ComparEdge Pricing

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

No annotations are provided, so the description carries the full burden. It describes what the tool returns (TCO with hidden costs) but does not state whether it is read-only or has side effects. On the positive side, it does not contradict any annotations since none exist, but more transparency would be beneficial.

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, but the second sentence redundantly lists parameters already detailed in the input schema. While not overly long, it could be more concise by omitting the param list and focusing on tool behavior.

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 and no output schema, the description explains the input semantics well but gives no indication of the output structure (e.g., numeric value, breakdown). It is adequate for basic use but not fully complete for an agent to understand what the tool returns.

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. The description merely lists the parameter names and for 'billing' repeats the enum values from the schema. It adds no new meaning beyond what the schema provides (e.g., defaults for tier are already in schema 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 clearly states the tool computes 'Total cost of ownership for a team' with seat-aware and annual-aware subscription plus hidden costs. This distinguishes it from sibling tools like get_pricing or get_hidden_costs, which handle only part of the calculation.

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 usage when a combined TCO (subscription + hidden costs) is needed, but it does not explicitly state when to prefer this tool over siblings or provide when-not scenarios. The guidance is implicit, not explicit.

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. It describes the output structure (full record and compact matrix) but does not disclose any behavioral traits such as whether it is read-only, required authentication, error handling for invalid slugs, or rate limits. The description is basic but does not contradict any annotations (since none exist).

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 a single, front-loaded sentence that efficiently conveys the tool's purpose and output structure. It is concise without being under-specified, though a few more details could enhance clarity without significant bloat.

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 and the tool has moderate complexity (comparison of multiple products), the description provides a reasonable overview but leaves some gaps. It does not explain what constitutes a 'full record' beyond the matrix fields, nor how results are ordered or if there are constraints on product types.

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 schema coverage for the only parameter (slugs) is 100%, and the description in the schema already explains it accepts 2-4 product slugs with examples. The tool description adds no additional meaning beyond this, so the baseline score of 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?

The description clearly states the tool performs a structured side-by-side comparison of 2-4 products, producing a full record and compact matrix with specific fields like starting price, free tier, etc. This distinguishes it from sibling tools like calculate_tco (which focuses on cost) or get_pricing (which returns single product pricing).

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 the tool is for comparing 2-4 products side-by-side, but does not provide explicit guidelines on when to use this tool versus alternatives, such as when a single product pricing query is sufficient. No when-not-to-use or exclusions are mentioned.

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 states the tool returns 'compact cards with source link' but omits details like pagination behavior, response size limits, or whether results are sorted. The schema's limit parameter (default 50, cap 200) is not mentioned in the description, leaving some behavior implicit.

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 concise sentences. The first clearly lists the search criteria, the second states the return format. Every word adds value; no redundant or irrelevant information. Highly efficient.

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 tool has 5 optional parameters and no output schema. The description only vaguely mentions 'compact cards' without specifying the fields in each card (e.g., name, description, price). For an agent to decide if the results suffice, more detail on the response structure 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 description coverage is 100%, so all parameters are documented in the schema. The description reiterates the criteria (category, maxPrice, hasFreeTier, keyword) but adds no new meaning beyond what the schema already provides. Baseline score of 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?

The description clearly states the tool's purpose: 'Find software by criteria' listing specific filters (category, max price, free-tier, keyword) and the output format ('compact cards with source link'). This distinguishes it from sibling tools like compare_software or get_pricing, which focus on comparison or pricing details.

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 usage for discovery tasks by listing criteria but does not explicitly tell the agent when to use this tool versus alternatives like calculate_tco or get_cost_guide. No exclusions or when-not-to-use guidance is provided.

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 must disclose behavior fully. It explains the tool returns rate card data and optionally an estimate, implying it is a read-only query. No destructive behavior is suggested, and the purpose is 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 a single sentence that captures the core functionality without any extraneous words. It is front-loaded with the primary action ('Per-model token rate card') and clearly separates the two modes (with and without token volume).

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?

While the description covers the basic purpose, it lacks details about the output structure (e.g., what fields are returned in the rate card) and does not mention any side effects or prerequisites. For a tool with no output schema, this is a minimum viable description but leaves uncertainty for an AI agent.

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 context by explaining the return type (rate card and estimate) and the optional nature of token inputs for cost estimation. This goes beyond the schema descriptions which only name the 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 the tool provides per-model token rate cards and optionally computes cost estimates. This distinguishes it from sibling tools like get_pricing (which may cover broader pricing) and calculate_tco (which likely deals with total cost of ownership).

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 guidance is given on when to use this tool versus alternatives like calculate_tco or get_pricing. The description only states what it does, not when it's appropriate or when to avoid it.

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 must fully disclose behavior. It does so by listing the exact contents of the brief, suggesting a read-only operation. No side effects or destructive actions are implied. However, it does not mention rate limits, authentication needs, or what happens on invalid input, keeping it from 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?

The description is a single sentence that efficiently conveys the tool's purpose and contents. It is front-loaded with key terms ('Negotiation-ready true-cost brief'). Each listed item is relevant, and there is no fluff. Could be split into shorter sentences for clarity, but remains concise.

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 tool with one parameter and no output schema, the description adequately covers what the tool returns. It specifies the brief's components, which is sufficient for an agent to understand the output. However, it lacks information on error handling or edge cases, leaving slight room for improvement.

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 description need not add much. The parameter 'slug' is described in the schema with examples. The description adds context ('for one product') but does not deepen understanding of the parameter beyond the schema. 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?

Clearly states the tool returns a 'negotiation-ready true-cost brief for one product' and enumerates specific contents (real renewal-rate costs, vendor transparency score, discount programs, negotiation tactics, negotiable vs fixed, and a link). The verb 'get' and resource 'cost guide' are specific, and the description distinguishes it from siblings like get_hidden_costs or get_pricing by focusing on negotiation readiness.

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 indicates usage for a single product ('for one product') but does not explicitly state when not to use or suggest alternatives. No guidance on prerequisites or when to prefer this over sibling tools like calculate_tco or get_pricing. Implied usage is clear, but explicit exclusions are absent.

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 lists specific hidden cost categories (implementation, add-ons, overage, support) and mentions 'intro context and category positioning,' giving the agent a clear picture of the output scope.

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 is informative, second is slightly promotional but adds a usage hint. No wasted words overall, though the second sentence could be more direct.

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 tool with one parameter and no output schema, the description covers purpose, scope, and output contents (hidden costs + context). Some missing details like return format, but adequate.

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% for the sole parameter 'slug.' The description adds no new semantic information beyond the schema's 'Product slug.' 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?

The description clearly states the tool retrieves 'costs beyond the sticker price' for one product, distinguishing it from sibling tools like get_pricing or compare_software. The verb 'get' matches 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?

The description implies use for uncovering hidden costs but does not explicitly state when not to use it or provide alternatives. The phrase 'for one product' hints at single-product scope, but no direct comparison to 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?

No annotations provided; description discloses output components but not behavioral aspects like error handling, data freshness, or whether it's read-only.

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?

Single sentence front-loads key purpose; no wasted words, though structure could be improved with lists for clarity.

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 or annotations, description explains return values (median, min, max, sample size) and context; lacks edge-case handling but adequate for a simple 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 has 100% coverage for the single slug parameter with basic description; the tool description adds context about output but not parameter semantics beyond what schema provides.

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 price positioning statistics (starting price vs category median, min, max, sample size) for a product, distinguishing it from siblings like get_pricing or get_price_history.

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?

Implies use when needing price positioning compared to category, but no explicit guidance on when to use over alternatives like get_pricing or calculate_tco.

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. It lists the data returned (stability signal, snapshot, change, trend), which is adequate for a read-only query. However, it does not disclose whether it requires any special permissions or if there are rate limits.

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 concise sentence of 14 words that front-loads the key output ('Price-stability signal'). No wasted words, though it could be slightly more structured.

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 only 1 parameter and no output schema, the description adequately lists the types of data returned (stability signal, snapshot, change, trend). It is sufficient for an agent to understand the tool's output.

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% (the only parameter 'slug' is described in schema). The description does not add meaning beyond the schema's 'Product slug.' 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?

The description explicitly states what the tool retrieves: price-stability signal, latest verified snapshot, last observed change, and derived trend for a single product. The purpose is distinct from sibling tools like get_pricing or get_cost_guide.

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 guidance on when to use this tool versus alternatives. It only mentions it is for one product, but does not specify when to prefer it over get_pricing or other pricing tools.

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 implies a read operation but does not disclose authentication needs, rate limits, error behavior, or whether the data is cached or real-time. Lacks behavioral details beyond what it returns.

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?

Single sentence efficiently lists key data points. Well-structured and front-loaded with core purpose. 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?

Description covers output contents adequately but does not mention error handling, pagination, or how to interpret results. Given no output schema, more detail on what the verdict or plan advice entails would improve completeness.

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 description adds no new parameter meaning. The description does not elaborate on slug, depth, or fields beyond schema descriptions. 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 clearly states 'pricing record for one product' and lists contents, making purpose obvious. It distinguishes from siblings like get_price_history or get_hidden_costs by being comprehensive, but could be more explicit about uniqueness.

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 guidance on when to use this tool vs alternatives such as get_hidden_costs or get_price_history. The description does not provide when-to-use or when-not-to-use context.

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