{ k.n }} | {% if k.pythia %}{{ '%.0f'|format(100 * k.pythia.mean) }}% ({{ '%.0f'|format(100 * k.pythia.min) }}–{{ '%.0f'|format(100 * k.pythia.max) }}%, {{ k.pythia.n }} run(s)){% else %}—{% endif %} | {% if k.baseline %}{{ '%.0f'|format(100 * k.baseline.mean) }}%{% else %}—{% endif %} | {% if k.recall %}{{ '%.0f'|format(100 * k.recall.mean) }}%{% else %}—{% endif %} |
Judge: {% if b.judge.n %}approved {{ b.judge.fooled }} of {{ b.judge.n }} plausible wrong answers{% if b.judge.fooled %} (each one is a judge error){% endif %}{% else %}no check yet{% endif %}. Cost: Pythia US${{ '%.2f'|format(b.costs.pythia) }}{% if b.cost_per_correct %} (US${{ '%.3f'|format(b.cost_per_correct) }} per correct answer){% endif %} · baseline US${{ '%.2f'|format(b.costs.baseline) }}.
{% if b.regressions %}Latest run {{ r.started_at|dt }} ({{ r.arm }}, {{ r.config.reason or 'manual' }}) — {{ r.passed }}/{{ r.total }} {{ '(in progress)' if r.status == 'running' }}
| {{ 'passed' if x.passed else 'failed' }} | {{ x.question }} {{ x.kind or '' }}{% if x.sealed %} · sealed{% endif %} expected: {{ x.expected }} {{ x.answer }} {{ x.rationale }} |
Registered ({{ questions|length }} active)
| {{ q.question }} {{ q.kind or '' }}{% if q.sealed %} · sealed{% endif %} | {{ q.expected }} |