Trades With AI + SaaS Price Watch

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds what the comparison surfaces (price, category, trades, integrations) and the 2-12 item bound, which is meaningful context given there is no output schema.

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, zero waste, with the core scope and dimensions front-loaded and the invocation options following. Nothing redundant.

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?

Covers both parameters, the item bound, and the comparison content for a tool with no output schema. The one soft spot is that no parameter is marked required, so the description's 'pass slugs, or a comparison slug' is the only signal that at least one input is needed.

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 goes beyond it by showing the alternative invocation path and giving a concrete example format for the comparison slug ("ai-receptionist-pricing"). This clarifies how the two parameters relate when the schema only labels them individually.

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 (compare) and resource (trades tools), plus the scope (2 to 12) and the dimensions compared. The multi-tool scope implicitly separates it from the singular sibling get_trade_tool.

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?

Explains the two invocation modes (tool slugs or a prebuilt comparison slug) but never states when to prefer this over search_trade_tools or get_trade_tool, and gives no exclusions or prerequisites. Usage is implied by the parameter guidance rather than spelled out.

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 readOnly, idempotent, non-destructive, and closed-world behavior, so safety is covered. The description goes further by disclosing the payload semantics (quoted prices with source text, integrations, trades served, check date) and the freshness signal ('check date'), which is genuinely useful since there is no output schema. No contradiction with 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?

One sentence, front-loaded with the verb and scope, followed by the return contents; every clause earns its place and there is no filler or restatement of the title.

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 one required parameter, full annotations, and no output schema, the description carries the return-value burden and does so by enumerating the fields the agent will receive. It stops short of noting behavior for an unrecognized slug or the relationship to the sibling lookup tools, but nothing essential to calling it 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% and the single parameter's description already explains the slug format, gives examples, and notes 'a tool name also works'. The description adds no parameter-level meaning beyond that, so this sits at the baseline for fully documented schemas.

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?

Specific verb ('Get') plus resource ('one tool in the tradeswithai.com directory') and an enumeration of the returned fields, so the agent knows exactly what comes back. It implicitly separates itself from search_trade_tools and compare_trade_tools by the singular 'one tool', but it never names those siblings, so differentiation is inferred rather than stated.

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: fetching full details for a single tool follows naturally from a search result, and 'slug from search_trade_tools' hints at the workflow in the schema. There is no explicit when-to-use, when-not-to-use, or routing against compare_trade_tools / get_vendor_pricing.

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 readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely useful context beyond that: results come from a public pricing page, include the page quote, and carry a 'date checked' freshness marker — notable since there is no output schema to convey this.

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 tightly written sentence with the resource and scope front-loaded and zero filler. Every clause (public prices, per-plan, quote, date checked) contributes information.

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 read tool with no output schema, the description supplies the missing return-value context (plan prices, source quote, verification date), which is what an agent most needs here. It does not address failure behavior such as an unknown or unpriced vendor, a minor 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 description coverage is 100% and the single 'vendor' parameter is documented with examples ('hubspot.com' or 'Notion'). The description only restates that one vendor is accepted, adding nothing beyond the schema, so the baseline 3 applies.

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 ('Get the public plan prices for one SaaS vendor') and even specifies the granularity of the result (per-plan prices with page quote and check date). It implicitly separates itself from multi-vendor/sibling tools by scoping to 'one' vendor, but it never names an alternative tool, 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?

Usage is only implied: the 'one SaaS vendor' scoping suggests this is the single-vendor lookup rather than a broad search, which hints at when to use it versus search_saas_vendors or recent_price_changes. There is no explicit when-to-use, prerequisite, or exclusion statement.

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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful non-annotation context: the data comes from weekly diffing and includes added/removed entries with dates and source links. It says nothing about ordering, the effect of the limit cap, or empty-result behavior.

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 dense sentence that front-loads the verb and resource, then enumerates contents. Every clause carries information; no filler or repetition.

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 simple read-only list tool with no output schema, describing the return fields (added/removed prices, dates, source links) is a real contribution. It still leaves the limit and category parameters, plus result ordering, unexplained, which an agent would need to call it well.

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 only 33% (only 'since' is documented), so the description must compensate and largely doesn't. The phrase 'dates' hints at a date filter, but the limit parameter (default 20, max 50) and the category parameter are never explained in either the schema or the description.

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 (List) plus resource (SaaS price changes) and narrows scope to changes 'detected between weekly checks,' with the exact contents (prices added and removed). It implicitly separates itself from get_vendor_pricing and search_saas_vendors, but never names a sibling 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?

There is no when-to-use guidance, no prerequisites, and no mention of when to prefer this over get_vendor_pricing or search_saas_vendors. The 'recent price changes' framing implies a monitoring use case but nothing is stated outright.

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, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context by disclosing the return shape ('smallest monthly figure on each pricing page and the page URL'), which matters because there is no output schema. It still omits pagination behavior and result-count semantics.

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 tight sentences, with the scope and lookup modes front-loaded and the return shape following. 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 simple search tool with annotations covering safety and the description covering return semantics, an agent has enough to call it correctly. Remaining gaps are minor: combining query and category, pagination, and empty-result 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 67%, with query and category documented in-schema while limit is not. The description restates the name/category lookup modes and expands the category examples slightly ('design'), but adds no syntax or constraint detail, and the undocumented limit parameter (default 15, max 50) is not addressed. Baseline 3 for partial coverage.

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 300+ SaaS vendors... by name or category') and even names the data source (SaaS Price Watch), so the purpose is unambiguous. It does not, however, distinguish itself from pricing-oriented siblings such as get_vendor_pricing or recent_price_changes, leaving the agent to infer the boundary.

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 gather that name/keyword or category lookups are supported, but there is no explicit when-to-use, no exclusions, and no pointer to alternatives like get_vendor_pricing for a single vendor or recent_price_changes for deltas.

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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds useful provenance ('Data from tradeswithai.com, checked against each vendor site'), which tells the agent the results are curated rather than live scraped, but it does not cover result limits, pagination, or empty-result behavior.

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 tight sentences: the capability and covered trades are front-loaded, and the data-provenance sentence follows. No filler, though the long parenthetical trade list is the densest part and could be trimmed.

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 5-parameter, zero-required search tool with no output schema, the description covers what it returns conceptually but says nothing about result shape, the limit default/maximum, or how price filtering handles tools without listed pricing. Adequate but with clear gaps for an agent trying 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 80%, so the schema already documents task, trade, category, and max_monthly_price richly, including an example of the price-filter semantics. The description only restates the same four filter names and adds no syntax, format, or matching behavior beyond the schema (e.g., whether trade matching is fuzzy), so the baseline 3 applies.

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 ('Find') and resource ('AI and software tools') plus the domain (small trades businesses) and enumerates the covered trades, so the purpose is unambiguous. It does not, however, explicitly contrast itself with siblings like search_saas_vendors or compare_trade_tools, which is the only missing element for 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?

It lists the filter dimensions ('Filter by trade, task, category, and max monthly price'), which implies how to narrow results, but gives no explicit when-to-use guidance or naming of alternatives. The only routing hint ('Check full quotes with get_trade_tool') lives in the schema, not the description.

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