ComparEdge Pricing

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

With no annotations, the description must disclose behavioral traits. It explains that the tool is a calculation (safe/read-only) and mentions 'hidden-cost line items' as part of the output. However, it doesn't state idempotency, side effects, or authorization requirements, leaving some ambiguity.

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 with no filler. The first sentence delivers the purpose, the second lists parameters. Every word contributes to understanding, making it efficient for agent parsing.

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 4 parameters, the description adequately explains what the tool computes (subscription + hidden costs) but lacks details on return structure, edge cases, or how optional parameters affect results. It is sufficient for a straightforward calculator but not fully comprehensive.

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 baseline is 3. The description lists parameter names and the billing enum, but adds minimal new meaning beyond what the schema already provides (e.g., 'slug' is a product identifier). The tie to 'seat-aware' and 'annual-aware' provides limited added semantic context.

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, including subscription and hidden cost lines. It uses specific terms like 'seat-aware' and 'annual-aware' to distinguish from sibling tools like get_pricing or get_hidden_costs.

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 provide any guidance on when to use this tool versus its siblings (e.g., get_pricing, get_hidden_costs). It merely lists parameters, leaving the agent to infer usage context without explicit when-to-use or when-to-avoid instructions.

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, and the description does not disclose behavioral traits such as idempotency, rate limits, or authentication requirements. It only describes output structure, lacking context on side effects or data freshness.

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, well-structured sentence that front-loads core functionality (side-by-side comparison) and specifies output details efficiently. 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 provides a reasonable overview of return structure (full record + compact matrix with key fields). However, it omits details about error handling or edge cases, which slightly reduces 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% for the only parameter 'slugs', and the description adds context about the output but not additional parameter semantics. 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 performs a side-by-side comparison of 2-4 products, specifying output includes a full record and a compact matrix. This distinguishes it from sibling tools like get_pricing or calculate_tco.

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 valid input range (2-4 products) but does not specify when to use this tool over alternatives like discover_software or get_positioning. No explicit exclusions 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?

With no annotations, the description carries full burden. It mentions returns 'compact cards' but lacks details on side effects, data freshness, or auth requirements. The behavioral profile is insufficient for an agent to understand implications.

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-loaded with criteria, and contains no filler. Every phrase 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?

With 5 optional parameters, no output schema, and no annotations, the description is minimally adequate. It explains the tool's purpose and return type but does not cover behavior when no parameters are provided, combination logic, 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?

Schema coverage is 100%, so each parameter already has a description in the schema. The description repeats some parameter names but adds no new meaning or usage context beyond what's in the schema.

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 verb 'Find' and the resource 'software', listing specific criteria (category, max price, free-tier, keyword). It distinguishes from sibling tools like calculate_tco or compare_software, which focus on different aspects.

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 provided on when to use this tool versus alternatives like get_pricing or compare_software. The description does not mention excluded scenarios 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?

With no annotations provided, the description carries the full burden. It discloses the tool returns rate card data and estimates, but does not specify whether rates are dynamic, caching behavior, or data freshness. Adequate but not detailed.

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 conveys purpose and inputs. No filler, front-loaded with key information. Every word serves a purpose.

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 4 parameters, no output schema, and no annotations, the description is reasonably complete. It explains what the tool does and how parameters relate. Missing details on return format or behavior without token volumes, but overall 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 coverage is 100%, baseline 3. The description adds context by explaining the rate card structure and how token volumes (inputTokens, outputTokens) are used for estimation, enhancing understanding beyond property names and types.

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 cost estimates, with specific verb 'estimate' and resource 'llm cost'. It implies differentiation from siblings like get_pricing by focusing on token-based pricing, but does not explicitly contrast with alternatives.

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 needing token rates or cost estimates for a given volume, but lacks explicit guidance on when to use this tool versus siblings like calculate_tco or get_pricing. No when-not or alternatives 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?

No annotations are provided, so the description carries the full burden. It details the content of the brief but does not disclose behavioral traits such as read-only nature, authentication requirements, or side effects. The description is informative about output but lacks 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?

The description is front-loaded with 'Negotiation-ready' and efficiently lists key contents, but it is a bit lengthy with two long sentences. It earns its place with specific details, though minor trimming could improve conciseness.

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, the description comprehensively lists all return components: renewal costs, transparency score, discount programs, negotiation tactics, fixed vs negotiable items, and a link. This fully explains what the agent will receive, making it complete for its purpose.

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 only parameter 'slug' has a schema description with examples. Since schema coverage is 100%, baseline is 3. The description adds no extra meaning beyond the schema, as the examples are already provided in the schema.

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 provides a 'Negotiation-ready true-cost brief for one product' and enumerates specific outputs such as renewal costs, cost-transparency score, discount programs, negotiation tactics, and a link to an email generator. This distinguishes it from sibling tools like 'get_pricing' or 'get_hidden_costs'.

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 needing a negotiation-ready cost brief for a single product, but it does not explicitly state when not to use or contrast with siblings. No alternative tools 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?

No annotations provided, so description carries full burden. Describes return data (cost types, intro context, category positioning) but does not state read-only nature, side effects, or requirements. Adequate but not thorough.

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, front-loaded with key information. No redundant phrasing; every word adds value.

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?

Single parameter, no output schema. Description covers return content well (hidden cost categories, intro context, positioning). Lacks explicit return structure but sufficient 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 coverage is 100% with parameter 'slug' described as 'Product slug.' Description adds context that it's for one product but no additional format or constraints. 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 returns 'costs beyond the sticker price' for a single product, listing specific cost types (implementation, add-ons, etc.) and context. It distinguishes from siblings by emphasizing this is data 'most pricing answers miss'.

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 usage for deep cost analysis per product but does not explicitly state when to choose this over compare_software, calculate_tco, or get_pricing. No exclusions or alternatives 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 bears full burden. It lists returned fields but does not disclose read-only status, authentication needs, rate limits, or other behavioral traits beyond output.

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 with clear outcome. Minor redundancy ('most citable one-line stat') but overall 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?

For a simple read-only tool with one parameter and no output schema, the description adequately explains what is returned. Missing definition of 'category' but likely domain-known.

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 parameter (slug). The description adds no further meaning beyond 'Product slug.' Baseline 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 returns price positioning relative to category median, min, max, and sample size. It identifies the specific resource (price position) and distinguishes from siblings like get_pricing and get_price_history by focusing on competitive positioning.

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 quick 'one-line stat' but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though sibling names provide hints.

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 disclose behavior. It lists the output components (signal, snapshot, change, trend) but omits details like data recency, computation method, or side effects. Adequate but not thorough.

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 that efficiently conveys the tool's output. Front-loaded with key terms, no excess 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's simplicity (one param, no output schema), the description adequately covers what the tool returns. Could mention necessary permissions or whether data is real-time, but current version is functional.

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 covers the single parameter 'slug' with description 'Product slug.' The tool description adds no additional context, but schema coverage is 100%, so 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?

Description clearly states the tool provides 'Price-stability signal, latest verified snapshot, last observed change and derived trend for one product,' distinguishing it from siblings like get_pricing which likely give current price. However, it could be more explicit about the action (get/retrieve).

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 versus sibling tools like get_pricing or get_hidden_costs. The description only says 'for one product,' implying per-product use, but no direct comparison or exclusion criteria.

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 lists the content of the response but does not disclose behavioral traits like whether it is read-only, authentication requirements, rate limits, or caching behavior. The description is adequate but not comprehensive.

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 front-loads the main purpose and then lists the components. While it is not overly verbose, the list could be better structured (e.g., bullet points) to improve readability. It earns its place but could be more 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?

Given no output schema and no annotations, the description provides a list of returned fields but lacks details on data structure or types. For a complex tool with many return items, additional structure would improve completeness. However, it covers the key elements.

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 description adds minimal extra meaning beyond the schema. It mentions 'product slug' which matches the schema, but does not provide additional context or clarifications. 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 provides a comprehensive pricing record for a single product, listing specific components like tiers, price range, discounts, hidden costs, and more. It distinguishes itself from siblings like get_hidden_costs and compare_software by focusing on a full record for one product.

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 retrieving a full pricing record for one product but offers no explicit guidance on when to use this tool versus alternatives such as get_hidden_costs or compare_software. No when-not-to or exclusion criteria are provided.

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