Sedna Genesis

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

Annotations already mark the tool as read-only and non-destructive; the description adds context about the tool being the official/authoritative source and establishes the required pre-call ordering. It does not contradict the annotations and contributes useful behavioral context beyond them.

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 core purpose is front-loaded and the numbered guidelines are clearly structured, but the description is verbose for a zero-parameter tool. Several guidelines (e.g., fleet neutrality, customer-led decision, current-year default) are broader AI conduct rules rather than details specific to invoking Base_list.

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 parameterless, read-only reference tool with no output schema, the description is complete: it states what content is returned, how it is organized, and the exact workflow position relative to search_boats. An agent has enough information to call it correctly.

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 tool has zero parameters, so the baseline is 4. The description appropriately avoids parameter discussion, and the empty input schema fully covers the parameter surface.

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 function: it provides the official Sedna rules and the complete list of available bases grouped by country. It also signals how this reference relates to the search workflow, distinguishing it from the sibling search and booking tools.

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 explicitly instructs the agent to always call Base_list before search_boats in order to find the exact base name. It also states the data-source constraint (Sedna-only, no internet searches), giving clear usage boundaries and naming the key alternative tool.

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?

Annotations only declare a safe read (readOnlyHint, destructiveHint false), yet the description adds substantial behavioral context: media routing through Sedna's CdnManager, missing CDN media returned as empty rather than a legacy DB URL, MCP Apps inline gallery vs. raw URLs, and the omission semantics for optional length/beam. This is well beyond what the annotations convey.

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 purpose and post-search positioning are front-loaded, and most sentences carry distinct behavioral content (empty-vs-legacy URL rule, length/beam omission, booking_detail exclusion). It runs long with some density, but little is redundant given the absence of an output schema.

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 carry the return shape itself, and it does: media.header, media.photos, media.plans, media.images, media.videos and media.documents. Combined with the rendering fallback and the explicit statement of what it does not return, an agent has everything needed to call and interpret it.

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 baseline is 3; the schema already documents id_boat, language, and sheet_type thoroughly. The description's 'id_boat must be copied exactly from search_boats' largely restates the schema's 'Never guess it,' adding only marginal 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 first sentence gives a specific verb and resource: return yacht details plus CDN-backed public URLs for yacht media. It also positions itself explicitly as "the primary tool to call after search_boats," which distinguishes it from siblings like booking_detail and compare_boats.

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 names the trigger conditions (customer asks to see photos, gallery, plans, videos, documents, or layout/capacity/dimensions/crew/itinerary) and the alternative for pricing (use booking_detail for date-specific prices, extras, availability). It even gives a negative guideline: do not exclude a yacht or ask for length/beam absent an explicit customer requirement.

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?

Annotations declare destructiveHint=true and readOnlyHint=false, and the description adds real behavioral context beyond them: the action re-prices before submitting, selections are not auto-persisted from the preview tool, and submitted extras must be verified via saved_extras. It does not cover auth requirements, error modes, or how the saved_extras verification is surfaced, so it stops 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?

Front-loads the core purpose in the first sentence and keeps each following sentence on a distinct, useful point (repricing, preview contrast, extras repetition, client data, no-guessing rule). Minor waste: leftover markdown backticks and the embedded '**** strong rule' formatting are noisy, but content is dense rather than 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 15-parameter, 9-required mutation with no output schema, the description covers the highest-risk pieces (extras fidelity, client data, submission semantics) but leaves the arrival/departure, currency, and port-pay parameters unexplained. An agent would have to infer those from terse schema text alone.

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%, so the schema documents most parameters. The description adds meaningful semantics for selected_extras (must repeat every extra with exact id_opt and quantity, empty list only when nothing was selected) and for the client_* fields, but it says nothing about arrival_selected, departure_selected, currency_id_devise, arrival_port_pay_option, or departure_port_pay_option.

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 verb (submits) and resource (booking/option request) and explicitly contrasts this action with booking_detail_mod, which is called out as a stateless preview. An agent can distinguish this from siblings like booking_detail and booking_detail_mod without opening the schema.

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 explicit routing conditions: use this to actually submit, use booking_detail_mod only to preview. It also states prerequisites (full client details required) and the strong rule that the AI must not invent customer data but must ask the customer — a clear when/when-not instruction.

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?

Beyond the readOnlyHint annotation, it discloses output semantics (images here are supplemental; boat_details is canonical), a workflow constraint (use only booking_detail_mod's server-calculated totals after changes), and a pricing caveat (quote customer_cost_summary.full_customer_cost; deposits are returned separately and excluded). This is substantive context the annotations cannot carry.

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?

Purpose is front-loaded and every sentence carries routing, constraint, or output information. It is somewhat dense with branching instructions (media, extras, totals, final offers) that could be tightened, but nothing is pure 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?

With no output schema and a read-only annotation, the description compensates by naming the response fields an agent needs (customer_cost_summary.full_customer_cost, separate deposits) and by specifying the follow-up tools for mutation and booking. An agent has enough to call and interpret this tool correctly.

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 five parameters are already documented in the schema, including the DD/MM/YYYY formats. The description adds only the sourcing constraint for id_boat/id_tbf1 ('exactly as returned by search_boats'), which the schema phrasing partly mirrors, so the baseline of 3 holds.

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?

Opens with a specific verb and resource ('Return date-specific availability, pricing, extras and booking choices') and immediately distinguishes itself from the sibling boat_details for media. An agent can tell what this tool is for and what it is not for without opening the schema.

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?

Explicit routing: call boat_details instead when only photos/media are wanted, and call booking_detail_mod after the customer changes extras, passengers, currency, ports or payment options. It also states the prerequisite that id_boat and id_tbf1 must come verbatim from search_boats.

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?

Annotations already mark this readOnly/non-destructive, and the description is consistent with that ('stateless price preview and does not save the selection'). Beyond that it discloses real behavioral constraints: Sedna is the only source of truth for prices, never compute totals in the LLM, do not add payable_now to payable_at_base, and keep the refundable deposit separate. This is rich, non-obvious operational 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?

Reasonably sized and front-loaded with the core purpose and the price-authority rule. Every sentence carries an instruction the agent needs, though a couple of lines drift toward downstream output handling rather than the call itself. No filler or tautology.

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 an 11-parameter tool with no output schema, the description compensates well: it names the return fields to quote (customer_cost_summary.full_customer_cost, payable_now, payable_at_base, refundable deposit) and explains how to present them. Combined with workflow and price-authority guidance, an agent has what it needs to call and interpret this 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 coverage is 100%, so the baseline is 3, but the description adds cross-tool provenance (id_boat/id_tbf1 come from search_boats) and semantic handling of selected_extras (send the complete list, and repeat it in booking_create). It also frames currency, ports and payment options as inputs. This meaningfully exceeds what the schema text alone conveys.

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 verb+resource: applies customer selections and returns server-recalculated booking details, and clarifies it is a stateless price preview that does not persist. It implicitly separates itself from booking_create (the save step). It doesn't address why one would pick booking_detail_mod over the sibling booking_detail, so it stops short of full sibling differentiation.

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 clear workflow context: copy id_boat/id_tbf1 from search_boats, and if the customer proceeds, repeat the extras in booking_create. The when-not-to-use case (this preview does not save) is explicit. No guidance on choosing between booking_detail and booking_detail_mod, which are the closest siblings.

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?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: pricing comes from the same booking preview as booking_detail, the refundable deposit is always reported separately, and missing length/beam values are omitted rather than estimated.

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 parameter bullets are front-loaded and each sentence carries information; the second paragraph is dense but every claim (cost breakdown, deposit separation, cabin labels, missing-value handling) is substantive rather than 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?

With an output schema present, return values need not be fully described, yet the description still explains how customer_cost_summary partitions charter price, extras, full cost and deposit, and how cabin fields are labeled. Combined with the parameter and behavioral notes, an agent has everything needed to call it correctly.

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 0%, so the description must carry the parameter burden, and it does: it states the 2..4 boat_ids cardinality (absent from the schema's array definition), the pax meaning, the currency enum EUR/USD/CNY with default, and the YYYY-MM-DD format for start_date/end_date.

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 opening sentence names a specific verb ('Compare') and resource ('boats'), and constrains the scope to 2-4 boats using Sedna's date-specific customer pricing. It clearly differs from siblings like search_boats and boat_details, though it never names those alternatives 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 by the parameter list: use it when you have 2-4 boat ids and a pax count and want a dated price comparison. However, there is no explicit 'use this instead of X when Y' guidance and no stated prerequisites or exclusions relative to search_boats or boat_details.

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 adds useful context by framing this as a static, authoritative rule set that applies to all conversations. It does not contradict the readOnly/openWorld/destructive annotations. It could be slightly more explicit that invoking this tool returns the rules as its output, but the content makes that clear.

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 its purpose and then delivers a numbered, actionable list. Each rule earns its place and there is no filler or redundant wording. The length is justified because the description is itself the substantive content of the readme tool.

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 provides complete operational context: ordering requirements, ID integrity rules, date clarification, media handling, and the distinction between search, details, and booking tools. Nothing needed for an agent to use the tool correctly is missing, and no output schema is required for a static rule set.

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 tool has zero parameters and the schema already covers this fully with an empty object. Per the baseline for no-parameter tools, the description does not need to add parameter meaning; it is compatible and does not introduce any confusion.

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 exactly what the tool provides: the official Sedna rules for public yacht-search conversations. It distinguishes itself from the operational sibling tools because it is a rule set, not an action. It is specific and not a tautology of the tool name.

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 explicitly says the rules govern every public yacht-search conversation, and the numbered rules directly tell the agent when to use which sibling tool, e.g., 'Call Base_list before search_boats', 'call boat_details', and 'Use booking_detail only for date-specific availability'. This is strong when-to-use guidance with concrete alternatives.

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?

Annotations declare a safe read (readOnlyHint=true, destructiveHint=false), but the description goes well beyond them: results have passed planning/block and pricing checks, results intentionally omit images, the 30-result display policy, and the rule that missing length/beam must be omitted rather than zeroed, estimated, or used to exclude yachts. This is rich behavioral context the annotations do not carry.

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 purpose, then structured into distinct paragraphs for result-count policy, media routing, and missing-value handling. Every sentence carries a rule, though the length/beam paragraph is somewhat tangential to the actual parameter set and could be tighter.

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 and 13 parameters, the description compensates thoroughly by describing result behavior (30-result threshold, full-list vs. preference prompt, no arbitrary subsets, alternative suggestions), return-content limits (no images), and data-quality rules for missing fields. An agent has everything needed to call and interpret the 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 the schema already documents all 13 parameters (pax, price, boat_model, etc.) and the baseline is 3. The description adds only marginal param meaning, notably that 'base' must be an official Base_list name and that dates are the exact requested dates; length/beam it discusses are not even parameters here.

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 verb and resource ('Search Sedna for yachts available for the exact requested dates') with scope qualifiers (date-availability, passed planning/block and pricing checks). It is clearly distinguishable from siblings like Base_list, boat_details, and booking_detail, which it names directly.

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 prescribes prerequisites and alternatives: 'Call Base_list first and use an official base name,' route photo/media requests to boat_details with id_boat, and use booking_detail for date-specific prices, extras, and ports. It also gives concrete branching rules for >30, <=30, and zero results.

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