Lucky vehicle number calculator for India: plate digit sum scored against birth number.
Scored across 2 tools
plateTotal is a pure numeric reduction of a plate, while vehicleLuck adds a date of birth and produces a harmony score, so their purposes are distinguishable from the descriptions. However, the plate-total calculation is embedded in vehicleLuck's output, so an agent may wonder which tool to call for a plate-only question.
Both names use camelCase in a consistent noun+qualifier style (plateTotal, vehicleLuck) that reads predictably. They are not verb_noun, but the convention is uniform across the set.
Two tools is thin for a server, and one (plateTotal) largely duplicates a step already reported by vehicleLuck. For the narrow numerology domain the scope is defensible, but it sits at the borderline of being too small.
The core use cases—plate numerology and plate-vs-birth-number harmony—are covered with detailed outputs. Gaps remain: no way to compare two plates, batch-score candidates, or inspect/override the traditional friend/neutral/enemy table referenced in the descriptions.
Takes a registration plate and an optional letters flag (A=1..Z=26) and returns the plate total, a single number 1 to 9, with every addition step. Example input: {"plate":"MH12AB3456","letters":false}
| Name | Required | Description | Default |
|---|---|---|---|
| plate | Yes | Vehicle registration plate, letters and digits only, e.g. MH12AB3456 | |
| letters | No | Also count letters as A=1 to Z=26; default false counts digits only |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does disclose the return shape: a single number from 1 to 9 plus every addition step. It does not mention determinism, error handling, or validation behavior beyond the schema, keeping it below 5.
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, front-loaded sentence with a useful example and no wasted wording. The purpose, optional flag behavior, return value, and example are all packed efficiently.
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 two-parameter computational tool with no output schema and no annotations, the description adequately explains the calculation and return value. It could be more complete by clarifying the exact response structure and any error conditions, but the essentials are present.
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%, so both parameters are already documented in the schema. The description adds only a concise restatement of the letters flag mapping (A=1..Z=26) and an example input, which is baseline-level added value.
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-like operation ('takes a registration plate... returns the plate total') and resource (registration plate), making the core purpose clear. It does not differentiate from the sibling vehicleLuck, so it falls short of a 5.
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 is implied by the description of the computation and the example, but there is no explicit guidance on when to use this tool versus vehicleLuck or when not to use it. No alternatives or exclusions are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Takes a registration plate, a date of birth and an optional letters flag, and scores the plate against the owner's birth number. Sums the plate digits (digits only by default; letters mode adds A=1..Z=26), reduces to 1 to 9, reduces the day of birth to the mulank, looks up friend/neutral/enemy in the traditional table, and returns the plate total, mulank, harmony, a 0 to 100 score, the arithmetic trail and a one-sentence verdict. A number game, not advice. Example input: {"plate":"MH12AB3456","dob":"1990-08-17","letters":false}
| Name | Required | Description | Default |
|---|---|---|---|
| dob | Yes | Owner date of birth as YYYY-MM-DD; only the day is used for the mulank | |
| plate | Yes | Vehicle registration plate, letters and digits only, e.g. MH12AB3456 | |
| letters | No | Also count letters as A=1 to Z=26; default false counts digits only |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the calculation method, the returned fields, the default letters behavior, and that the result is 'a number game, not advice.' It does not mention side effects, but the operation appears to be a pure computation.
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 front-loaded with the tool's purpose and then explains the algorithm, outputs, disclaimer, and example input. It is dense but every part adds useful context. It could be slightly more structured, but there is little wasted text.
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?
Given no output schema and no annotations, the description compensates by listing the return values and explaining the scoring logic. It also provides an example input and a clear disclaimer. It is complete enough to invoke correctly, though it does not address error behavior or distinguish from the sibling tool.
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%, so all three parameters are already documented in the schema. The description explains the letters mode and mulank reduction, but this mostly restates or elaborates on information already present in the schema. Baseline 3 is appropriate.
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 operation: scoring a vehicle registration plate against the owner's birth number using numerology. It clearly identifies the inputs and output. However, it does not mention or distinguish the sibling tool plateTotal, so an agent must infer the difference.
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 explains what the tool does but gives no explicit guidance about when to use it versus plateTotal or other alternatives. It does not state prerequisites, exclusions, or typical use cases beyond 'a number game, not advice.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Free Vedic astrology: panchang, kundali, transits, matching, doshas, eclipses, numerology
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