Lo Shu grid numerology for India: life path, Chaldean name number, compatibility.
Scored across 4 tools
Each tool targets a distinct calculation: pair compatibility, individual life path, Lo Shu grid, and name numerology. The overlapping birth-date inputs for lifePath/loShuGrid are differentiated by output and description, so misselection is unlikely.
Names are noun-based domain labels, with lifePath, loShuGrid, and nameNumber in camelCase; compatibility is a single lowercase word, a minor inconsistency. The set is still predictable and readable.
Four tools is well within a reasonable range and each maps to a distinct numerology workflow; no tool appears redundant. The surface is appropriately scoped for a focused calculator server.
Core numerology operations are covered: birth-date life path, Lo Shu grid, name number, and two-person compatibility. Minor potential gaps include combined reports or name-based compatibility, but agents can work around them.
Takes two birth dates (dobA, dobB, YYYY-MM-DD) and returns a 0 to 100 harmony score, a label and the reasons from life path and mulank. Example input: {"dobA":"1990-05-14","dobB":"1992-11-03"}
| Name | Required | Description | Default |
|---|---|---|---|
| dobA | Yes | First person's birth date, YYYY-MM-DD | |
| dobB | Yes | Second person's birth date, YYYY-MM-DD |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It does disclose the return shape (0-100 score, label, reasons) and the underlying computation basis (life path and mulank), which is useful. It omits error behavior for invalid dates, whether the result is symmetric for (A,B) vs (B,A), and whether the score is deterministic.
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 compact sentences plus an example input; the output contract is front-loaded and nothing is wasted. The example earns its place by resolving format ambiguity in one line.
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?
With no output schema, the description correctly supplies the return value shape itself, so an agent knows what comes back. It lacks only edge-case guidance (invalid dates, symmetry) for a two-parameter tool that is otherwise fully specified.
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 coverage is 100%, so the schema already documents dobA and dobB with format and pattern. The description reinforces the YYYY-MM-DD format and adds a concrete worked example, which is a modest value-add over 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 operation: takes two birth dates and returns a harmony score with label and reasons derived from life path and mulank. This implicitly distinguishes it from the single-person sibling tools (lifePath, loShuGrid, nameNumber) by being the pairwise comparison, though it never names them explicitly.
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 only implied by the two-person input shape; there is no explicit statement of when to use this versus the sibling numerology tools or any exclusions. An agent can infer it's for relationship/partner matching but the description doesn't confirm that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Takes a birth date (dob, YYYY-MM-DD) and returns the life path number (masters 11, 22, 33 kept) with its trail, plus mulank and bhagyank. Example input: {"dob":"1990-05-14"}
| Name | Required | Description | Default |
|---|---|---|---|
| dob | Yes | Birth date as YYYY-MM-DD, between 1900 and 2100 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does reasonably well: it discloses the input format, the returned fields (life path, trail, mulank, bhagyank), and a non-obvious behavioral rule that master numbers 11/22/33 are preserved rather than reduced. It does not cover error behavior for invalid dates or the shape of the 'trail' output.
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?
A single front-loaded sentence establishes input and outputs, followed by a compact example. Every clause carries information and nothing is padded.
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 one-parameter, no-annotation, no-output-schema tool, the description covers the essentials: valid input shape, what is returned, and the special master-number handling. The main remaining gap is how the 'trail' is structured and what happens on out-of-range or malformed dates.
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 coverage is 100% and already documents the dob format and the 1900–2100 range, so the description need not repeat it. It still adds value by supplying a concrete example payload ('{"dob":"1990-05-14"}') that makes the expected call trivially reproducible.
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 gives a specific verb ('takes a birth date') and a specific, enumerated output (life path number, trail, mulank, bhagyank), so the agent knows exactly what computation happens. It does not explicitly distinguish itself from siblings like nameNumber or loShuGrid, though the birth-date basis implicitly separates it.
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 only implied: the agent can infer 'call this when you need a life path number from a birth date.' There is no explicit statement of when to prefer this over nameNumber or loShuGrid, 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.
Takes a birth date (dob, YYYY-MM-DD) and returns the filled 3x3 Lo Shu grid with present, missing and repeated numbers, completed planes, the arithmetic trail and a short reading. Example input: {"dob":"1990-05-14"}
| Name | Required | Description | Default |
|---|---|---|---|
| dob | Yes | Birth date as YYYY-MM-DD, between 1900 and 2100 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it does disclose the shape of the return value: grid occupancy, planes, arithmetic trail, and a short reading. It omits any statement of read-only/pure-computation semantics or performance characteristics, but the deterministic birth-date-to-grid framing makes the non-mutating nature effectively implied.
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?
A single front-loaded sentence covering input and output, followed by a compact example. Every clause earns its place and nothing is padding.
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?
There is no output schema, so the description must describe return values, and it lists the grid contents, planes, arithmetic trail, and reading clearly enough for an agent to know what comes back. It stops short of describing the exact response structure or field names, which would be the remaining gap.
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 coverage is 100% and the single parameter is fully documented in the schema, including the pattern and the 1900–2100 range, so the baseline is 3. The description adds a concrete example input ({"dob":"1990-05-14"}) and repeats the YYYY-MM-DD format, which is genuinely useful for correct invocation.
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 gives a specific verb+resource: it takes a birth date and returns a filled 3x3 Lo Shu grid with present, missing and repeated numbers. This is clearly distinct from numerology siblings (lifePath, nameNumber, compatibility) that compute other things, though the description does not explicitly name those alternatives.
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 single-input design and the description of the output, so an agent can infer when to reach for this tool. However, there is no explicit statement about when to use this over the sibling numerology tools, and no prerequisites or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Takes a name in Latin letters (name) and returns its Chaldean destiny number, compound number and the per-letter trail. Example input: {"name":"Chloé"}
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name in Latin letters, up to 100 characters; accents are folded (Chloé becomes CHLOE) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full disclosure burden. It usefully reveals the returned components and the accent-folding behavior (Chloé becomes CHLOE), which sets expectations for input normalization, but says nothing about error behavior for non-Latin characters, whether the computation is deterministic, or the exact response shape.
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 sentences, front-loaded with the input-output contract, followed by one concrete example. Nothing is wasted and nothing essential is buried.
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, read-only calculation tool with no output schema and no annotations, the description is nearly sufficient: it names the returned values and clarifies normalization. It falls short only in not sketching the structure of the per-letter trail, which an agent may need to interpret the result.
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 coverage is 100%, so the single 'name' parameter, its length bounds, and accent folding are already documented in the schema. The description's example input adds only marginal value beyond that baseline.
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 (takes a name) and resource (name in Latin letters) and enumerates exactly what is returned: Chaldean destiny number, compound number, and per-letter trail. An agent can distinguish it from lifePath, loShuGrid, and compatibility because the input is a name rather than a birth date or grid, though no sibling is named explicitly.
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 rather than stated: an agent can infer this is the name-based numerology calculation, and the example input models a call. There is no explicit when-to-use, when-not-to-use, or pointer to a sibling tool for other numerological calculations.
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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