Google Scholar Scraper Alternative: Papers, Citations & BibTeX

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the readOnly/openWorld annotations by disclosing the execution model (runs the Apify Actor pandadad0214/literature-search on the caller's own Apify account), the billing rule ($0.003 per paper found, empty runs uncharged), and the per-call spending cap. That cost and auth-ownership context is exactly what an agent needs before invoking a paid, non-idempotent operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight paragraphs: purpose and input/output first, then execution and pricing mechanics. Every sentence carries information an agent would otherwise have to dig out of structured fields, and nothing is redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 21-parameter paid tool with no output schema, the description compensates by enumerating the returned fields (DOI, citations, PDF link, retraction flag, citation and BibTeX) and the billing model. The remaining gap is routing guidance versus sibling research tools, which is not covered here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 21 parameters at 100% schema coverage, the schema already documents every field including enums and defaults. The description only summarizes them at a high level ('query or seed DOIs plus year and citation filters') and repeats the cost note for run_max_charge_usd, adding grouping but no new per-parameter meaning. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('find real scholarly papers on a topic') plus the underlying corpus (250M+ OpenAlex works) and explicitly positions itself as a Google Scholar scraper alternative. It also names the input shape (query or seed DOIs plus year/citation filters) and the output fields, so an agent can tell this is a discovery tool rather than the citation/reference-checking siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use this to find real scholarly papers on a topic' gives a clear triggering context, and the seed-DOI framing clarifies the two operating modes (topic query vs. citation-graph exploration). It stops short of naming alternatives such as reference_checker or pubmed_evidence_table, so there is no explicit when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.