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BioContextAI Knowledgebase MCP

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bc_get_string_network_image

Retrieve a protein-protein interaction network image from the STRING database by providing a protein symbol and species taxonomy ID.

Instructions

Generate protein-protein interaction network image from STRING database. Always provide species parameter.

Returns: Image or dict: Network visualization as PNG image object or error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
protein_symbolYesProtein name to search for (e.g., 'TP53')
speciesYesSpecies taxonomy ID (e.g., '10090' for mouse)
flavorNoNetwork flavor (e.g., 'confidence', 'evidence', 'actions')confidence
min_scoreNoMinimum combined score threshold (0-1000)
Behavior3/5

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

No annotations are provided, so the description bears full burden. It discloses the return type (image or dict/error) and the mandatory parameter. However, it lacks details on potential side effects, authentication requirements, or rate limits. Given the simplicity of the tool, the transparency is adequate but not comprehensive.

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 extremely concise: two sentences and a return line with no extraneous information. Every part adds value, and it is front-loaded with the core purpose.

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

Completeness4/5

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

Given there is no output schema, the description adequately explains the return format (image or dict error). The tool is simple, and the description covers the essential behavioral context. It could mention the flavor and min_score parameters, but those are already fully described in the schema.

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

Parameters3/5

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

All 4 parameters have descriptions in the input schema, resulting in 100% schema coverage. The description does not add significant new meaning beyond restating the need for the species parameter. Per criteria, baseline is 3 when schema coverage is high.

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 'Generate protein-protein interaction network image from STRING database', specifying both the action and the resource. It distinguishes from sibling tools like bc_get_string_interactions (returns data) and bc_get_string_similarity_scores (returns scores), making it easy to select for visual output.

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

Usage Guidelines3/5

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

The description provides one guideline: 'Always provide species parameter.' However, it does not explicitly state when to use this tool versus alternatives like bc_get_string_interactions for data or bc_get_string_id for identifiers. The context is implied but not directly referenced.

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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