Physics MCP Server

by IBM

Overview Schema Related Servers Score Discussions

Python

Hybrid

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.5.1
Disambiguation3/5
Most tools have distinct purposes, but there is significant overlap in the calculation category, such as multiple collision tools (elastic_collision, elastic_collision_3d, inelastic_collision_3d) and projectile tools (calculate_projectile_motion, calculate_projectile_with_drag). Descriptions help differentiate, but an agent might struggle to choose between similar tools without careful reading.
Naming Consistency5/5
Tool names follow a highly consistent snake_case pattern with a clear 'verb_noun' structure, such as 'calculate_force', 'add_rigid_body', and 'check_collision'. There are no deviations in naming conventions across all 62 tools.
Tool Count2/5
With 62 tools, the count is excessive for a single server, making it overwhelming and difficult to navigate. While the domain is broad, the toolset feels bloated with many specialized calculations that could be consolidated, leading to a heavy and confusing interface.
Completeness5/5
The toolset provides comprehensive coverage of physics simulation and calculations, including simulation management (create_simulation, step_simulation), rigid body dynamics, orbital mechanics, fluid dynamics, and various checks (equilibrium, conservation). There are no obvious gaps for the stated purpose of a physics server.
Average 4.5/5 across 62 of 62 tools scored. Lowest: 3.6/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 28 commits in the last 12 weeks
- Last stable release on December 1, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return format (vector and magnitude) and provides an example, but does not mention side effects, error conditions, or behavior for edge cases like zero moment of inertia. The conservation context is informative but not behavioral.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat verbose, including educational tips and a detailed example that could be shortened. However, it is well-structured with sections for Args, Returns, Tips, and Example, aiding readability.
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 the lack of output schema and annotations, the description provides sufficient context: parameter details, return format, a concrete example, and educational notes on conservation. It covers most aspects needed to use the tool correctly, though error handling and precision are not addressed.
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?
The schema has 0% description coverage, so the description compensates by listing each parameter with units (e.g., 'Moment of inertia in kg⋅m²', 'angular velocity components in rad/s'). This adds meaningful context beyond the schema types and is essential for correct usage.
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?
The description clearly states 'Calculate angular momentum' and provides the formula L = I × ω, effectively communicating the tool's purpose. While it distinguishes from linear momentum through the formula, it does not explicitly differentiate from sibling rotational tools like calculate_torque or calculate_moment_of_inertia.
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 explains the tool's function and includes conservation tips, but lacks explicit guidance on when to use this tool versus alternatives such as calculate_momentum (linear) or calculate_angular_acceleration. The usage is implied by the name and formula, but no when-not-to-use conditions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It confirms a read-only equilibrium check but does not explicitly state that no state is modified, nor does it discuss error handling or limitations.
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?
The description is well-structured with a clear heading, explanation, args, returns, and an example. It is somewhat lengthy but each sentence adds value. Could be slightly tighter.
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?
The description explains the tool's purpose, inputs, and outputs in detail, including an example. However, it does not mention integration with simulations or error behavior, and no output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by explaining that 'forces' is a list of vectors or JSON string in Newtons and 'tolerance' is a fraction with default 0.01. This adds essential meaning beyond the schema's bare types.
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 'Check if forces are in equilibrium: ΣF = 0' and provides a specific verb-resource pair. It distinguishes from siblings like check_torque_balance by focusing solely on force equilibrium, and the example reinforces its purpose.
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 says 'Essential for statics problems and structural analysis,' giving context, but does not explicitly state when not to use this tool or compare it to alternatives like check_equilibrium or check_torque_balance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description effectively discloses the output structure (dict with orbital radius, velocity, period, acceleration) and the default gravitational constant. It lacks mention of error handling or constraints (e.g., altitude must be positive), but it is largely transparent for a physics computation tool.
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 well-structured with distinct sections for purpose, arguments, returns, and example. Every sentence adds value and there is no redundancy. It is concise yet informative.
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 the absence of an output schema, the description fully enumerates return keys. It includes a helpful example. However, it could be more complete by mentioning assumptions (e.g., circular orbit, no atmospheric drag) and ensuring consistency in units. Still, it is largely adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by defining each parameter with units and providing a concrete example. This adds significant meaning beyond the minimal schema.
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 the tool analyzes a circular orbit at a given altitude, combining period, velocity, and acceleration. This distinguishes it from sibling tools like calculate_orbital_period or calculate_centripetal_force which compute single quantities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., using individual calculation tools). The example hints at a typical use case but does not state when this combined analysis is preferred or not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, description carries full burden. It mentions downward positive loads and returns a dict, but lacks edge case handling (e.g., invalid inputs, distributed loads). Partially transparent.
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?
Structured with Args, Returns, and Example. Informative but slightly verbose; could be trimmed without losing clarity.
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?
No output schema, so description includes return dict. Covers basic beam reaction calculation. Missing error handling and units consistency, but sufficient for simple use.
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?
Adds meaning beyond schema: loads and load_positions are described as point loads in Newtons and positions in meters, with 'or JSON string'. beam_length only gets 'in meters'. Schema coverage 0% makes this valuable.
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?
Description clearly states 'Calculate reaction forces for a simply supported beam', which is a specific verb+resource. It distinguishes from sibling tools like calculate_force or calculate_torque.
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?
Provides an example and explains the method (moment equilibrium). Does not explicitly state when not to use or alternatives, but the tool is unique among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It explains that the Magnus force is perpendicular to velocity and spin axis, describes the return dict structure, and provides units. It lacks details on error handling or side effects, but for a calculation tool this is adequate.
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?
The description is well-structured with a summary line, physics explanation, parameter list, returns, and an example. It is longer than necessary but every section adds value. The front-loading with the core purpose is effective.
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?
Despite lacking an output schema, the description fully documents the return structure and includes an example. It covers the essential aspects of the tool: input format, output, and physical principle. Minor omissions like error conditions are acceptable given the tool's simplicity.
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?
The input schema only defines types (string, number), but the description adds critical meaning: velocity and angular_velocity are arrays in m/s or rad/s (or JSON strings), radius in meters, fluid density with default. The example further clarifies usage, compensating for the schema's lack of descriptions.
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 the tool calculates Magnus force on a spinning ball, a specific physics calculation. It distinguishes itself from sibling tools by specifying the unique physics phenomenon, and the example reinforces its use for sports balls.
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 context for use (spinning ball, sports) but does not explicitly state when to use this tool versus alternatives or when not to use it. The example implies typical usage, but no comparative guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains the concept of moment of inertia, lists formulas, and provides an example. However, it does not disclose behavior for invalid inputs, edge cases, or how missing parameters are handled (e.g., when shape requires length but not provided).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough but lengthy, including a general definition of moment of inertia that may be unnecessary. It is front-loaded with purpose, but later sections (formulas, example) could be abbreviated without losing clarity.
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 8 parameters and no output schema, the description explains inputs thoroughly and provides a minimal output dict. It lacks error handling details and behavior for invalid combinations (e.g., rod without length), but overall covers most aspects adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate, and it does excellently. Each parameter is explained with context (units, allowed values, dependencies on shape). Common formulas show how parameters relate, adding significant meaning beyond schema names.
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 the tool calculates moment of inertia for various shapes. It lists specific shapes and provides formulas, making its purpose unambiguous and distinguishable from sibling tools that perform other physics calculations.
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 implies usage for rotational inertia problems but does not explicitly state when to use this tool versus others like calculate_torque or calculate_angular_momentum. No exclusion criteria or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes outcome (constrain motion between bodies) and lists joint types, but does not disclose error handling, prerequisites (bodies must exist), or side effects. No annotations provided to compensate.
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?
Well-structured with summary, type descriptions, args/returns, and a detailed example. Every sentence adds value; no wasted words.
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?
Covers the core functionality, joint types, and a full example. Lacks explanation of return values (joint_id) and edge cases, but is sufficient for a creation tool with a complex input schema.
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?
Adds meaning beyond schema by explaining joint types and showing parameter usage in example. Schema coverage is 50% (sim_id lacks description), but the description includes sim_id in example. The nested joint object properties are well-documented.
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?
Clearly states 'Add a joint/constraint to connect two rigid bodies' and lists joint types with descriptions. Differentiates from sibling tools like add_rigid_body by focusing on constraints.
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?
Provides explicit guidance on when to use each joint type (FIXED, REVOLUTE, etc.) and includes a complete example. Lacks explicit when-not-to-use or alternative tool mentions, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description discloses the formula, return values (drag force vector, magnitude, Reynolds number), and behavioral details like viscosity estimation when omitted. No contradictions.
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?
The description is front-loaded with the formula and purpose, and provides structured examples. It is detailed but somewhat long; every sentence contributes value, though minor redundancy exists.
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?
Despite lacking an output schema, the description explains return values and covers all parameters comprehensively. Examples illustrate usage in different scenarios, making the tool fully understandable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, but the description compensates thoroughly by explaining each parameter with units, defaults, and typical values (e.g., 'velocity: Velocity vector [x, y, z] in m/s').
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 'Calculate drag force for an object moving through a fluid', uses a specific verb-resource pair, and the formula and context distinguish it from siblings like lift force or buoyancy.
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 includes common drag coefficients and examples for different fluids, which imply typical use cases, but it does not explicitly state when to use this tool over alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses supported units, parameter purpose, return format, and examples. It does not cover error handling or idempotency, but overall is informative.
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?
The description is well-structured with bullet points, args/returns, and examples. It is slightly lengthy but every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description includes return fields, examples, and supported units, making it complete for a unit conversion tool.
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?
Input schema has 0% description coverage; the description lists parameter names, types, and example values, adding meaning that the schema lacks.
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 'Convert a value from one unit to another', lists supported units/categories, and distinguishes itself from sibling physics calculation tools.
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 implies usage for any unit conversion but does not explicitly specify when to use this tool over alternatives like list_unit_conversions, nor does it provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It discloses that it calculates velocity and acceleration from position data, extracts a component, and returns multiple derived quantities. However, it does not mention error handling or data validation.
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?
The description is well-structured with sections for Args, Returns, and Example, and the first sentence states the purpose. It is slightly lengthy but each sentence adds value. Could be trimmed slightly.
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 the complexity and lack of output schema, the description covers input parameters, return structure with keys, and includes an example. It lacks units for velocities/accelerations but is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains each parameter: times as seconds or JSON string, positions as vector arrays in meters, component with default 'magnitude' and enum-like options. This adds substantial meaning beyond the schema.
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 'Generates motion graph data (position, velocity, acceleration vs time)' and distinguishes from siblings like calculate_instantaneous_velocity by producing multiple series. The verb 'generate' and resource 'motion graph' are specific.
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 implies usage by showing automatic calculation of v and a, but it does not explicitly state when to use this tool over individual calculation tools, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It thoroughly explains the parameters, units, default values, and return structure. However, it does not mention error handling, units conversion, or performance characteristics, which is acceptable for a pure calculation tool.
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?
The description is well-structured with formula, parameter list, return keys, and an example. It is slightly lengthy but each part adds value. The use of docstring-style formatting aids readability. Could be trimmed slightly, but overall efficient for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return dictionary keys and their meaning. The example is realistic and covers typical usage. All parameters are documented. The tool has moderate complexity with 7 parameters, and the description provides sufficient context for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds full semantics: each parameter has units, explanation, and context (e.g., 'pressure1: Pressure at point 1 in Pascals'). The default values and optional nature of velocity2/height2 are clearly stated. This fully compensates for the missing schema descriptions.
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 calculates Bernoulli's equation and provides the formula. The title is null but the name 'calculate_bernoulli' combined with the equation and explanation leaves no ambiguity about the tool's purpose. It is distinct from the many other physics calculation tools by focusing on Bernoulli's principle for fluid flow.
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 includes an example but does not explicitly state when to use this tool versus alternatives like calculate_venturi_effect or calculate_pressure_at_depth. Usage is implied by the equation's domain but no when-not-to-use or comparison to siblings is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the calculation formula, expected input units (kg, meters), and the return structure including center_of_mass and total_mass. Since no annotations are provided, the description carries the full burden and does so effectively, though missing potential error conditions.
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 well-organized with sections for formula, args, returns, and an example. Every sentence adds value, and there is no redundancy or wasted text.
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?
The description is complete for a calculation tool: it explains inputs, units, outputs, and provides an example. Minor gaps exist, such as error handling for empty lists or mismatched dimensions, but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only specifies types as 'string', but the description explains that masses should be a list of floats in kg and positions a list of coordinates in meters, optionally as JSON strings. This adds essential meaning beyond the schema.
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 explicitly states 'Calculate center of mass for a system of point masses' and provides the formula, clearly differentiating it from sibling tools that calculate other physical quantities.
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?
While the purpose is clear, the description does not provide explicit guidance on when to use this tool versus alternatives like calculate_moment_of_inertia. The example offers usage context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully describes the tool's behavior: it returns position, velocity, damping ratio, and regime, and explains the three damping regimes. It does not mention side effects or performance, but for a calculation tool this is sufficient.
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?
The description is well-structured with sections for Args, Returns, Damping regimes, and an Example. It is slightly verbose but every sentence adds value. Front-loaded with core purpose. Could be more concise by merging some explanations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (physics of damped oscillations) and the absence of an output schema, the description is complete. It explains all output fields, the damping ratio calculation, and the three regimes. The example further clarifies usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description thoroughly explains each parameter with units and default values. It adds critical meaning beyond the schema, such as 'mass in kg' and 'damping_coefficient: damping strength', making it very helpful.
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 the tool calculates damped oscillation with friction/resistance, defines three damping regimes, and provides an example. It distinguishes itself from siblings like calculate_simple_harmonic_motion by focusing on damping.
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 does not explicitly state when to use this tool versus alternatives like calculate_simple_harmonic_motion or calculate_projectile_with_drag. However, its detailed explanation of damping regimes implies the specific context of damped oscillators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the physics assumptions (perfectly elastic, 1D) and the full set of return values. It does not discuss edge cases or potential errors, but for a pure calculation tool, it is reasonably transparent.
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?
The description is well-structured with clear sections for Args, Returns, and Example. Some redundancy exists (e.g., repeating 'conservation of momentum and energy'), but overall it is efficient and front-loaded.
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 no output schema, the description thoroughly explains the return dict and includes a concrete example. It partially covers parameter semantics (units). Missing constraints like positive mass, but for a physics tool it is fairly complete among many sibling tools.
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 0% with 4 parameters lacking descriptions. The description adds units (kg, m/s) and clarifies that velocities are 1D. It does not specify allowed ranges (e.g., mass > 0), but the provided information is meaningful beyond the bare schema.
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 calculates final velocities after a 1D elastic collision using conservation of momentum and energy. It distinguishes itself from siblings like calculate_inelastic_collision_3d by specifying 'elastic' and '1D'.
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 specifies it's for perfectly elastic collisions in 1D, with an example of pool ball collision. It does not explicitly mention when not to use it or contrast with 3D version, but the context is clear enough for an agent to select the appropriate tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does well by explaining the calculation formula, input requirements (times in seconds, accelerations in m/s²), and the detailed return structure. However, it does not disclose potential error conditions or input validation.
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 well-structured with a concise definition, parameter explanation, return format, and a clear code example. Every sentence adds value without redundancy.
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?
The description covers purpose, parameters, and returns in sufficient detail for a pure calculation tool. It lacks output schema but compensates by explicitly listing returned fields. Minor omission: no mention of error handling or input constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only specifies type 'string' for both parameters, leaving 0% coverage. The description adds essential meaning: times are in seconds, accelerations are vector arrays in m/s², and both can be passed as JSON strings. This vastly compensates for the bare schema.
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 'Calculate jerk (rate of change of acceleration)' with a specific verb and resource. It explains the physical importance and differentiates from sibling tools like calculate_angular_acceleration by focusing on linear jerk in 3D.
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 context with an example but lacks explicit guidance on when to use this tool versus alternatives like calculate_acceleration_from_position. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for transparency. It clearly states the formula, default gravity value, and that an additional derived value (equivalent kinetic velocity) is returned. It does not mention side effects or destruction, but as a calculation tool, that is appropriate.
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?
The description is moderately long but well-structured with sections (description, args, returns, example). It front-loads the core formula and then details parameters and output. A minor improvement could be trimming the example explanation, but overall it is clear and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully describes the return values (potential_energy in Joules, equivalent_kinetic_velocity in m/s). With only 3 parameters, all documented, and no constraints or enums, the description covers all necessary context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description fully explains each parameter: mass (kg), height (m), gravity (default 9.81 m/s²). It provides units, defaults, and an example that illustrates usage. The schema only provides types and defaults without descriptions, so the description adds essential meaning.
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 calculates gravitational potential energy using the formula PE = mgh, and explicitly distinguishes from siblings by specifying the formula and that it also returns equivalent kinetic velocity. The verb 'calculate' and resource 'potential energy' are specific, and the addition of 'gravitational' reinforces the scope.
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 does not provide explicit guidance on when to use this tool versus alternatives like calculate_kinetic_energy or other potential energy forms. The example and formula imply its use case, but no 'when not to use' or comparative statements are given. Given many siblings, this is a gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the calculation, returns (terminal velocity, time to 95%, drag force), and includes an example output. This is adequate for a pure calculation tool.
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?
The description is well-structured with a summary, formula, parameter list, and example. It is somewhat lengthy but front-loaded with the core purpose, and every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and lack of output schema, the description is complete: it covers inputs, formula, return values, and an example. No major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by defining each parameter, providing typical values (e.g., fluid density for air/water, drag coefficients), and listing defaults. This adds significant meaning beyond the input schema.
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 the tool calculates terminal velocity when drag equals weight, with the formula provided. It is specific to terminal velocity, distinguishing it from sibling physics tools.
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 context (when drag balances weight) and an example, but does not explicitly state when to use this tool versus alternatives like calculate_drag_force or calculate_projectile_with_drag.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It describes outputs and example but does not disclose any side effects, destructive actions, or limitations. However, the tool appears to be a pure computation function, so the lack of behavioral warnings is acceptable.
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 well-structured with sections for description, args, returns, and example. Every sentence adds value, and it is appropriately sized without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is complete: it explains what the tool does, all parameters, return values, and provides a concrete example. An AI agent has enough information to use it correctly.
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 has 0% description coverage (all string types), but the description explains each parameter: times in seconds, positions as vector arrays, fit_type with enumerated options. This adds significant meaning beyond the raw schema.
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 'Fit polynomial to trajectory data,' which is a specific verb+resource. It distinguishes from sibling tools like 'calculate_projectile_motion' by focusing on fitting curves to arbitrary trajectory data, not just projectile calculations.
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?
Mentions it's 'useful for smoothing noisy data or finding trajectory equations,' providing clear usage context. However, it does not explicitly state when not to use this tool or compare to alternative tools among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully assumes the burden. It explains the calculations and return dictionary fields. It does not mention side effects or permissions, but for a stateless calculation tool this is sufficient.
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, front-loaded with purpose, and uses a clear structure with Args, Returns, and an Example section. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description comprehensively details all return fields. Given the tool's simplicity and the presence of many similar sibling tools, the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining that positions are position vectors and times are time values, including units and acceptable formats (list or JSON string). The example further clarifies 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 'Calculate average speed along a path' and provides the formula. It distinguishes from sibling tools like calculate_instantaneous_velocity by focusing on average over a segment.
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 includes the formula and return values but does not explicitly advise when to use this tool versus alternatives like calculate_instantaneous_velocity. Usage is implied but not contrasted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavior: it calculates the ideal banking angle using the given formula and returns a dict with angle in radians and degrees. It explains the physics concept and includes practical tips, leaving no ambiguity about the tool's operation.
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?
The description is well-structured with sections for formula, args, returns, tips, and an example. It is somewhat lengthy but each part adds value. Minor redundancy in the formula repetition could be trimmed.
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 the simple input schema and no output schema, the description provides adequate coverage: formula, parameter explanations, return structure, and a concrete example. It does not discuss edge cases (e.g., invalid inputs) but this is acceptable for a straightforward physics calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must and does provide full semantics: velocity in m/s, radius in meters, gravity in m/s² with default 9.81. This adds critical meaning beyond the bare schema types.
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 'Calculate ideal banking angle' and provides the formula θ = arctan(v² / (rg)). It is specific to banking angle calculation, distinguishing it from sibling tools that handle other physics computations.
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 does not explicitly state when to use this tool versus alternatives. While it provides tips and an example, it lacks comparative guidance with sibling tools for similar calculations (e.g., centripetal force). Usage context is implied but not clearly delineated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the algorithm (interpolation/differentiation) and the return structure, including fields like 'interpolated'. Despite no annotations, it is transparent about key behaviors. It lacks details on error handling or assumptions.
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?
The description is well-structured with sections for args, returns, and an example. It is concise yet informative, though the example adds length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and sparse input schema, the description provides complete context: purpose, method, all parameters, return values, and a concrete example. It leaves no major gaps.
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?
With 0% schema coverage, the description adds significant meaning: it explains positions as vectors in meters or JSON string, times as seconds, and target_time as time. This compensates well for the sparse schema.
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 explicitly states 'Calculate instantaneous velocity at a specific time' and distinguishes it from siblings like calculate_average_speed by detailing the method (interpolation vs differentiation).
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 explains when interpolation or numerical differentiation is used, providing clear context. However, it does not explicitly state when to use this tool over alternatives or exclude cases where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It clearly explains the calculation, input parameters with units, and return value structure (lift_force and dynamic_pressure). It does not mention side effects, but as a pure computational tool, this is appropriate. The transparency is high for a calculation tool.
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 well-structured: formula, Args, Returns, and Example. Each sentence serves a purpose, and the brevity is appropriate for the complexity of the calculation. No redundant text, and the example aids understanding without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description fully specifies the return dict with fields lift_force and dynamic_pressure, including units. The example also shows expected results. Given the simplicity of the tool (pure calculation), the description provides complete information for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameter descriptions (0% coverage), but the description compensates excellently by detailing each parameter with units and a default for fluid_density. The Args section lists velocity, wing_area, lift_coefficient, and fluid_density with explanations, and the example provides concrete values. This adds significant meaning beyond the schema.
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 the tool calculates lift force using the standard formula L = (1/2) ρ v² C_L A and references Bernoulli's principle and wing aerodynamics. It distinguishes itself from sibling tools like calculate_drag_force by focusing on lift, making its purpose unambiguous.
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 implies usage for lift force calculations through its formula and example, but it does not explicitly state when to use this tool versus alternatives (e.g., calculate_drag_force) or when not to use it. However, the example provides context for typical usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description explains the calculation, includes formulas, default values, and return values. It is transparent but could mention limitations like angle ranges.
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 well-structured with formulas, parameter descriptions, return dict, and an example. Every sentence adds value without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a formula-based physics tool with no output schema, the description is complete: it explains formulas, parameters, return values, and includes an example.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description fully compensates by detailing each parameter (mass, gravity, angle_degrees, additional_force), including units, defaults, and formula relation.
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 calculates normal force on an inclined plane, provides the formula, and distinguishes from sibling tools by specific context (inclined plane).
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 implies use for inclined plane normal force but lacks explicit guidance on when to use vs alternative tools or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full burden. It clearly explains the mathematical relationship and return fields, though it does not disclose edge cases or error handling (e.g., negative depth). The behavior is largely transparent for a simple calculation tool.
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 well-structured with formula, args, returns, and an example. Every sentence provides essential information without redundancy. It is front-loaded with the core formula and promptly details parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, no output schema, and no annotations, the description is complete. It covers all parameters, return fields, and provides a realistic example. The sibling tools are all physics calculations, and this description is adequate for differentiation and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage). The description compensates fully by explaining each parameter, providing typical values, defaults, and a complete example. It adds crucial meaning beyond the schema's raw type definitions.
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 explicitly states 'Calculate pressure at depth' with the formula P = P_atm + ρgh, clearly identifying the tool's purpose. It is distinct from siblings like calculate_buoyancy and calculate_drag_force, which focus on other physical phenomena.
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 a concrete scuba diving example, implying usage scenarios, but does not explicitly guide when to use this tool versus related siblings like calculate_buoyancy or calculate_bernoulli. It lacks 'when not to use' or alternative tool recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It transparently describes return structure and the deterministic calculation, but lacks details on edge cases or validation.
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?
Well-structured with formula, parameter details, example, and tips. Slightly lengthy but each section adds value; front-loaded with key information.
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?
Covers essential aspects for a simple calculation tool: formula, parameters, return dict with unit. No output schema, so description of return value is necessary and provided. Lacks error handling info.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides only numeric types (0% coverage). Description adds units (kg⋅m², rad/s) and clarifies each parameter's physical meaning, fully compensating for schema gaps.
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 explicitly states the tool calculates rotational kinetic energy, provides the formula KE_rot = (1/2) I ω², and distinguishes it from sibling tools like 'calculate_kinetic_energy' by specifying 'rotational'.
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?
Tips explain when to use (total KE, rolling objects, flywheel energy storage) and imply context, but no explicit when-not-to-use or comparison to similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description adequately describes the mathematical computation and expected inputs/outputs. For a pure calculation tool, this covers behavioral traits sufficiently. It does not disclose any side effects because none exist.
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 well-structured with sections for purpose, parameter list, return values, and an example. Every sentence adds value; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully specifies the return dictionary with keys, units, and an example. All necessary information for a physics calculation tool is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description includes detailed docstrings for each parameter with units (e.g., 'inlet diameter in meters'). This adds significant meaning beyond the bare schema, enabling correct 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 calculates the Venturi effect using continuity equation and Bernoulli's principle. The specific verb 'calculate' and resource 'Venturi effect' are precise, and the tool is distinct from sibling physics calculation tools.
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 mentions 'flow through constriction' and provides an example, but does not explicitly guide when to use this tool over closely related siblings like 'calculate_bernoulli'. No 'when not to use' or alternatives are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully explains the tool's behavior: checks conservation, returns detailed results. No side effects mentioned, but it's a read-only verification.
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?
Well-structured with sections, but slightly long due to example and tips. Front-loads purpose efficiently.
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?
Comprehensive with return value description and example. Lacks error handling info, but output schema not provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Each parameter is described with units and purpose in the Args section. Schema coverage is 0%, so description carries full burden and does it well.
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?
Clearly states it verifies energy conservation in physics processes. Differentiates from siblings like check_momentum_conservation by focusing on energy.
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?
Provides tips for when to use (isolated systems, friction, numerical errors) and example usage. Does not explicitly mention when not to use or compare to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the numerical integration method, forces considered, and return values (trajectory, final state, max depth, total distance). This is good transparency, though default values are mentioned for some parameters.
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 well-structured with a clear header, bullet-pointed forces, arg list, return statement, and example. Every sentence adds value, and the length is appropriate for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no output schema, and a complex simulation with many siblings, the description covers parameters, return values, assumptions, and provides an example. It is complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the 'Args' section fully documents each parameter with units, defaults, and explanations. This adds significant meaning beyond the schema. An example further clarifies 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 simulates underwater projectile motion with drag and buoyancy using numerical integration. This distinguishes it from siblings like calculate_projectile_motion (no drag/buoyancy) and calculate_buoyancy (single force).
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 implies use for underwater scenarios with realistic physics but does not explicitly state when to use this tool versus alternatives like calculate_projectile_with_drag or calculate_drag_force. More explicit guidance would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full responsibility. It details the numerical method (central differences), explains input format flexibility (arrays or JSON strings), and outlines the return structure. However, it does not discuss edge cases like non-uniform time steps, insufficient data points, or error handling.
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 well-structured with separate sections for purpose, formulas, arguments, return values, and an example. Every sentence adds value without redundancy, making it efficient and easy to parse.
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 the moderate complexity (numerical differentiation), the description covers the core method, input/output details, and an example. It is nearly complete, though it could mention the minimum number of time points required (at least 3 for central differences) and whether uniform time steps are assumed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates fully by explaining that 'times' are time values in seconds (or JSON string) and 'positions' are position vectors in meters (or JSON string), with a concrete example demonstrating the expected format.
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 the tool calculates acceleration from position data via numerical differentiation using central differences. It specifies the formulas and distinguishes itself from sibling tools like calculate_instantaneous_velocity and calculate_jerk by focusing on acceleration from position history.
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 provides an example usage for analyzing recorded position data. It implies the tool is for discrete time-series data but does not explicitly exclude other use cases or mention alternative tools for different scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the computation, the vector nature, and conservation, but does not explicitly state that it is a stateless, non-destructive operation. This is a minor gap.
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 well-structured with Args, Returns, Tips, and Example sections. It is front-loaded with the formula, every sentence adds value, and there is no redundancy.
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?
The description explains the return structure (momentum vector and magnitude) and provides physics context. Minor omissions include no error handling guidance (e.g., negative mass) and implicit units for momentum (shown in example but not explicitly in description).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage. The description compensates excellently by explaining each parameter (mass must be positive, velocity components in m/s) and providing an example. This adds significant meaning beyond the bare schema.
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 explicitly states 'Calculate momentum from mass and velocity (p = mv)', clearly specifying the verb, resource, and formula. It distinguishes itself from sibling tools like calculate_force or calculate_kinetic_energy by directly naming momentum.
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 provides context on when to use the tool (e.g., analyzing impacts, explosions, rocket propulsion) and mentions conservation of momentum. However, it does not explicitly state when not to use it or compare it to alternative tools for collisions among the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It explains the math, return values (torque vector and magnitude), and physical conditions (right-hand rule, max/zero torque). It does not mention side effects or permissions, but for a pure calculation tool this is sufficient.
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?
The description is well-structured with a formula, explanation, Args, Returns, Tips, and Example. It is slightly verbose (e.g., listing all vector components in Args), but the organization is clear and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (vector cross product), the description covers the calculation, parameter meanings, return format, and usage context comprehensively. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description provides full parameter explanations with units (Newtons, meters) and implicit meaning (force components, position vector components). This compensates completely.
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 'Calculate torque from force and position: τ = r × F (cross product).' It specifies the exact operation and distinguishes it from sibling tools by focusing on torque specifically.
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 includes tips and an example for common use (opening a door) but does not explicitly exclude alternative tools for related concepts like angular momentum or rotational inertia.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description thoroughly explains the equilibrium conditions and return values. It adds context about input formats and defaults, making the tool's behavior clear.
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 well-structured with a purpose statement, Args/Returns sections, and an example. It is efficient and front-loaded.
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?
The description covers input, output, and an example sufficiently for a simple calculation tool. It could add notes on error handling or edge cases, but it's largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds detailed meaning: forces as vector lists with units, positions as coordinates, pivot default, tolerance default, and a concrete example. This fully compensates for the schema gap.
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 checks static equilibrium (ΣF=0 and Στ=0), distinguishing it from sibling tools like 'check_force_balance' and 'check_torque_balance' which check only one condition.
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 implies usage for full equilibrium checks, and the presence of sibling tools for individual balances provides context. However, it lacks explicit when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully covers behavior: vector nature, direction importance, external forces impact, and example. Could briefly mention that it is a pure computation without side effects, but overall informative.
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?
Well-structured with Args, Returns, Tips, and Example sections. Slightly verbose in tips (e.g., 'Momentum is ALWAYS conserved...') but overall efficient and front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains all return fields. Covers physics context, parameter types, tolerance, and example usage. Complete for an LLM to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description provides detailed parameter explanations: initial_momentum and final_momentum as [x,y,z] vectors in kg·m/s, tolerance as fraction. Also fully explains the return dict, exceeding what schema alone offers.
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 verifies conservation of momentum and distinguishes from siblings like check_energy_conservation and check_angular_momentum_conservation by explicitly focusing on momentum conservation.
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?
Indicates it is used for isolated systems and collision calculations, with tips about external forces. Does not explicitly mention when not to use or alternatives, but context from sibling tools and physics knowledge fills the gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the tool's behavior (checking equilibrium, returning net torque and balance status) without annotations. While it doesn't explicitly state read-only or lack of side effects, the context implies a pure computation. Could be improved by noting it does not modify state.
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?
Well-structured with sections for Args, Returns, and Example, but the description is somewhat lengthy. Every sentence serves a purpose, but it could be slightly more concise while retaining clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description provides complete information: purpose, input parameters, return value structure, and a concrete example. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, so the description fully explains the two parameters: torques (list of vectors or JSON string) and tolerance (fraction with default 0.01). This adds significant value beyond the schema.
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?
Clearly states the tool checks torque equilibrium (Στ = 0), specifying the verb 'check' and the resource 'torques equilibrium'. Distinguishes from sibling tools like check_force_balance and check_equilibrium by focusing specifically on torques.
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?
Provides context for usage ('Essential for rotational equilibrium and lever problems') and an example (seesaw balance), but does not explicitly describe when not to use or mention alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses that it creates a new physics world and returns a simulation ID for subsequent operations. It mentions resource freeing and default gravity direction. It could improve by noting that calling it multiple times creates independent simulations, but overall it is transparent about effects and prerequisites.
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?
The description is well-structured with sections for Args, Returns, Tips, Requirements, and Example. It is front-loaded with the core purpose. While slightly verbose, every sentence adds value, and the structure aids readability. A minor reduction in redundancy (e.g., tips and args overlap slightly) would earn a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description details the return format (sim_id and config) and provides an example. It covers requirements, practical tips (ID memory, integrator choice), and cleanup. Given the tool's complexity (6 parameters, many siblings), the description is complete and leaves no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description carries the full burden. It thoroughly explains each parameter with units, defaults, and practical meaning (e.g., dt accuracy trade-off, gravity components, integrator options). This goes well beyond the schema and helps the agent choose correct values.
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 the tool creates a new physics simulation using the Rapier engine, initializing a rigid-body world with configurable gravity and timestep. It distinguishes itself from sibling tools (e.g., add_body, step_simulation) by being the entry point, and the example and tips reinforce its role.
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 provides clear context on when to use the tool: before other simulation operations, and it warns to destroy when done. Requirements (Rapier provider configured, service running) and tips (keep IDs) guide usage. However, it does not explicitly state when not to use it or compare to alternatives, though among siblings it is unique.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully discloses that it returns a dictionary mapping categories to unit lists. No side effects or destructive behavior is mentioned, which is acceptable for a read-only listing tool.
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?
Description is concise, well-structured with bullet points and an example. Every sentence earns its place, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description completely explains the return format and content with an example. No gaps remain.
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?
No parameters in schema; baseline score of 4 applies. Description adds value by detailing the return structure and example, which compensates for lack of parameters.
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?
Description clearly states 'List all supported unit conversions' with a specific verb and resource. It distinguishes itself from sibling tool 'convert_unit' by providing the list of available units.
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?
Description implies usage as a precursor to conversion, but does not explicitly state when to use it or when not to use it. It is clear that it serves as a reference for available units.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the simulation is stepped, records per timestep, and describes return frame structure. Without annotations, it carries the full burden and covers key behaviors, though could mention simulation state mutability more explicitly.
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?
Well-organized with sections for description, args, returns, tips, and example. Every sentence adds value; no redundancy.
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?
Covers return format comprehensively given no output schema. Mentions prerequisites indirectly (sim_id, body_id) but does not address error conditions or missing bodies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Fully explains all 4 parameters including purpose, optionality (dt), and typical values. Compensates for 0% schema coverage with clear descriptions and an example.
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?
Clearly states verb (record), resource (trajectory of a specific body), and scope (over time). Differentiates from siblings like record_trajectory_with_events by focusing on pure trajectory recording without events.
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?
Provides practical context: generating animation data for R3F, tips for FPS, and example usage. However, does not explicitly mention when not to use or compare to sibling alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It details the return structure (frames, initial/final energy, loss, power) and explains that it analyzes damping, bounces, and energy loss mechanisms. No side effects or contradictory information.
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?
The description is well-structured with clear sections (Description, Args, Returns, Tips, Example). It is somewhat lengthy but every section adds value. The opening sentence is front-loaded and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 params, nested object, no output schema in structured data), the description is complete. It covers all parameters, return values in detail, includes an example, and provides usage tips. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides detailed parameter documentation in the Args section: trajectory_data (dict with 'frames' field), mass (kg), gravity (default 9.81), reference_height (default 0). This adds essential meaning beyond the bare schema.
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 states 'Track energy dissipation over a trajectory' and explains it analyzes energy changes over time. This clearly distinguishes it from sibling tools like calculate_kinetic_energy or check_energy_conservation, which focus on static calculations or conservation checks rather than trajectory analysis.
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 explicitly recommends using this tool after record_trajectory or record_trajectory_with_events, and provides tips for interpretation (e.g., visualize energy vs time). It does not explicitly state when not to use it, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully explains the tool as a pure calculation with no side effects. It clearly states inputs, formula, and output. Lacks mention of edge cases or potential errors (e.g., zero moment of inertia).
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?
Well-structured with sections: formula, description, args, returns, tips, example. Front-loaded with key formula. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given only two numeric parameters and no output schema, the description fully explains input semantics, output format, and provides an example. Tips add educational value. Complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% coverage for descriptions, but the description compensates by providing units ('N⋅m', 'kg⋅m²') and an example with concrete values, adding meaning beyond the bare schema.
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?
Description clearly states 'Calculate angular acceleration' with formula α = τ / I, using specific verb and resource. It distinguishes from siblings like 'calculate_torque' and 'calculate_momentum' by focusing on rotational dynamics.
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?
Provides explicit usage context: 'Use for: motor acceleration, spinning up flywheels' and includes an example. However, it does not mention when not to use or contrast with alternatives like 'calculate_torque' or 'calculate_angular_momentum'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully explains the calculation (buoyant force = displaced fluid weight) and returns: buoyant force and displaced mass. It does not mention side effects, auth, or rate limits (not needed), but it provides clear behavioral context for a calculation tool.
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 well-structured with a formula, parameter explanations, return values, and a concrete example. It is concise yet covers all necessary information without extra fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, no output schema), the description is complete: it explains parameters, return values, and provides an example usage. The example ties everything together for practical understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates fully. It explains each parameter: volume in m³, fluid_density with typical values (water=1000, air=1.225), gravity default (9.81), and submerged_fraction range (0.0-1.0) and default (1.0). Adds units and examples.
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 calculates buoyancy force using Archimedes' principle, with a specific formula. It distinguishes itself from sibling physics calculation tools by focusing on buoyancy, and the example further clarifies its purpose.
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 explains when to use the tool (calculating buoyancy force) and provides an example showing how to apply it to real-world scenarios like checking if an object floats. However, it lacks explicit guidance on when not to use it or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses that it returns a dict with centripetal force and acceleration, explains physics behavior (v² relationship, direction). Lacks explicit statement that it's a pure calculation without side effects.
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?
Well-structured with formula, explanation, args, returns, tips, and example. Every sentence adds value, front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return dict structure. Covers key physics context, examples, and tips. No missing elements for a calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description defines each parameter's units and meaning (mass in kg, velocity in m/s, radius in meters). Provides an example with real values, compensating fully for schema's lack of description.
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 the purpose: calculate centripetal force using the formula F_c = m v² / r. It distinguishes from sibling tools like calculate_force and other specific forces by focusing on circular motion.
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?
Provides tips on when to use (car turns, satellite orbits, centrifuges) and explains it's the net inward force, not a new force. Could be improved by explicitly stating when not to use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the formula, key properties (independence of mass), default gravitational constant, and expected behavior. No contradictions.
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 well-structured with formula, key facts, parameter list, return info, tips, and an example. Every sentence is informative and efficient, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description details the return format (dictionary with two velocity fields including units) and provides an example result. It is fully complete for a physics calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains each parameter (mass, radius, gravitational_constant with units and default). This adds essential meaning beyond the bare schema.
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 the tool calculates escape velocity with the formula v_escape = √(2GM/r). It specifies the inputs and outputs, distinguishing it from sibling physics calculation tools by its specific purpose.
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?
Provides tips with example values for Earth, Moon, Sun and notes independence of escape direction and mass. However, it does not explicitly contrast with sibling tools or state when to use this over alternatives like calculate_orbital_period.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: it computes Re, determines flow regime, provides typical viscosity values, and explains the return structure. No hidden behaviors.
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 well-organized with formula, parameter doc, returns, and example. It is concise yet complete, with no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully documents the return dict including reynolds_number and flow_regime with thresholds. The example further clarifies usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has zero parameter descriptions (0% coverage). The description compensates by detailing each parameter with units, typical values, and the formula's role. Example shows concrete 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 the tool calculates Reynolds number and provides the formula. It distinguishes itself from sibling physics calculation tools by its specific purpose.
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 includes an example but does not explicitly state when to use this tool versus alternatives. Usage is implied by the tool name and context among many physics calculators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, disclosing the physics assumptions (ideal springs, amplitude independence), output structure, and units. However, it lacks explicit mention of parameter limits or potential errors.
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 well-structured with sections for args, returns, tips, and an example, and every sentence provides essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and only two parameters, the description covers all necessary aspects: formula, parameters, return values, assumptions, and an example, making it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions, but the tool description fully explains each parameter's units and physical meaning, and provides tips on how they affect the results, adding substantial value beyond the schema.
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 explicitly states that the tool calculates the period of a spring-mass system using the formula T = 2π√(m/k), clearly distinguishing it from sibling tools like calculate_pendulum_period and calculate_damped_oscillation.
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 provides tips on how mass and spring constant affect the period and includes an example, but does not explicitly state when to avoid using this tool (e.g., for non-ideal springs or damped systems).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It discloses that the tool frees memory and that simulations persist until destroyed, which is important for understanding side effects and server resource management.
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?
Well-structured with sections (Description, Args, Returns, Tips, Example). Each sentence adds value, though slightly longer than strictly necessary. Tips for LLMs are helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, parameter, return value, usage guidelines, and behavioral impact. No output schema needed; the description adequately explains what the tool does and what to expect.
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 0% (no descriptions in schema), but the description adds 'sim_id: Simulation ID to destroy' and includes an example, providing clear meaning beyond the raw type.
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 'Destroy a simulation and free resources' with a specific verb and resource. It distinguishes itself from sibling tools like create_simulation and step_simulation by focusing on cleanup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Cleanup when done with a simulation' and 'Always destroy simulations when conversation ends or changes topic.' Provides clear when-to-use guidance and implies not to use while simulation is still needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It explains how body types behave, collision interactions, sensor mode, drag physics, default values, and return value. It also clarifies nuances like box size being full extents and plane shape not needing size. Extremely transparent.
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?
The description is well-structured: summary, parameter list, tips, examples. It is front-loaded with purpose. However, it is somewhat verbose—each parameter has a sentence explaining its default—but this is justified by the complexity (21 parameters). A minor improvement would be to group defaults more succinctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description still explains the return value (body_id). It covers all parameters, prerequisites, behavioral nuances (collisions, sensor mode, drag), and provides multiple examples. For a 21-parameter tool, this is highly complete. Missing error handling info, but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must (and does) provide all parameter details. It explains each parameter's meaning, valid values, defaults, and inter-dependencies (e.g., plane uses normal/offset). Examples illustrate usage. This adds immense value beyond the raw schema.
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 adds a rigid body to an existing simulation, with detailed subtypes (static, dynamic, kinematic). It distinguishes from siblings like create_simulation (creates the simulation) and add_joint (adds constraints). The example usage makes its purpose unmistakable.
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 implies the simulation must already exist (prerequisite). It provides tips like creating ground first and shows common use cases in examples. However, it does not explicitly exclude alternative tools or state when not to use this tool (e.g., for modifying existing bodies). But the context is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully covers behavior: it computes a force vector and magnitude, and provides tips about Earth's gravity and common accelerations. No destructive side effects exist, so this is transparent.
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?
The description is well-structured with Args, Returns, Tips, and Example, but the Tips section is somewhat verbose for an LLM. Overall, it is clear and front-loaded, with minimal redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides complete information: parameters, return value details, and a worked example, ensuring the agent can invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds detailed semantics: mass must be positive, acceleration components in m/s², and the formula. This compensates fully for the lack of schema descriptions.
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 explicitly states 'Calculate force from mass and acceleration using Newton's Second Law (F = ma)', with a specific verb and resource. It distinguishes from sibling tools like calculate_drag_force or calculate_angular_acceleration by focusing on the fundamental F=ma relation.
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 says 'Fundamental for dynamics, engineering, and understanding motion', implying it is the default choice for basic force calculations. It does not explicitly mention when not to use or alternatives, but the context of being fundamental provides adequate guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that momentum is always conserved and explains energy loss behavior with the coefficient. It does not mention any side effects, limitations, or edge cases, but the core behavioral traits are well-covered.
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?
The description is thorough but somewhat lengthy. It is well-structured with sections (Args, Returns, Tips, Example), which aids clarity. However, some parts (like Tips for LLMs) add valuable context but could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of output schema and sparse input schema, the description fully compensates by detailing all parameters, return values, and physical context. It is complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds extensive meaning: units (kg, m/s), format of velocity (array or JSON string), range and defaults for coefficient, and full return fields. This is far beyond the bare schema.
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 calculates 3D inelastic collisions with a coefficient of restitution, differentiating it from sibling tools like calculate_elastic_collision_3d. The verb 'calculate' and resource '3D collision' are specific, and the context of energy loss is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool, including coefficient of restitution values and example use cases (e.g., billiard balls vs. car crashes). It also clarifies momentum conservation and offers tips for LLMs, leaving little ambiguity about appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It fully discloses the formula, all parameters, return values, and limitations (circular orbits only). Tips and examples further clarify behavior.
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?
The description is well-structured with formula, Args, Returns, Tips, and Example sections, but is somewhat verbose. Could be slightly more concise without losing key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is remarkably complete: it explains purpose, all parameters, full return dictionary with four fields, helpful tips, and a worked example. No gaps for an LLM to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description explains each parameter in detail, including units, default for gravitational_constant, and provides concrete examples with values.
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 calculates orbital period using Kepler's Third Law for circular orbits, with specific verb 'Calculate orbital period' and equation. It is distinct from sibling tools like 'analyze_circular_orbit' which likely does more comprehensive analysis.
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 provides clear context for when to use this tool (calculating orbital period for circular orbits) but does not explicitly mention when not to use it or compare to alternatives like 'analyze_circular_orbit'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: formula, dependence only on length and gravity, large-angle correction, and return structure including small_angle_approximation flag. No contradictions.
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?
The description is well-structured with formula, args, returns, tips, and example. It is slightly lengthy but every section adds value. Front-loaded with the formula.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully specifies the return dict. It covers theory, parameters, output, and includes an example. Complete for a simple physics tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains each parameter in detail: length in meters from pivot to center of mass, gravity default 9.81 m/s², optional amplitude_degrees for correction. It also describes the return dict.
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 calculates the pendulum period using the formula T = 2π√(L/g). The verb 'calculate' and resource 'pendulum period' are specific. It is distinct from sibling tools like calculate_orbital_period or calculate_spring_mass_period.
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 provides implicit usage context through tips (e.g., independence of mass, small angle approximation) and an example. However, it does not explicitly state when to use this tool over siblings like calculate_simple_harmonic_motion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fully compensates by detailing method (RK4), forces, and return fields. No contradictions.
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?
Long but well-organized with sections, formulas, and examples. Could be slightly trimmed but earns its length due to complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description fully documents return dict. Examples cover diverse scenarios. Complete for a complex projectile tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description documents all 15 parameters with defaults, units, and common values, adding immense value well beyond schema.
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?
Clearly states tool calculates projectile motion with drag using numerical integration. Distinguishes from sibling calculate_projectile_motion explicitly.
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?
Provides explicit comparison with no-drag version and multiple sports examples, guiding when to use. Lacks explicit 'when not to use' but context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It fully discloses the behavior: vector inputs as JSON or arrays, optional time, return structure with work and possibly power (None if no time). No contradictions.
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?
The description is well-structured with sections for Args, Returns, and an Example. It is informative but not overly verbose. Minor redundancy (repeating formulas in text and example) but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully explains return values (work and power). It covers all parameters, usage, and provides a concrete example. With many sibling tools, this is self-contained and complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so description adds crucial meaning: force and displacement are 3D vectors in specific units (Newtons, meters) and can be arrays or JSON strings. Time is in seconds. This goes far beyond the schema.
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 'Calculate work done by a force and optionally power.' It provides the specific formulas and distinguishes itself from many sibling physics tools by focusing on work and power computation.
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 explains that power calculation is optional and requires a time parameter. It includes an example. However, it does not explicitly state when not to use this tool or mention alternatives, but given the sibling set, the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully discloses the tool's behavior: it performs a conservation check computation, returning a dictionary of results. It implies no side effects, which aligns with the tool's nature.
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?
The description is well-structured with sections (Args, Returns, Tips, Example) and front-loads the core purpose. However, the tips and example add length; minor trimming could improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully covers inputs, outputs (all fields of return dict), and provides educational context about angular momentum conservation, making it complete for an agent to use correctly without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds extensive meaning beyond the schema: specifies units (kg⋅m²/s), format (JSON string), and default tolerance (0.01 = 1%), plus an example. The schema has 0% coverage, so the description fully compensates.
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 the verb 'verify' and the resource 'conservation of angular momentum', and the purpose is distinct from sibling tools like check_momentum_conservation (linear) and check_energy_conservation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use context (no external torques), examples (ice skater, gyroscope, planets), and a full example with input values, guiding the agent on proper usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It explains the underlying model (spheres with constant velocity), the analytic method, and the return values. However, it does not discuss edge cases or error handling, which would make it fully transparent.
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?
The description is well-structured with sections (Args, Returns, Tips, Example) and is appropriately front-loaded. It is somewhat lengthy but justified by the tool's complexity. Minor redundancy in the example could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete: it explains all parameters, return values, assumptions, and provides a usage example. It covers the tool's behavior thoroughly given the absence of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, the description thoroughly explains each parameter in the Args section, adding meaning beyond the schema's type definitions (e.g., units, positivity constraints). This compensates for the lack of schema descriptions.
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 the tool's purpose: "Check if two moving spherical objects will collide." It specifies the exact function and distinguishes itself from siblings by mentioning an alternative tool for complex shapes or forces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance, including when to use this tool (e.g., asteroid tracking, car crash prediction) and when to use an alternative: "For complex shapes or forces, use create_simulation instead." It also includes an example.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description explains bounce detection via velocity reversals near ground, the role of bounce_height_threshold, and the returned fields (bounces with time/position/speeds/energy loss). It does not cover potential side effects or performance considerations, but adequately discloses key behavioral traits.
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?
Well-structured with clear sections: short intro, formatted Args/Returns, actionable Tips, and a concise Example. Every sentence adds value; no fluff. Length is appropriate for the tool's complexity.
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?
Covers purpose, parameters, return structure (frames, bounces, contact_events), and typical use case with an example. However, it lacks details on the output fields beyond bounces, and does not mention how contact_events will be structured or if any side effects occur on the simulation. Still, it is largely complete for a simulation tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema provides only types and defaults (0% description coverage). The description fully compensates with detailed Args documentation explaining each parameter's purpose, default behavior, and practical usage (e.g., dt override, bounce_height_threshold meaning). The example shows concrete parameter values.
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?
Clearly states the tool records trajectory and detects collision/bounce events, enhancing the sibling record_trajectory. The description explicitly differentiates by labeling it an 'enhanced version' and listing detected event types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use this instead of record_trajectory when you need event detection.' The Tips section further advises on when to adjust parameters like bounce_height_threshold, and includes an example that demonstrates typical usage for bounce counting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: it conserves both momentum and energy, returns final velocities and verification quantities. The example demonstrates expected behavior (ball 1 stops, ball 2 moves). No hidden side effects or destructive actions.
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 well-structured with clear sections (Args, Returns, Tips, Example). Every sentence adds value—no fluff. Front-loaded with main purpose, then details. Appropriate length for a physics tool with multiple parameters and a complex output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully specifies return values (two velocity arrays, two momentum vectors, two energy values). It includes an example with realistic values and expected outcome, covering all necessary context for an AI agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters are explained with units, types, and input formats (list or JSON string). The schema has 0% description coverage, so the description compensates fully, adding meaning beyond bare schema like 'velocity of object 1 [x, y, z] in m/s (or JSON string)'.
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 the tool's function with specific verb and resource: 'Calculate 3D elastic collision (perfect energy conservation).' It distinguishes from siblings by explicitly noting it's the elastic version (e=1.0) and hints at 3D specificity, differentiating from potentially 2D siblings like 'calculate_elastic_collision'.
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 provides when-to-use tips (e.g., 'Ideal approximation for billiard balls, Newton's cradle') and key physics behavior (equal masses exchange velocities). It does not explicitly mention when not to use or compare to inelastic version, but the special case note and example imply appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses behavior: the formula, parameter meanings, return values, and even the negative sign implication. It is completely transparent.
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 yet comprehensive, with a clear structure: formula, explanation, parameter details, return, tips, and example. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete for a simple 2-param tool without output schema. It covers purpose, physics, parameters, return values, and provides an example.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description compensates fully by explaining each parameter's units and meaning, and also describes the return structure.
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 calculates spring force using Hooke's Law, with a clear verb and resource. It distinguishes from siblings like calculate_force by specifying the exact law and application.
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 provides context for when to use (springs, elastic materials, SHM) and includes tips, but does not explicitly state when not to use or compare to similar tools like calculate_elastic_collision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully discloses behavior: kinetic energy is scalar, mass must be positive, velocity components in m/s, returns kinetic energy and speed. Comprehensive behavioral context.
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?
Well-structured with sections: description, args, returns, tips, example. Each section adds value, no fluff. Front-loaded with formula and purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete description for a 4-parameter tool with no output schema. Explains formula, units, scalar nature, tips, example, and return values thoroughly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but the description explains each parameter (mass in kg, positive; velocity components in m/s) and provides an example and tips, adding significant meaning.
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?
Clearly states 'Calculate kinetic energy from mass and velocity (KE = ½mv²)' with a specific verb and resource. Distinguishes from sibling tools by focusing on kinetic energy.
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?
Provides context for use (collision analysis, vehicle safety, energy transfer) but does not explicitly state when not to use or differentiate from other energy tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavioral traits: it models ideal ballistic motion without air resistance, describes parameters and their constraints, and details the return structure. There are no contradictions.
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 well-structured with clear sections (summary, Args, Returns, Tips, Example). It is thorough without being verbose; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers return fields in detail. All four parameters are explained, and usage context is provided. The example and tips ensure completeness for an LLM.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides detailed parameter semantics: initial_velocity must be positive, angle_degrees range 0-90 with explanation, default values for initial_height and gravity, and alternative gravity values. This fully compensates.
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 the tool calculates projectile motion using kinematic equations, listing outputs like max height, range, time of flight, and trajectory points. It distinguishes itself from sibling tools like calculate_projectile_with_drag by explicitly specifying that air resistance is not modeled.
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 provides use cases (ballistics, sports, education) and tips (45° for max range, conversion to 3D). It implies when not to use (when air resistance matters) but does not explicitly name alternative tools. This is clear enough but could be more direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It fully discloses the output structure (position, velocity, acceleration) with formulas and units, plus tips about phase relationships and maxima. This is completely transparent.
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 well-structured with distinct sections: formula, description, Args, Returns, Tips, and an example. Every sentence adds value without redundancy. The key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description thoroughly explains return values with formulas and units. It covers all four parameters, required and optional, and provides a complete example. The tips further enhance usability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It provides clear parameter explanations: amplitude in meters, angular_frequency in rad/s, time in seconds, phase in radians with default. This adds all necessary meaning beyond the schema.
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 explicitly states the tool calculates simple harmonic motion: position, velocity, and acceleration using the formula x(t)=A cos(ωt+φ). It identifies models like springs and pendulums, clearly distinguishing it from sibling tools that cover other mechanical calculations.
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?
While it doesn't explicitly state when not to use this tool, it provides context that it models ideal oscillating systems. The example and tips guide the agent on appropriate use cases. A score of 4 is given for clear context but no explicit exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses the tool's behavior: it computes static friction and optionally checks slip. It avoids any side effects, and the example clarifies the output format. No contradictions.
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 with Args, Returns, and Example sections. Each sentence adds value, and the example illustrates usage efficiently without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description documents the full return dictionary with fields and conditions. It also includes a concrete example. For a simple physics calculator, this is complete and covers all necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description compensates fully. It explains each parameter (normal_force, coefficient_static_friction, applied_force) with units and optionality, and provides example values. This adds significant meaning beyond the schema.
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 explicitly states the tool calculates maximum static friction force and determines slip condition. It provides the formula f_s,max = μ_s × N and an example, making the purpose highly clear and distinct from sibling tools like calculate_kinetic_energy or calculate_force.
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 includes when to use (to check if an object slips) and gives an example, but does not explicitly mention alternatives or when not to use (e.g., kinetic friction). Still, the context is clear enough for most scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully discloses behavioral traits: it advances simulation, returns complete state, includes timeout limits, and describes the return structure (SimulationStepResponse with bodies, time, etc.).
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 well-structured with a summary, parameter details, return info, tips, and example. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description completely covers return types and provides tips for effective use. Given the moderate complexity of a simulation stepping tool, it is fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description explains each parameter's meaning: sim_id is the simulation ID, steps is number of timesteps with default and example, dt is optional timestep override. This fully compensates for missing schema descriptions.
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 the tool steps the simulation forward in time using a specific verb ('step') and resource ('simulation'). It distinguishes from sibling tools like 'create_simulation' and 'destroy_simulation'.
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 provides tips on when to use specific step counts ('real-time preview' vs 'final result') and warns about timeouts for large steps. However, it does not explicitly state when not to use this tool or mention alternatives.
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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