semantic-scholar
v1.0.0Search, retrieve, and organize scholarly metadata with the Semantic Scholar APIs. Use when Codex needs to find papers or authors, build paper sets from compl...
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bySiyu Liu@grenzlinie
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the included scripts and references: Graph API, Recommendations API, Datasets API workflows are implemented or documented. All request URLs point to api.semanticscholar.org and the scripts implement search, batch fetch, recommendations, and dataset guidance—functions consistent with the description.
Instruction Scope
SKILL.md and the scripts limit operations to calling Semantic Scholar endpoints, writing JSONL/CSV outputs, and handling retries/pagination. The instructions do not ask the agent to read unrelated host files or exfiltrate secrets. The scripts preserve raw output before flattening as recommended.
Install Mechanism
There is no registered install spec (skill is effectively delivered as code). The Python scripts declare typical Python deps (requests, optional pandas) but the registry metadata doesn't declare dependency installation; the scripts themselves include comments like 'pip install requests pandas'. This is not malicious but means dependencies must be installed manually. The smoke-test script expects an unlisted 'uv' CLI tool to exist (see environment note).
Credentials
Scripts optionally read SEMANTIC_SCHOLAR_API_KEY via environment; that is expected and proportionate for an API client. Registry metadata lists no required env vars; this is acceptable because the API key is optional in code, but users should be aware the key increases rate limits. No unrelated credentials or secrets are requested.
Persistence & Privilege
Skill does not request always:true, does not modify other skills or global agent config, and only writes its own output files. Autonomous invocation is allowed by default (platform normal) but combined with the rest of the footprint does not introduce unusual privilege.
Assessment
This skill appears to do what it says: query Semantic Scholar and save results. Before installing/running: (1) Review and install Python dependencies (requests; pandas only if you need CSV export). The skill has no automated install step. (2) If you want higher rate limits or repeated/bulk jobs, set SEMANTIC_SCHOLAR_API_KEY in your environment; the scripts look for x-api-key but will run without it (with lower limits). (3) The provided smoke-test expects an external 'uv' command (not documented in registry metadata); you don't need to run the smoke-test if 'uv' is unavailable. (4) The scripts perform network requests to api.semanticscholar.org and write JSONL/CSV files to disk—inspect outputs and running directory before sharing them. (5) If you plan to use the Datasets API or large bulk downloads, confirm storage/bandwidth expectations first. Overall: coherent and consistent with the stated purpose, but install/runtime dependencies should be manually verified before execution.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.