OpenComment AI

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so this is unambiguously a safe local read. The description adds nothing beyond that safety profile — no indication of return format, whether it is static documentation or dynamic state, or how it relates to the other reference tools.

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 front-loaded sentence with no wasted words. Slightly generic in 'product workflow', but structurally 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 parameterless read tool with annotations and no output schema, the description is minimally adequate. It does not, however, say what the agent gets back or why this differs from the other overview/reference siblings, which is the main remaining 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. No parameter-related gaps exist.

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 names a specific scope (sign up, connect an agent, begin the product workflow), so an agent can tell this is an onboarding/quickstart resource rather than a search or reference tool. However, it offers no explicit differentiation from siblings like product_overview or pricing_reference, which could also plausibly cover 'getting started' material.

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 statement of when to call this versus product_overview, pricing_reference, or product_search, and no prerequisites or exclusions. Usage is only weakly implied by the 'sign up / connect an agent' phrasing.

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 cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint=false). The description adds one genuine behavioral fact beyond them: pricing data is not cached, so results must be fetched live. It does not clarify whether the tool returns a URL, a rendered page, or structured plans/credits data.

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 short sentences with no waste; the core purpose leads and the freshness caveat follows immediately. Every sentence 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?

For a parameterless, read-only lookup with no output schema, the description covers purpose and the live-data caveat adequately. The one remaining ambiguity is what the 'canonical page' actually returns, which is a minor gap for a task this simple.

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 takes zero parameters, so by the baseline rule parameter semantics default to 4. There is nothing in the schema for the description to compensate for.

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 ('Get the canonical page for current plans and credits'), which is clearly distinct from product_search or product_overview. It does not name a sibling or explicitly draw the boundary, so it stays at a strong 4 rather than 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?

'Prices are not cached in MCP' implies the agent must call this for pricing rather than relying on prior context, which is a useful implicit usage cue. However there is no explicit when-to-use vs when-not, and no comparison to the sibling tools, so the guidance remains implied.

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 structurally. The description adds only 'canonical product sources', which is too vague to convey whether the response is static, cached, or curated — nothing beyond the annotations in practice.

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 short sentence, front-loaded with the tool's purpose and no filler. It is appropriately sized for a no-parameter read tool, though its brevity comes partly from under-specification rather than economy.

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, non-destructive read tool with no parameters and annotation-covered safety, an output schema is not required and the description is technically adequate. However, it leaves the agent unable to tell what this returns or how it differs from get_started, which is a real gap in a crowded sibling 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 takes zero parameters and schema coverage is 100%, so there is nothing for the description to disambiguate. Per the zero-parameter baseline, a 4 is appropriate despite the description offering no parameter 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 restates the title 'About OpenComment AI' as 'Learn what OpenComment AI does' — a near-tautology with no distinct verb+resource framing beyond the tool's own name. It also fails to distinguish this tool from the close sibling get_started, which an agent would plausibly confuse it with.

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 statement of when to use this versus get_started, product_search, or pricing_reference. The phrase 'canonical product sources' hints at content provenance but does not tell the agent which query or intent should route here.

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. The description adds useful scope by saying results are 'curated public' facts and page summaries, which aligns with the closed-world annotation, but it does not cover result format, pagination, or 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?

The description is a single front-loaded sentence with no wasted words. It clearly presents the core action and resource immediately.

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 one-parameter search tool with safety annotations and no output schema, the description is minimally adequate. However, it omits query semantics and sibling-tool differentiation, leaving gaps an agent may need 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%, and the single required query parameter has no description in the schema. The tool description implies a search query but does not explain syntax, expected input, or constraints beyond what the name 'query' already suggests.

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 and resource: search OpenComment AI product facts and page summaries. It is clear what the tool does, but it does not explicitly distinguish itself from sibling tools like product_overview or pricing_reference.

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 guidance on when to use this search tool versus alternatives such as product_overview or pricing_reference. Usage is only implied by the word 'Search,' with no conditions or exclusions.

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