LoopingAgent

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly states that the tool only retrieves a booking link and that actual slot selection happens externally on Cal.com, preventing the agent from promising booking functionality. It doesn't mention return format or edge cases, but the key behavioral boundary is well communicated.

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 focused sentences with no filler. The core purpose is front-loaded and the important behavioral caveat about external slot selection is included without unnecessary detail.

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 is simple: one optional parameter, no output schema, no annotations. The description tells the agent what to do with the result (present the link) and what not to do (select the slot). This is sufficient for a correct invocation.

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 topic parameter is already documented as optional. The description adds value by clarifying that topic is only a hint and cannot be used to select the slot, which goes beyond the schema's basic explanation.

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 the specific verb and resource: getting a booking link to schedule a free 30-minute call with Laurent Knauss via Cal.com. The description also clearly differentiates this from the sibling content-retrieval tools (get_article, get_profile, etc.) by making the booking purpose explicit.

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?

Clearly implies use when a user wants to schedule a call with Laurent Knauss, and clarifies the agent's role is to present the link rather than handle booking. It doesn't explicitly list alternatives or exclusions, but sibling names are obviously unrelated, so the intended use case is clear enough.

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 burden of behavioral disclosure. It explains that this is a metadata-only operation (not full content) and that full content is server-rendered at the returned URL. This adds meaningful behavior beyond the name and 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?

Three sentences, each earning its place: what the tool returns, where to find the slug, and what to do for full content. The most important information is 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?

For a single-parameter metadata retrieval tool, the description covers the return fields, the key input source, and the full-content route. It doesn't describe error behavior or response structure, but no output schema exists and the operation is simple enough that these omissions are not critical.

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 fully documents the single 'slug' parameter with examples and 100% coverage. The description adds a useful hint that the slug can be found via list_articles, but this is modest additional context rather than substantial semantic enrichment.

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 ('Get') and resource ('metadata for a single article on loopingagent.com'), then enumerates exactly what is returned: title, category, excerpt, cover image, and canonical URL. It clearly distinguishes itself from list_articles by focusing on a single article rather than a listing.

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 explicitly tells the agent how to obtain the required 'slug' parameter by referencing list_articles, and it clarifies that full content is available via the returned URL. It doesn't explicitly state alternatives or exclusions, but for a simple retrieval tool the guidance is adequate.

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 disclosure burden. It clearly communicates that this is a read-only profile retrieval and lists the specific information returned, implying no side effects or destructive behavior. It does not detail authentication or data freshness, but the absence of parameters and the informational nature keep the gap small.

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 focused sentences with no filler. The main identity of the tool is front-loaded, the content list is compact, and the usage guidance is delivered in a single clear directive.

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, zero-parameter profile-fetch tool, the description is complete: it names the subject, lists the returned fields, and tells the agent when to use it. No output schema or nested structures exist, and the description sufficiently covers what an agent needs to select and invoke 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?

The input schema is empty (0 parameters), so the baseline is 4. The description adds meaningful contextual information about what the profile contains, even though there are no parameters to document. It does not need to compensate for schema gaps because there are none.

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 begins with 'Full professional profile of Laurent Knauss' and enumerates the contained data (title, location, availability, contact, socials, certifications, booking link), making the tool's function unambiguous. It clearly distinguishes from sibling tools like book_call, get_skill, and list_articles, which target different resources.

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 instruction 'Use this first to understand who he is and how to reach him' provides explicit context for when to call this tool and positions it as an initial step. It does not explicitly mention alternatives or exclusions, but for a zero-parameter profile lookup the guidance is sufficient.

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 the burden of behavioral disclosure. It mentions the structure (grouped by domain, each skill has label and detail), which is useful, but does not explicitly state that this is a read-only operation, nor any limitations like recency or completeness.

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 zero waste. The first sentence states the resource and structure; the second gives the intended use case. Every phrase adds value, including the domain list which helps an agent understand the data's scope.

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 0-parameter read-only tool, the description adequately covers what the tool returns and why it might be used. It does not provide an exhaustive output schema, but the label/detail/grouping description is sufficient for the low complexity. A minor gap is not explaining how the 'fit' assessment should be performed, but that is arguably outside the tool's scope.

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 has zero parameters, so there is no parameter behavior to explain. The description appropriately details what the returned data contains, satisfying the baseline of 4 for a no-parameter tool.

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 identifies the resource as Laurent Knauss' technical skills, grouped by domain, and lists the specific domains. It does not explicitly differentiate from siblings like get_profile, but the focus on skills and role-fit is distinct enough.

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 context for when to use the tool: 'assess fit for AI/agentic development roles.' There is no explicit exclusion or mention of alternatives, but the stated use case is specific and actionable.

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 the behavioral burden. It clearly indicates a read-only listing operation ('List') and discloses the exact return shape (slug, title, category, excerpt), plus the category filtering behavior. It does not mention pagination or ordering, but neither is critical for a simple blog-list tool.

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?

Three short sentences with no filler: purpose is front-loaded, return fields follow, and the filter option is last. Every sentence adds useful 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 single-optional-parameter list tool with no output schema, the description supplies everything needed to call it correctly: what it lists, what it returns, and how to filter. No other context is essential.

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 input schema already fully documents the category parameter with enum values and a filter description (100% coverage). The description adds only optionality and repeats the enum values, which is useful but not a significant semantic addition over 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 names a specific verb ('List'), a specific resource ('all articles on loopingagent.com'), and the returned fields. It clearly distinguishes from siblings like get_article by framing this as the plural list operation.

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 makes the usage context explicit: call this when you need all articles, optionally filtered by category. It does not explicitly contrast with get_article for full single-article retrieval, so it stops short of the top score.

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