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search_pdb_entity

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Search PDBj for structures, chemical components, or BIRD molecules. Retrieve detailed fields: experimental method, resolution, bound ligands, formula, SMILES, and citation.

Instructions

Search PDBj for structures, chemical components, or BIRD molecules.

Returns rich, named fields per hit (not just the title) — for pdb, each result carries the experimental method, resolution, bound ligands, and citation; for cc, the formula, SMILES, and InChI.

RETURNS a JSON string {"total": int | null, "results": [ {…fields…} ]}. total is null when PDBj gives no count (typical for structured-filter searches) — that is NOT zero and does NOT mean "no results"; consult results directly. On upstream/HTTP failure returns a JSON object with an error key instead — CHECK FOR error BEFORE reading results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbYesThe database to search in. Allowed values are: - "pdb" (Protein Data Bank, macromolecular structures) - "cc" (Chemical Component Dictionary, ligands / small molecules) - "prd" (BIRD, Biologically Interesting Reference Molecule Dictionary, mostly peptides).
nameNo
termNo
limitNoMax results to return, in [0, 500]. Default 20.
queryNoFree-text keywords. May be empty when at least one structured filter is supplied. Accepts aliases: `search`, `term`, `keyword`, `keywords`, `search_term`, `name`. If both `query` and an alias are given with different values, this raises ValueError (pass only one).
ligandNo
methodNo
offsetNoNumber of leading results to skip (server-side pagination). Default 0.
searchNo
smilesNo
sourceNo
formulaNo
keywordNo
res_maxNo
res_minNo
keywordsNo
search_termNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds meaningful context: it explains the return format (rich named fields), clarifies that a null total does not mean zero results, and warns about error key checking. This goes beyond the annotations and is valuable for safe invocation.

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

Conciseness5/5

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

The description is concise, well-structured, and front-loaded with the purpose. It uses clear formatting (capitalized key sections) and highlights critical caveats like total null and error handling in a readable way, with no wasted words.

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

Completeness2/5

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

Given the tool's complexity (17 parameters) and low schema coverage, the description lacks essential parameter guidance. While it thoroughly explains the return format (aided by the output schema), it does not explain how to use most search filters or constraints, making correct invocation difficult for an agent.

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

Parameters2/5

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

Schema description coverage is only 24% (4 of 17 parameters have descriptions). The tool description does not compensate; it only briefly mentions the 'db' parameter and focuses on output format. Many parameters like 'name', 'ligand', 'res_min', 'res_max', 'source' remain undocumented, leaving users to guess their meaning and usage.

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

Purpose5/5

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

The description clearly states it searches PDBj for structures, chemical components, or BIRD molecules, using specific verbs ('Search') and resource types ('PDBj', 'structures', 'chemical components', 'BIRD molecules'). This distinguishes it from sibling tools like search_uniprot_entity or search_reactome_entity, which target other databases.

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

Usage Guidelines4/5

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

The description implicitly indicates usage for PDBj-specific searches, but does not explicitly state when to use this tool versus alternatives or provide exclusions. It does mention the supported database types, which gives context, but lacks a direct 'use when' statement.

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

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