DealScore

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

No annotations are provided, so the description carries the burden. 'Explain' implies a non-mutating read operation, and the alias to POST /api/explain adds a small amount of implementation context. However, it does not disclose return format, error behavior, or whether the operation has any 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.

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

The description is very concise: two short sentences, each earning its place. The core purpose is front-loaded, and the API alias sentence adds useful implementation context without redundancy.

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 explain tool, the description is minimally viable. It identifies the input and the operation, but with no output schema and no annotations, it leaves out what the explanation response looks like and what constraints apply to delta_pct.

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 0% and the description only names delta_pct without defining its meaning, valid range, or units. The phrase 'for a delta_pct' adds minimal context beyond the schema, and since coverage is 0%, the description should have compensated more.

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 states a specific verb ('Explain'), a specific resource ('the score_v1 rubric grade'), and an input ('delta_pct'). This clearly distinguishes it from its siblings: health is a health check and score_deal is about computing a score, while this tool explains an existing rubric grade.

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 intended use is implied: use this when you need an explanation of a score_v1 rubric grade for a delta_pct. However, it does not explicitly compare itself to score_deal or health, nor does it state when not to use it, so the guidance relies on inference.

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 behavioral burden. It discloses what the endpoint returns (health, coverage, cache policy, limitations) and identifies it as a GET request, which implies a read-only operation. However, it does not explicitly confirm no side effects, error behavior, or response structure.

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 short sentences with no filler. The content is front-loaded with the value proposition, and the endpoint mapping is a useful one-line addition. Every phrase earns its place.

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 health check, the description is largely complete without an output schema: it names the four content areas returned and gives the API endpoint. It could be slightly richer by noting whether the output is a simple status object or contains nested sections, but an agent can call it and inspect the response safely.

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 parametersched, so the schema fully describes the input surface. The description adds no parameter detail, but none is needed beyond the schema. This is the appropriate baseline for a parameterless tool.

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 states exactly what the tool reports: service health, coverage, cache policy, and limitations. Mapping it to GET /api/health removes ambiguity, and the sibling tools (explain_grade, score_deal) are clearly unrelated. This is a specific, unambiguous definition.

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 call it—when service status, coverage, cache policy, or limitations are needed—but does not explicitly state use cases or exclusions. It provides no guidance on alternatives, though the sibling tools are obviously different. Usage is clear by inference, not by instruction.

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?

No annotations are provided, so the description carries the full behavioral burden but does not say what the output looks like (a letter, a numeric score, a range?), whether it is deterministic, or what errors can occur. 'Same inputs/outputs as POST /api/score' references an external REST endpoint the agent cannot inspect, which adds no usable behavioral detail.

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?

Three short sentences with the core purpose front-loaded and no filler prose. The final API-endpoint sentence is of questionable value to an MCP agent, but the text is otherwise tight and well-ordered.

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 an 8-parameter tool with no annotations, no output schema, and 0% schema coverage, the description leaves too much unsaid: the meaning of a 'grade', how the market-value comparison is expressed, and the semantics of the six undocumented inputs. It is adequate only at the highest level of the operation.

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 0% across 8 parameters, so the description must compensate and mostly does not: required 'mileage' is never mentioned, and vin/make/model/trim/year are left entirely undocumented. The one statement given ('ZIP is optional') merely restates that zip is absent from the required list, adding no new meaning.

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+resource ('Grade a car deal') and immediately explains the operation: 'compare asking price to expected market value.' This is far clearer than the bare name, though it never distinguishes itself from the sibling 'explain_grade', leaving the boundary between scoring and explaining implicit.

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?

There is no explicit guidance on when to call this versus 'explain_grade' or what a valid call requires. 'ZIP is optional' is the only usage-style hint, and it is a parameter note rather than a routing instruction. An agent must guess the scenario boundary between the two grade-related siblings.

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