async-learning-teacher
Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user…
Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when
$ npx -y skills add tamdogood/builder-essential-skills --skill paper-opportunity-radar --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/paper-opportunity-radarContext preview
The summary Claude sees to decide when to auto-load this skill.
Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when
name: paper-opportunity-radar description: Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when asked to monitor papers every day, mine buried research, evaluate whether a paper is credible or reproducible, find unimplemented research ideas, or separate promising work from hype, weak evidence, and retracted or contradicted results. metadata: effort: high
Treat the literature as an evidence base to traverse over time, not a feed to summarize. Build a cumulative corpus, audit important papers at claim level, look for what happened after publication, and turn only defensible gaps into testable opportunities.
This skill runs when invoked. It does not silently create a background scheduler. If the user wants a daily cadence, preserve resumable state and give their scheduler the recurring prompt in [Daily Operation](#daily-operation). Never say monitoring is active until a recurring job actually exists.
databases, query strings, dates, languages, document types, and traversal cursor. Say "all records returned by this protocol," not "all papers ever."
fetched source. Mark interpretations as `INFERENCE` and gaps as `UNKNOWN`.
Independent replication, convergent evidence, or real-world validation is a separate evidence layer.
`RETRACTED`, `CORRECTED`, or `FORMAL MISCONDUCT FINDING` only when the publisher, institution, court, or regulator supports that status.
author reputation, and code availability are signals to inspect, never proof.
how, and when prior art was searched and use `NOT FOUND IN SEARCH`.
confidence, implementation feasibility, and real-world value. Never average them into one score that hides a fatal weakness.
Require a **topic**. Infer the remaining inputs when safe:
monitor scientific progress;
Ask one concise question only when the topic is missing or a domain ambiguity would materially change the corpus. Otherwise state the inferred scope and begin. For medical, legal, safety-critical, or investment decisions, describe the work as research analysis and identify where a qualified professional is needed.
Use the user's requested location. Otherwise use `research/paper-opportunity-radar/<topic-slug>/` and keep:
scope.md Stable boundary, query atlas, and run policy search-log.md Exact source/query/filter/time/result log corpus.tsv Deduplicated paper inventory and queue opportunity-ledger.md Living opportunities, blockers, and verdicts papers/<canonical-id>.md One deep-audit dossier per paper reports/YYYY-MM-DD.md Detailed daily report
Use DOI as the canonical ID when available, then PMID/arXiv/other repository ID, then a normalized title-year hash. `corpus.tsv` must include:
paper_id title year canonical_url discovered_at discovery_source status relevance evidence_verdict next_action
Allowed status values are `discovered`, `triaged`, `queued`, `audited`, `monitor`, and `excluded`. Never overwrite a prior report. Update living files atomically and preserve user edits.
Write the topic as:
1. the core phenomenon, mechanism, or problem; 2. synonyms, former names, acronyms, and neighboring terminology; 3. inclusion and exclusion rules; 4. the opportunity decision the research should inform; 5. what evidence would make a paper or opportunity uninteresting.
Read [references/discovery-protocol.md](references/discovery-protocol.md), then write the query atlas and source plan to `scope.md`. If the topic is huge, partition it by mechanism or use case. Do not silently narrow it.
Read `scope.md`, the most recent report, unresolved paper dossiers, `opportunity-ledger.md`, and `corpus.tsv`. Resume the recorded source cursor and backfill window. On the first run, create these files and label the historical corpus `BASELINE IN PROGRESS` until every planned source/time band has been visited.
Every daily run covers:
and later implementations connected to high-value or disputed papers.
Use at least two independent scholarly indexes plus one domain index when one exists. Search exact terms, controlled vocabulary, mechanism synonyms, and application language. Record every exact query, filter, timestamp, result count, new-paper count, and limitation in `search-log.md` before changing lanes.
Deduplicate before screening. A database hit is not a paper read. Triage every new candidate for
A repository for skills that are essential to my daily work
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