Skip to main content
Glama

UK Data: Science formulas

calculate_cell_density

Read-onlyIdempotent

Calculates cell density (cells per mL) from optical density (OD) measurement and dilution factor. Formula: OD × dilution × factor (default 1e9 cells/mL per OD unit, organism-dependent). (cost: 1 credit)

Input Schema

NameRequiredDescriptionDefault
odNonumber, required, optical density measurement, absorbance units, no default
factorNonumber, optional, cells/mL per OD unit, default 1e9
dilutionNonumber, required, dilution factor, fold dilution, no default

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuinely new behavioral context: the exact formula applied, the default conversion constant's organism dependence, and a cost of 1 credit — none of which appear in structured fields.

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

Conciseness4/5

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

Two compact sentences plus a short cost tag; the output unit and formula are front-loaded before the caveat. No filler, though the formula restates the multiplicative relationship in a slightly redundant way alongside the parameter list.

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?

For a pure read-only calculation with fully documented parameters and no output schema, the description supplies everything needed to invoke it correctly, including the default constant and its caveat. It only omits minor practical notes such as the valid linear range for OD readings.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline would be 3, but the description goes further by showing how the three parameters combine multiplicatively and flagging that factor is the organism-specific tuning knob. That relational meaning is not derivable from the per-field schema text alone.

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

Purpose4/5

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

States a specific verb and resource ("calculates cell density (cells per mL)") plus the exact inputs it consumes, so the agent knows precisely what it produces. It does not mention the closely related sibling calculate_bacterial_growth, so differentiation is left to inference.

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?

Usage is implied by the named inputs (OD reading plus dilution factor), and the note that the factor is "organism-dependent" hints at when to override the default. There is no explicit guidance on when to prefer this over calculate_bacterial_growth or what conditions make the formula invalid.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources