FFT Companion

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

No annotations provided, so description carries full burden. It clarifies the tool is read-only (compares, not modifies), reports exact field changes, and requires entity id and kind. Lacks details on edge cases like missing entities but overall transparent.

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 sentences, front-loaded with purpose and examples, no redundancy. Every sentence 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?

Given 3 params, no output schema, and complexity of cross-version diffing, the description covers purpose, usage, and output format (reports field changes). Examples and sibling differentiation make it 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 coverage is 67% (2 of 3 params described). Description adds value through examples and context, but does not significantly expand beyond schema descriptions for id, kind, and versions. 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?

Description explicitly states it compares an entity across psx, wotl, and ic releases and reports field changes, with concrete examples like weapon nerfs or restrictions. Distinguishes from sibling tools by focusing on cross-version diffing.

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?

Clearly states when to use (comparing across releases) with examples, and mentions it's free while unmetered. Does not explicitly list when not to use or alternatives, but context is sufficient.

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 full weight. It discloses that the data is indexed backwards from game data and that the tool is free while unmetered. For a read-only lookup tool, this is adequate behavioral context.

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 sentences, front-loaded with the purpose. Every sentence adds essential information: action, scope, technical detail, and status. No unnecessary 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?

Given the tool has 2 required params and no output schema, the description sufficiently explains the purpose and parameters. It lacks details on return format, but for a reverse lookup tool the description is mostly 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 coverage is 100%, but the description adds value by providing examples (e.g., 'excalibur') and expanding on the version enum with clear explanations of each option and noting data differences between versions.

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 uses a specific verb "Reverse lookup" and clearly states the resource: every way to obtain an item. It lists specific sources (outfitter, monsters, treasure tiles), distinguishing it from sibling tools like get_monster or query_equipment.

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 this tool is for reverse lookup and is not readable from the item record alone, implying when to use it. However, it does not explicitly state when not to use it or mention alternatives, though the context is clear.

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 provided, the description carries the full burden. It explains the returned data comprehensively but does not disclose behavioral traits such as whether the operation is read-only, if authentication is required, or any rate limits. The note about being 'free and unmetered' is a pricing signal, not a behavioral one.

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 concise and front-loaded with core purpose, but it includes a pricing statement ('Free while this deployment runs unmetered') that is not essential for tool selection or invocation. This slightly reduces conciseness, though the structure is otherwise clear and well-organized.

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 that there is no output schema, the description thoroughly explains the return values: stat multipliers, growth, move/jump/evasion, ability sets with JP costs, equipment types, and stat ceilings. This covers all expected data for a job record tool, making it contextually 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?

The description adds no additional meaning for the parameters beyond the input schema. With 67% schema description coverage (2 of 3 parameters documented), the missing parameter 'lang' has a default and enum but no explanation. The description does not clarify how parameters like version affect output or provide examples.

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: returning a full job record including stat multipliers, growth, abilities with JP costs, equipment types, and stat ceilings. It effectively distinguishes itself from siblings like get_monster and query_equipment by specifying the unique data it provides.

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 does not explicitly state when to use this tool versus alternatives. While the sibling tools have different purposes (e.g., compare_versions for version comparison, find_item_sources for item locations), there is no guidance on contextual trade-offs or prerequisites like requiring a specific version or jobId.

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 the tool is free and unmetered, providing cost/usage transparency. Given no annotations, it adequately conveys that this is a read operation returning comprehensive monster data, though it could note that it does not modify data.

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-loading the key contents of the response and then a bonus note about free usage. 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?

Without an output schema, the description lists the major response fields (stat multipliers, poach drops, abilities, locations). It covers the essential information an agent would need to decide whether to call this tool, though it omits size limits or pagination.

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 description does not add parameter-level details beyond what the schema provides. Schema already covers version and monsterId with descriptions; lang lacks description but is an enum with default. The description's lack of parameter elaboration results in a baseline score.

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 it returns a full monster record including poach drops, abilities, and spawn locations. It distinguishes itself from sibling tools like search and get_records by being monster-specific.

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 mentions the tool is free for the deployment, which is a usage context. However, it does not provide guidance on when to use this tool versus alternatives like search, nor does it mention prerequisites or caveats.

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 full burden. It discloses that results include resolved cross-references and that the tool is free and unmetered, but does not mention authentication, rate limits, or side effects (assumed read-only). Useful but incomplete.

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: first sentence delivers core purpose and constraints, second adds a usage perk. Every word earns its place, no 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?

With 4 parameters, 3 required, no output schema, the description adequately states inputs (IDs, kind, version implied) and lists what is returned (stats, costs, effects, availability, resolved names). Omits output shape but sufficient for an agent to understand functionality.

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 50% (descriptions for ids and version only). The description adds context such as 'up to 25 ids' and 'one entity kind', but does not describe the 'lang' or 'kind' parameters beyond their enum values. The baseline of 3 is appropriate as description partially compensates but does not fully cover missing schema details.

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 ('Returns') and resource ('complete records') along with constraints ('up to 25 ids of one entity kind') and included content ('stats, costs, effects, availability'). It clearly differentiates from siblings like get_job or search by emphasizing bulk retrieval with cross-references resolved.

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 use when you need full record details from known IDs, but lacks explicit guidance on when to use this vs. alternatives like get_job or query_equipment. No mention of when not to use or prerequisites.

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 full burden. It discloses the tool's output scope (three releases, record counts) but omits other behavioral traits like authentication or cost. Adequate for a simple read-only list.

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 with no wasted words. The first sentence states the primary function, the second provides usage guidance. Highly concise and front-loaded.

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?

The description is mostly complete for a simple tool with no parameters and no output schema. It could mention the output format briefly, but the essence is covered.

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?

No parameters exist, so baseline is 4 per guidelines. The description adds no param info, which is acceptable given zero parameters.

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 that the tool lists the three Final Fantasy Tactics releases and record counts per entity kind, which is specific and distinguishes it from sibling tools like compare_versions.

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?

Explicitly advises 'Call this first to pick a version,' providing clear guidance on when to use the tool. Does not elaborate on when not to use it, but the context implies it's a prerequisite.

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 burden. It discloses that the tool is free and unmetered, but fails to mention that version is required, what happens with no results, or any authentication needs. The behavioral profile is partially transparent but has gaps.

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 extremely concise: two sentences that front-load the purpose and then provide usage guidance and cost note. No unnecessary words; every sentence serves a distinct function.

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 8 parameters (including nested minStat) and no output schema, the description is short but omits important context like return format, required version emphasis, and pagination. It is adequate for a simple query 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?

The description adds conceptual meaning by mapping filter types (category, cost, stat thresholds) to parameters, but 63% schema coverage means the schema already details some parameters. It does not explain parameters like version, lang, or limit beyond what the schema offers, so the added value is moderate.

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 filters and sorts the equipment table by category, weapon/armor type, cost, and stat thresholds. It directly differentiates from the sibling tool get_records with the instruction to 'use this instead of paging through get_records when shopping', making the purpose unambiguous.

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 provides explicit guidance on when to use this tool ('when shopping for best X under Y gil') and distinguishes it from get_records. However, it does not mention other sibling tools like search or find_item_sources, limiting comprehensiveness.

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 burden. It discloses that results contain only ids and display names, matches multiple languages, and is punctuation-insensitive. It does not discuss idempotency, rate limits, or empty result behavior, but these are less critical for a search 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?

Two sentences with no filler. First sentence gives purpose and scope, second sentence provides return format, guidance to other tools, and search behavior. Every sentence adds value and is front-loaded.

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 5 parameters, the description covers purpose, return format, and search behavior. It does not mention limit pagination or sorting, but overall adequately positions the tool among siblings.

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 60%; the description adds meaning to query (language/punctuation behavior) but does not mention lang, limit, or kinds parameters beyond schema. It partially compensates but leaves gaps in explaining limit's role in pagination or kinds' filtering effect.

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 finds entities by name or id across a specific list of kinds, distinguishes it from sibling tools like get_records by specifying it returns only ids and display names, and directly says to use get_records or specific data tools for full data.

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?

Explicitly directs users to get_records or specific data tools when full data is needed, and mentions language coverage and punctuation-insensitivity. However, it does not explicitly state when to avoid this tool in favor of more specialized sibling tools like find_item_sources or get_job, though the context of multi-kind search is clear.

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