Wedtide wedding seating

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

No annotations exist, so the description carries the full burden and does so richly: privacy model ('Nothing is stored on a server; the guest list is encoded in the link'), persistence ('saved on the user's device'), partial-failure behavior ('anything that could not be satisfied'), and a directive about the return value ('Give the user both links unchanged'). This is exactly the behavioral context an agent needs for a mutation-like generator with no annotations.

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?

Front-loaded with the core action, then usage, then output/behavior, then a usage directive. Every sentence adds distinct information (what it does, family handling, outputs, storage) with no repetition of schema text. Efficiently sized for a 5-parameter generator.

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 tool with no output schema and no annotations, the description fully explains the two returned links, their purpose, device-local persistence, partial-failure reporting, and how to relay the result. Nothing an agent needs to call and use the tool correctly is missing.

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 baseline is 3, but the description adds real value: it explains that couples/families on one line stay together and that 'rules keep named guests apart or together,' which gives the rules parameter operational meaning beyond the schema. It doesn't add syntax guidance for seats_per_table or setting, keeping it from a 5.

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 opens with a specific verb+resource ('Arrange a wedding guest list at tables') and adds the distinctive output ('return a link that opens the plan in Wedtide'). This clearly separates it from the only sibling, seating_tips, which by its name sounds advisory rather than a generator. An agent can route without ambiguity.

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?

It states when to use it: 'whenever the user shares a guest list (pasted names, a spreadsheet, CSV) and wants a seating chart or table assignments.' It also implicitly distinguishes itself from seating_tips by being about producing a plan rather than giving advice. However it never names seating_tips or states an explicit exclusion, so it falls short of a 5.

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 burden, and it does disclose the output content (a topic menu of etiquette guidance), the optional-parameter effects, and the fallback that unknown culture values get general guidance. It does not state that the tool has no side effects or describe the response format, which keeps it short of a 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?

Two front-loaded sentences: coverage/topic scope first, then usage trigger and optional-parameter effects. Every clause carries information an agent can act on, with no 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?

For a two-optional-parameter knowledge tool with no output schema, the description adequately covers scope, trigger, and parameter behavior, and 'concise, practical' hints at response style. A brief note on what the returned guidance looks like would make it fully self-sufficient.

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 'for a table count' meaning of guests and the unknown-value fallback for culture. The description's 'culture adds notes for some traditions; guests adds a table count' largely restates that, adding little new semantics.

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 resource and scope: wedding seating etiquette covering head table, parents, kids tables, plus-ones, singles, and table counts. It is clear this is an advisory/knowledge tool rather than a plan generator, but it never names the sibling create_seating_plan, and 'who should sit where' could plausibly be read as a plan request.

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?

Gives an explicit trigger: 'Use it when the user asks who should sit where or how to handle a delicate seating situation.' That distinguishes advice-seeking from plan creation in spirit, but it does not explicitly say when to prefer create_seating_plan over this tool, so no true exclusion is stated.

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