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scholar-mentions-log

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Mis à jour24 juin 2026 à 18:25

A monthly routine for scholars: search the web for recent mentions, press, talks, and citations of a named researcher and their work, then append the genuinely-new ones to a CSV (date logged, date published, title, source, URL, one-line description) — deduped against what's already there. Use when a researcher wants to track who is talking about them and their work over time, with links they can skim later.

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timothyfraser

timothyfraser/systems-ai-workshop

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Enseignants postsecondaires, autresEnseignement et bibliothèques·SOC 25-1199

SKILL.md

readonly

name

scholar-mentions-log

description

Scholar mentions log (monthly routine)

Goal

Keep a running CSV of who is mentioning a scholar and their work — news, blogs, talks, syllabi, citations — so they can skim it once a month with links and short descriptions. Built to be re-run on a schedule without creating duplicates.

Inputs (ask if not given)

Who: full name, common variants/initials, and affiliation or field (to disambiguate from other people with the same name).
Window: how far back to look (default: the last 60 days).
CSV path: default 01_claude/examples/mentions.csv.

Steps

Search the web for recent mentions: the name (and variants) alongside the affiliation/field, plus titles of their well-known work. Use several queries, not one.
Disambiguate. Keep only items that are plausibly about this person. When unsure, keep it but flag the uncertainty in the description (e.g. "(possible match)"). Never pad the list with unrelated hits.
Read the existing CSV (if present) and dedupe — skip anything whose URL (or near-identical title) is already logged.
Append one row per new mention with these columns: date_logged, date_published, title, source, url, description
- date_logged = today's date (the user can supply it; don't invent a clock).
- date_published = the item's date if known, else blank.
- description = one neutral sentence: what it is and how it mentions them.
Summarize in chat: how many new items, and the 2–3 most noteworthy.

Cadence

Run it monthly — set a calendar reminder, or schedule it if your Claude supports scheduled tasks/routines. Each run only adds what's new.

Guardrails

Never fabricate URLs or sources. If you can't find the link, don't log the row.
Prefer primary sources over aggregators when both exist.
Don't log paywalled items you can't verify are about them.
This is a log to skim, not a citation report — keep descriptions short and factual.

CSV header

date_logged,date_published,title,source,url,description

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name

scholar-mentions-log

description

Scholar mentions log (monthly routine)

Goal

Inputs (ask if not given)

Who: full name, common variants/initials, and affiliation or field (to disambiguate from other people with the same name).
Window: how far back to look (default: the last 60 days).
CSV path: default 01_claude/examples/mentions.csv.

Steps

Search the web for recent mentions: the name (and variants) alongside the affiliation/field, plus titles of their well-known work. Use several queries, not one.
Disambiguate. Keep only items that are plausibly about this person. When unsure, keep it but flag the uncertainty in the description (e.g. "(possible match)"). Never pad the list with unrelated hits.
Read the existing CSV (if present) and dedupe — skip anything whose URL (or near-identical title) is already logged.
Append one row per new mention with these columns: date_logged, date_published, title, source, url, description
- date_logged = today's date (the user can supply it; don't invent a clock).
- date_published = the item's date if known, else blank.
- description = one neutral sentence: what it is and how it mentions them.
Summarize in chat: how many new items, and the 2–3 most noteworthy.

Cadence

Run it monthly — set a calendar reminder, or schedule it if your Claude supports scheduled tasks/routines. Each run only adds what's new.

Guardrails

Never fabricate URLs or sources. If you can't find the link, don't log the row.
Prefer primary sources over aggregators when both exist.
Don't log paywalled items you can't verify are about them.
This is a log to skim, not a citation report — keep descriptions short and factual.

CSV header

date_logged,date_published,title,source,url,description