Literature review

A literature question has two halves: finding the papers a domain expert would point to, and turning them into something more useful than a reading list — a synthesis that says what's established, what's contested, what's new, and where the holes are. Both halves can fail quietly and look like competent output until someone checks.

Setup (any agent, no API key)

This is a pure skill — kernel.py is deterministic Python (plain HTTP/stdlib calls to CrossRef and OpenAlex) and you (the base model) do all the reasoning: the finding, the synthesis, the prose. There is no host runtime and no LLM API. Load the helpers once per session in a Python cell:

exec(open("<this skill's directory>/kernel.py").read())

Nothing auto-loads it outside Claude Science. Then call the helpers directly — verify_dois, crossref_lookup, search_openalex, expand_citations, extract_dois, style_pass. If a helper name is not defined, you haven't exec'd kernel.py.

Configuration is via environment variables, not a host — no LLM key is involved:

• OPENALEX_API_KEY — required for the OpenAlex-backed steps (search_openalex, expand_citations); free at https://openalex.org/settings/api.
• HOST_USER_EMAIL — optional contact email for the CrossRef/doi.org polite pool (falls back to git config user.email; never sent to OpenAlex).