TradeBasis Automotive Appraisal MCP (US)

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

The description discloses that the tool returns static markdown with an as_of date, which is meaningful behavioral context. Since no annotations are provided, the description carries the burden adequately. It could add more but is sufficient for a simple read-only tool.

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

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

The description is two concise sentences, front-loaded with the core purpose, and contains no filler or redundant information.

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

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

For a simple, zero-parameter informational tool, the description fully explains what it returns (static markdown) and the content scope (what, problem, differentiation, audience). It is complete enough for an agent to know what to expect, though it could optionally clarify the as_of date further.

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

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

The tool has zero parameters, so the schema is fully covered. The description appropriately does not need to explain parameters; baseline of 4 is justified.

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

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

The description clearly states what the tool does: it returns static markdown about TradeBasis, including the problem it solves, differentiation, and target audience. This is specific and distinguishes it from siblings like pricing and research library tools.

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

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

Usage context is implied (use this for an overview of TradeBasis), but there is no explicit guidance on when to use this tool versus the sibling tools tradebasis_pricing_and_tiers or tradebasis_research_library. No alternatives or exclusions are mentioned.

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

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

The description discloses that this is 'Static markdown', which is a useful behavioral trait indicating no dynamic data or side effects. However, with no annotations provided, the description carries the full burden. It doesn't mention that no parameters are needed or that the content is fixed, though 'Static markdown' partially covers this.

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

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

The description is a single, compact sentence that front-loads the key information: the tool name, the two tiers, pricing, and what it covers. No wasted words.

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

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

For a zero-parameter, static content tool, the description is largely complete. It tells the agent what the tool returns and that it's static. It could mention that it's a reference/comparison rather than a transactional tool, but 'Static markdown' covers the essential context.

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

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

The tool has zero parameters, so the description doesn't need to explain parameter semantics. The baseline for 0 params is 4. The description adds value by summarizing what content the tool returns (pricing, inclusions, target audience).

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

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

The description clearly states the tool's purpose: comparing TradeBasis subscription tiers (Lite vs Pro) with pricing and target audience. It uses a specific verb ('pricing and tiers') and resource ('TradeBasis subscription tiers'). It doesn't explicitly differentiate from siblings, but the subject matter is distinct enough from 'about' and 'research_library'.

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

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

The description implies when to use this tool: when a user asks about TradeBasis plans, pricing, or what's included in each tier. It doesn't explicitly state when not to use it or name alternatives, but the sibling names (about, research_library) provide enough context for an agent to infer the right choice.

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

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

With no annotations, the description carries full responsibility for behavioral disclosure. It states that the content is 'static' and 'returns static markdown,' which implies a read-only operation with no side effects. It also explains the different behavior for list vs. retrieve, providing useful transparency beyond the bare minimum.

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

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

The description is two sentences long, front-loaded with the tool's purpose, and contains zero wasted words. It efficiently covers both invocation modes and the return format.

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

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

For a simple tool with one optional parameter and no output schema, the description provides all necessary context: how to list vs. retrieve, what the parameter means, and what the return value looks like (static markdown). It is complete for the tool's complexity.

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

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

The schema already fully describes the 'topic' parameter (brief slug or title, omit to list all briefs). The description repeats this information without adding new semantic details, so the baseline score of 3 is appropriate given the high schema coverage.

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

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

The description clearly states the tool's function: providing static research/market-report briefs, with explicit instructions to list all briefs when called with no arguments or retrieve a single brief by topic. This distinguishes it from the sibling tools (about, pricing) by its focus on research briefs.

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

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

The description gives clear usage direction: call with no arguments to list available briefs, or pass a topic (slug or title) to retrieve a specific brief. It does not explicitly mention alternatives or when not to use, but the sibling tool names are sufficiently distinct that the use case is obvious.

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

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

With no annotations, the description carries the full behavioral burden and largely succeeds. It communicates that this is an identification-only, non-valuation operation and enumerates the output fields across vehicle identity dimensions. It does not mention invalid-VIN handling or response shape, but for a simple read-only decode the key behavioral boundaries are disclosed.

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

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

Two tight sentences with no filler. The core action and output fields are front-loaded, followed by a crucial scoping exclusion that prevents misuse.

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

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

For a single-parameter tool with no output schema, the description adequately explains the return values by listing the identity fields and clarifying what the tool will not return. It could optionally describe response format or error behavior, but nothing essential is missing for an agent to call this tool correctly.

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

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

Schema description coverage is 100% and the schema already documents the vin parameter as 'The 17-character Vehicle Identification Number to decode.' The description reinforces the 17-character constraint and ties the output to the parameter, but adds no new semantic detail about parameter usage beyond the schema.

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

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

States a specific verb ('Decode'), the exact resource (17-character VIN), and the concrete identity fields returned. The 'Identification only' clause and explicit exclusions (no valuation, no comparable listings, no market data) make it easy to distinguish from other tradebasis data tools.

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

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

The description clearly signals when to use this tool for VIN decoding and, more importantly, when not to use it: it explicitly states it returns no valuation, comparable listings, or market data. It does not name a specific alternative tool, but the exclusion guidance is strong enough for an agent to route correctly.

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