Add a reproducible retrieval benchmark with at least 30 queries

Aperta
  • Qualcosa non va?
#46 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

I maintainer di solito rispondono entro 1 giorno

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
35/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
javascript, node.js
Ambito
ai-infra-agents, search

Direzione di ricerca

Read AGENTS.md, docs/PROJECT_CONTEXT.md, and the prerequisite issues #45 and #40; their dependent contracts must land before implementation, and the design should be discussed with the maintainer first. Then inspect the synthetic reference corpus, retrieval docs, and existing authorization, safe-error, and synthetic-fixture patterns to identify the benchmark entry point. Done means at least 30 MK/EN/SQ queries with explicit normalization, expected evidence and deterministic metrics, plus documented baseline scores and limits; the stated release target is at least 90% top-five retrieval for answerable queries with valid source references.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

area:backend area:docs priority:medium status:blocked type:feature

Part of #28 · Target: Release readiness / v1

Goal and scope

Define at least 30 realistic answerable/unanswerable retrieval queries over the synthetic corpus, expected evidence and deterministic metrics. Record baseline scores and include MK/EN/SQ cases with explicit supported normalization.

Implementation starting points

synthetic reference corpus, new benchmark command, retrieval docs. Follow AGENTS.md and docs/PROJECT_CONTEXT.md; reuse existing authorization, safe-error and synthetic-fixture patterns. New runtime dependencies need a documented reason.

Dependencies and readiness

Depends on #45, #40. Discuss the design before starting implementation; dependent contracts must land first.

Out of scope

No faculty credential requirement, private query telemetry or fabricated passing scores.

Acceptance criteria and test plan

At release, at least 90% of answerable queries retrieve expected evidence in top five and all results have valid source references. Unanswerable/partial-scope cases remain explicit. Benchmark fails clearly on regressions and documents limits rather than claiming general AI accuracy.

Run the relevant offline tests, npm run check and git diff --check; runtime changes also require npm test and npm audit. Report checks not run. No faculty credentials or private course material are required for a contribution.

Contributing

Comment here before starting so the maintainer can coordinate the approach and avoid duplicate work. Fork the repository, branch from master, and open a focused PR referencing this issue. No assignee or delivery deadline is set; required checks and review apply.

Lingua principale
JavaScript
Stelle
0
Fork
0
Merge medio
1h 25m
PR unite (30g)
13

Preparare l'ambiente

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di mahmutmft/courses-mcp

Tutte le issue di mahmutmft/courses-mcp

Issue simili

Altre issue su JavaScript

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.