FLAMES name game plus love and friendship calculators by name. A game, not a prediction.
Scored across 3 tools
All three tools take the same two-name inputs, and friendshipScore vs loveScore are near-identical letter-count percentage calculations differing only by algorithm. The descriptions do clarify the distinct outputs (relationship word vs FRIENDS % vs LOVES %), which prevents outright confusion, but an agent asked for 'compatibility' must guess which of the three game variants is intended.
Two tools use camelCase noun-with-suffix names (friendshipScore, loveScore) while the third is a bare lowercase word (flames). The style is readable and thematically coherent (each names a game), but the convention is not uniform.
Three tools is a small but reasonable surface for a novelty FLAMES-style game API, with each tool corresponding to one game mode. Nothing feels padded or missing at this scale.
The three common name-compatibility games (FLAMES, FRIENDS, LOVES) are all covered with detailed outputs including intermediate steps. Only minor gaps exist—no aggregate/compare-all mode or plain-text summary—but the core domain is fully served.
Takes two names (a, b) and returns the FLAMES relationship word (Friends, Lovers, Affection, Marriage, Enemies or Siblings) with the struck letters and each round. Example input: {"a":"Rahul","b":"Priya"}
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First person's name in Latin letters (A to Z), for example Rahul | |
| b | Yes | Second person's name in Latin letters (A to Z), for example Rahul |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations the description carries the full burden. It does disclose the return payload (the FLAMES word plus struck letters and per-round detail), which is valuable given there is no output schema, but it says nothing about determinism, purity, or error behavior for inputs like empty strings or duplicate letters.
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?
One front-loaded sentence plus an inline example payload, no filler. The only rough edge is the awkward phrasing 'with the struck letters and each round', which muddies the return-shape claim rather than adding length.
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 pure two-string calculator the description is mostly sufficient, but with no output schema the return structure ('struck letters and each round') stays undefined — an agent cannot know whether it gets a string, an enum, or an object with step records.
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 'Latin letters, e.g. Rahul' semantics and the 80-char cap are already documented in the schema. The description only restates the two-name arity and adds an example payload, which is the baseline-3 case where the schema does the heavy lifting.
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?
Names a concrete operation and its resource: takes two names and returns the FLAMES relationship word, with the six possible outcomes enumerated. It is clearly distinguishable from friendshipScore/loveScore in terms of output, though it never says so 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?
No statement of when to use this versus the sibling scorers (friendshipScore, loveScore), which are the obvious competing choices for a two-name compatibility query. Usage is only inferable from the described output.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Takes two names (a, b) and returns the FRIENDS letter-count friendship percentage, with the letter counts and the adding trail. Example input: {"a":"Rahul","b":"Priya"}
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First person's name in Latin letters (A to Z), for example Rahul | |
| b | Yes | Second person's name in Latin letters (A to Z), for example Rahul |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the tool returns a percentage plus letter counts and an adding trail, but it does not explicitly state that the operation is stateless, what happens with invalid input, or whether errors are returned for non-Latin characters.
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, front-loaded with the core purpose and followed by a compact example. Every sentence adds useful information without repetition or filler.
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 explain return values, and it does so by naming the friendship percentage, letter counts, and adding trail. It is nearly complete for a simple computation tool, though it omits edge-case or error behavior.
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 input schema already documents that a and b are required name strings with examples and a Latin-letter constraint. The description's example adds a concrete usage pattern but does not contribute meaningfully beyond the schema's parameter documentation.
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 action: it takes two names (a, b) and returns a FRIENDS letter-count friendship percentage, including the letter counts and adding trail. This is a clear verb-and-resource statement, but it does not explicitly distinguish the tool from its siblings flames and loveScore.
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 no guidance on when to use this tool versus the clearly related siblings flames and loveScore. It provides an example input but does not state conditions, exclusions, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Takes two names (a, b) and returns the LOVES letter-count love percentage, with the letter counts and the adding trail. Example input: {"a":"Rahul","b":"Priya"}
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First person's name in Latin letters (A to Z), for example Rahul | |
| b | Yes | Second person's name in Latin letters (A to Z), for example Rahul |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description has to carry the whole burden. It does disclose the return shape: the percentage, the per-letter counts, and the adding trail. It does not state that the tool is a pure, side-effect-free computation with no auth or rate limits, nor does it detail the output format, which is a meaningful gap when no annotations are provided.
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 definition is one dense sentence plus a short example, and the purpose is front-loaded. It is efficient, though the example partly duplicates the schema's own examples.
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 explain the return values, and it names the elements, which is percentage plus counts plus trail, but not their format or ordering. For a simple two-parameter toy computation this is adequate but not fully complete.
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 the schema already documents both parameters, including the Latin-letters constraint and the max length. The description only restates that a and b are names and repeats an example already present in the schema, so under the high-coverage baseline it earns a 3.
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 and resource: it takes two names and returns a LOVES letter-count love percentage plus the letter counts and the adding trail. That is much more specific than a restatement of the name. It does not explicitly contrast itself with the siblings flames or friendshipScore, 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?
The description supplies an example input, but it never says when to call this tool rather than flames or friendshipScore, or what distinguishes the two scoring systems. There is no when-to-use or when-not-to-use guidance at all.
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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Pythagorean and Chaldean systems, Kabbalistic numbers, destiny and name analysis.
Free Vedic astrology: panchang, kundali, transits, matching, doshas, eclipses, numerology
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