Phdtaketaketake

Evidence-first PhD advisor matcher — scores connection strength on a 4.0 scale, not h-index.

par powerofjinbo · powerofjinbo/phdtaketaketake

Testé · Fonctionne ★ 9.6/10

Phdtaketaketake — Evidence-first PhD advisor matcher — scores connection strength on a 4.0 scale, not h-index.

Ce que fait

Ranks candidate PhD advisors for a student profile using a deterministic 5-pillar (Connection/Advisor/Publication/Experience/GPA) scoring pipeline, with a hard 'no fabricated evidence' contract enforced by a --strict-evidence flag. Triggers on requests to score PhD application chances, find matching advisors, or rank professors by connection-first fit; also ships a parallel LaTeX CV-formatting sub-workflow.

Rapport de test

Ran the bundled physics_hep_audit_demo fixture through scripts/match.py for real (fresh venv, pydantic+pyyaml only) and got a deterministic, confidence-banded ranking (application_strength 3.30/2.76/2.68, bands ±0.58) with a full missing/unsourced-signal audit — a baseline unaided ranking has no such quantified uncertainty and would very likely cite unverifiable connections as fact, which is exactly what this skill's evidence contract forbids.

Testé le: 2026-07-14 · Claude Code 2.x (agent harness)

Installation

git clone https://github.com/powerofjinbo/phdtaketaketake
cd phdtaketaketake
mkdir -p ~/.claude/skills
cp -r . ~/.claude/skills/phdtaketaketake

Commandes et exemples de prompts

/phdtaketaketakeEvidence-first PhD advisor matcher — scores connection strength on a 4.0 scale, not h-index.

Les skills se déclenchent sur des demandes en langage courant — aucune commande à retenir. Après installation, des prompts comme ceux-ci l'activent (en anglais) :

Match me with PhD advisors who actually fit my research
Score how well this professor's work connects to my topic
Find supervisors for my HEP thesis with evidence, not rankings

Rapport complet →