summaryLightweight lookup for a PDB entry by 4-char ID: tries the RCSB UniProt endpoint first, falls back to the core entry record. Returns title, experimental method, resolution, and deposition date without the full polymer/ligand detail of structure.
| Name | Required | Description | Default |
|---|---|---|---|
| pdb_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral details beyond the annotations by disclosing the endpoint fallback strategy ('tries the RCSB UniProt endpoint first, falls back to the core entry record') and enumerating the returned fields. The annotations already establish read-only, idempotent, and non-destructive behavior, so the additional context about the lookup mechanism is valuable and non-redundant.
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?
The description is two sentences, front-loaded with the primary purpose ('Lightweight lookup for a PDB entry by 4-char ID'), and every clause adds essential information: endpoint behavior, return fields, and relationship to `structure`. There is no redundant or filler content.
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 simple single-parameter read-only tool with an output schema, the description is complete. It covers what the tool does, how it works (endpoint fallback), what it returns, and how it relates to a sibling tool, without needing to explain return values because the output schema exists.
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?
The schema has 0% description coverage, and the description compensates by specifying the valid format ('4-char ID') and the lookup behavior associated with the `pdb_id` parameter. It gives enough semantic context for an agent to understand what value to provide, though it does not mention validation rules beyond the character count.
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?
The description uses a specific verb ('lookup') and resource ('PDB entry by 4-char ID'), and explicitly distinguishes itself from the sibling `structure` by stating it returns metadata 'without the full polymer/ligand detail of `structure`.' This makes the tool's purpose unambiguous and differentiated.
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?
The description clearly implies when to use this tool ('Lightweight lookup') and contrasts it with `structure` ('without the full polymer/ligand detail of `structure`'), giving the agent a clear choice based on need for detail. It does not explicitly state 'when not to use' or name alternative tools beyond `structure`, but the context provides sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical in purpose, and structure/summary both fetch PDB entries. The server name 'Rcsb Pdb' doesn't match most tools, which are Pipeworx data tools, compounding ambiguity.
Mostly snake_case verb_noun, but verbs are inconsistent (ask, discover, generate, list, recall) and some names are noun phrases (entity_profile, polymarket_edges). No clear pattern unifies the set.
37 tools is excessive for a server ostensibly about RCSB PDB; only 6 tools relate to PDB while 31 serve unrelated Pipeworx functionality. The count feels like a bundled grab-bag rather than a focused toolset.
The PDB-specific tools cover the core operations (search, fetch, assembly, ligand, polymer entity), so the structural biology surface is mostly complete. However, the server's overall purpose is muddled, and the Pipeworx tools are a separate domain that happens to be bundled in, making it unclear what 'completeness' even means for this server.