Finally Offline

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

Annotations already establish read-only, non-destructive behavior. The description adds the important behavioral precondition that a registered, subscribed integration is required and that the agent must present the same agent_token, which is beyond what the annotations say.

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-loads the purpose and then gives the required call order with 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?

Given rich parameter descriptions and safety annotations, the only real gap is the absence of an output schema or explicit statement of how the HTML digest is returned/delivered. The core prerequisites and auth flow are covered.

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 schema already documents since, category, agent_name, and agent_token, including the 'Never put it in URLs' rule. The description only reinforces using the same token and does not add new parameter-level meaning.

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 verb and deliverable ('Generate a branded HTML digest') plus a scope ('your subscribed integration'), which distinguishes it from sibling tools like search_articles, get_culture_news, and subscribe.

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 states the prerequisite sequence: 'Call register_agent, then subscribe with its agent_token; use that same token here.' It does not spell out when to prefer this over the other content tools, so it stops short of a full when/when-not guide.

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 and destructiveHint=false, so the safety profile is covered. The description adds no extra behavioral context such as authentication requirements, rate limits, sorting behavior, or return format. It only restates scope already visible in the parameter schema, providing minimal value beyond the 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?

The description is two short sentences, with the core action and resource front-loaded. The second sentence listing categories is mildly redundant with the schema, but it is concise and not verbose. It earns its place by giving quick orientation.

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 fully documented parameters and no required fields, the description is nearly sufficient. The annotations cover safety and the schema covers invocation details. The lack of output-schema information is not a major gap here, though explicit mention of what is returned (e.g., a list of article summaries) 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 description coverage is 100%, so the baseline is 3. Every parameter (limit, since, category, agent_token) is already documented in the schema. The description's mention of categories adds no new semantic meaning beyond the schema's enum values.

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 fetches 'the latest human culture news' from 'Finally Offline', naming a specific verb and resource. It lists covered categories (sports, music, fashion, culture), which implicitly separates it from siblings like get_trending_topics and search_articles, though it does not explicitly name 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?

Usage context is implied: an agent would use this tool when it wants recent culture news. However, there is no explicit guidance on when not to use it or which sibling tool (e.g., search_articles for targeted queries, get_trending_topics for trends) would be more appropriate. This is acceptable but leaves the choice to inference.

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 and destructiveHint false, so the safety profile is covered. The description adds some context about what the tool returns, but it does not reveal behavioral details such as update latency, output volume, or how 'trending' is determined. It does not contradict the 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?

Two sentences with the core purpose front-loaded and the rest describing what is returned and who should use it. The phrase 'cultural pulse data' is somewhat vague, but the description is compact and has no significant waste.

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 zero required parameters and annotations covering safety, the tool is easy to invoke correctly. The description names three return components, which is helpful since there is no output schema. It could be stronger by defining what 'cultural pulse data' means or clarifying categories, but it is sufficient for an agent to understand the general result.

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 schema provides rich meaning for both parameters: timeframe has an enum and default, and agent_token includes credential source and usage warnings. The description adds no parameter-level detail, but with full schema coverage this is acceptable.

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 action ('Get what's trending right now in human culture') and enumerates return contents: topic frequency analysis, top headlines per category, and cultural pulse data. This is clear, but it does not explicitly distinguish itself from sibling tools like get_culture_news.

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 phrase 'Perfect for agents that need to stay current' gives a general use case, but it does not explain when to choose this tool over get_culture_news or generate_digest, nor does it mention exclusions. Usage context is implied rather than 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?

Given annotations only report readOnlyHint=false and destructiveHint=false, the description adds meaningful behavior: the token is one-time, must be saved securely, and the profile is self-reported rather than a verified person. This goes beyond the minimal annotation coverage.

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?

Four sentences, each with essential information: purpose, return values, security warning, identity caveat, and usage boundary. No redundant phrasing; critical details are front-loaded.

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 covers purpose, return values, security implications, and when registration is unnecessary. With 100% schema coverage and no output schema, this is mostly complete. Minor gaps (e.g., error conditions, token recovery) prevent a 5.

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 description reinforces that the operator profile is self-reported, but that information is already present in the schema (e.g., contact_email says 'self-reported'). No additional parameter semantics are provided.

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 uses the specific verb 'Register' with a clear resource ('an integration with a self-reported operator profile'). It also distinguishes itself from siblings by noting that public reading needs no registration and by describing unique return values (agent_id, agent_token).

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 clearly conveys when to use the tool (to register an integration) and states a when-not ('Public reading needs no registration'). However, it does not explicitly name an alternative sibling tool, so it falls just short of a 5.

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 annotations are minimal (all false), so the description carries the burden of behavioral disclosure. It does this well by stating the report is unverified and that the action does not verify a citation or confer featured status. This prevents an agent from over-trusting the side effect, even if it does not cover duplicate-report or overwrite 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?

The description is two sentences with no filler: the core action is front-loaded, and the critical limitation is stated immediately after. 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?

For a straightforward record action with four documented parameters and no output schema, the description is largely complete: it covers purpose, auth attribution, and behavioral limitations. The only minor gap is that it does not describe the response or success indication, but that is not essential for a simple logging call.

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 article_url, agent_id, platform, and agent_token. The description adds useful framing around the 'unverified self-report' and authenticated attribution, but it does not provide any parameter-specific detail beyond what the schema already gives.

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 uses a specific verb ('Record') and names the exact resource: an unverified self-report of sharing a Finally Offline article, attributed to the authenticated integration. It also explicitly states what the tool does not do—verify a citation or confer featured status—which cleanly distinguishes it from any verification or publication tool among the siblings.

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 gives clear context for when to use the tool: recording an unverified self-report of sharing, attributed to the authenticated integration. It also provides a 'when not' signal by saying the action does not verify or confer featured status, though it does not name alternative sibling tools. Since no sibling appears to offer this action, that omission is acceptable.

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 annotations already establish that this is a read-only, non-destructive operation. The description adds no behavioral details beyond that, such as result format, pagination, or authentication behavior. It does not contradict the annotations, so a baseline 3 is appropriate.

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 no filler. The scope is front-loaded and the examples in the second sentence add useful context without redundancy.

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 search tool with well-documented parameters and safety annotations, the description is largely complete. It could mention result format or ordering, but an agent can confidently select and invoke the tool based on what is provided.

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 parameters are already fully documented. The description reinforces the 'query' use case with examples but adds no additional parameter semantics beyond what the 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 opens with a specific verb and resource: 'Full-text search across all Finally Offline articles.' It also lists concrete search intents (topics, people, events, trends), making the tool's purpose unmistakable and clearly distinct from the trending/news sibling 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?

It provides clear usage context: use this when you need to find specific content anywhere in the archive. It does not explicitly name alternatives or state when not to use the tool, but the intended scenario is clearly communicated.

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 indicate the tool is not read-only and not destructive, so the description carries the burden of explaining what it actually does. It explains enabling/disabling a digest subscription, and it adds non-obvious operational constraints: registration must already exist and webhook delivery is unavailable.

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 deliver the action, the precondition, and the key caveat without filler. The structure is front-loaded with the purpose and then gives the most important usage warning.

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 schema fully documents each parameter Ia, and the description adds the registration prerequisite and webhook unavailability, which are essential and not inferable from the schema. A mention of the return value would be nice, but the tool is simple enough that this is not a blocking 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 schema already describes all six parameters, so the description does not need to add much parameter-level detail. The 'omit webhook_url' note is useful but largely duplicates the schema's own description of the webhook_url field.

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 precise action and resource: enable or disable digest access for an authenticated integration. It also distinguishes itself from registration by saying 'Register first,' and it clarifies that this is not webhook delivery by instructing to omit webhook_url.

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?

'Register first' establishes an explicit precondition, and 'Automatic webhook delivery is not enabled; omit webhook_url' gives a clear when-not instruction. It does not name sibling alternatives like generate_digest, but the registration prerequisite and webhook caveat are enough to guide appropriate use.

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