Pavels Web Solutions

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

With no annotations, the description carries the full behavioral burden. It does disclose one important trait - that this is a read/explain tool with no submission capability - but says nothing about permissions, rate limits, or what the response actually contains.

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?

Only two sentences, so it is short, but the first is phrased as an imperative to the agent ('Explain how...') rather than as a description of what the tool returns, which is awkward framing for a tool definition and pushes the actual return semantics into the background.

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 zero-parameter tool with no output schema, an agent still needs to know what comes back (contact form URL, email, phone number). The description gestures at that but never states it, so the definition is only marginally 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?

The tool takes zero parameters, so according to the rubric the baseline is 4. There is no parameter semantics to clarify and the description correctly implies a parameterless call.

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 name 'get_contact_details' and the description both point at the contact/get-in-touch area, and the second sentence usefully clarifies the tool's scope boundary (it is not a submission surface). However, the description never states what the tool actually returns - contact details, a form, an email address - leaving the concrete resource underspecified relative to its sibling content 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?

The line 'There is no endpoint an agent can submit to' is a genuine when-not signal that prevents an agent from misusing this as a write/submission path. It does not, however, say when to prefer this over list_team or read_page for contact-related information, so the routing guidance is only half-present.

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 implies a read operation by saying 'list', but discloses nothing about ordering, pagination behavior, or result shape, and the limit/pagination detail lives only in the 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?

A single front-loaded sentence with the resource first and the domain qualifier in parentheses; there is no filler to remove.

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 one-parameter list tool with no annotations and no output schema, the definition covers what the tool returns conceptually but omits ordering and result-format expectations the agent would otherwise have to discover by calling it.

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?

Only one parameter exists and its schema description coverage is 100% (default 20, max 50), so the schema carries the meaning. The prose adds no constraint or format information beyond it, making the baseline 3 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?

States a specific verb (list) and resource (articles) and even scopes the content domain (web development, performance, SEO), so the agent knows what it will get back. It does not explicitly distinguish itself from siblings like list_case_studies or search_content, but the resource is unambiguous enough to separate it.

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 indication of when to choose this over search_content (keyword search) or read_page, nor any prerequisites or exclusion conditions. Usage is only implied by the name and the domain note.

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 full burden, and it does disclose one genuine behavioral trait beyond the schema: results come back 'newest first'. However, it says nothing about read-only nature, pagination behavior beyond the schema's limit, total counts, or result shape, leaving the behavioral picture thin.

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 zero filler; the resource and the sort order are both delivered immediately 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 simple read-only list tool with one optional parameter, no annotations, and no output schema, the description covers the resource and ordering well enough to invoke correctly. Minor gaps remain around result shape and pagination, but nothing critical is missing.

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 single 'limit' parameter already documents its default (20) and maximum (50). The description adds no parameter meaning beyond that, so the 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 names a specific verb and resource ('List client projects Pavels Web Solutions has delivered') plus the ordering ('newest first'), which separates it from list_articles, list_services, and list_team by subject matter. It stops short of explicitly contrasting itself with those siblings, so it is clear but not sibling-differentiating.

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 explicit when-to-use, when-not-to-use, or named alternative; the agent must infer from the tool name and resource scope that this is for portfolio/case-study browsing. Usage is implied rather than stated, which is the minimum viable level.

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 load. It discloses the return shape (summary plus a page reference) but says nothing about ordering, pagination, or whether the result set is static. For a zero-parameter read that is thin but acceptable given its triviality.

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-loaded with the verb and resource, and the trailing clause adds meaningful return-value detail without 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?

For a simple zero-arg listing with no output schema, the description covers the essentials: what is listed and what each item includes. It omits return structure beyond the item shape and any usage context, which is a gap but not fatal.

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 no parameters, so the baseline is 4. The description correctly implies a parameterless enumeration and describes what each returned entry contains.

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 (List) and resource (services) and describes the returned shape: each service with a summary and its describing page. It is distinguishable from list_articles/list_team/list_case_studies by resource, though it doesn't explicitly contrast against 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?

No when-to-use guidance, no indication of when to prefer search_content or read_page over this listing, and no prerequisites mentioned. Usage is inferable from the name but not stated.

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 full behavioral burden and discloses almost nothing: it doesn't say whether results are paginated, what fields each person entry contains, or whether it is a safe read. 'List' weakly implies read-only, but the agent gets no confirmation.

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 short sentence that front-loads the verb and target with no wasted words. It is efficient, though it leaves room for one more clause of routing or return-value context.

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 zero-parameter read tool with no output schema, the definition is minimally viable but omits what a caller would want: the shape of returned person records and how it relates to the sibling lookup tools.

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 the baseline is 4; there is nothing to document and the description correctly implies no filtering input is accepted.

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 (List) and resource (people/team) scoped to one organization, so the agent knows exactly what entity is returned. It does not distinguish itself from siblings such as get_contact_details or search_content, which may also surface people, so the routing value is incomplete.

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 no indication of when to call this versus get_contact_details (for a single person) or search_content. There are no exclusions, prerequisites, or alternative-selection cues at all.

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 usefully discloses the return format (Markdown full text) and that only public pages are served, but says nothing about behavior on an invalid path, rate limits, or whether content is cached/static.

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: the first establishes what is returned, the second the prerequisite. No padding, and the core capability 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?

With no output schema, the description correctly states the return format (Markdown text), and it covers the path-acquisition prerequisite. It is nearly complete for a single-param read tool; only error/failure behavior is left unstated.

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 already gives a format example for `path`. The description adds only the constraint that the path must be valid and where to get one, which is helpful but not meaningfully beyond 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?

States a specific verb (read/return), resource (one public page of pavels.dev), and output form (Markdown), and scopes it against the sibling list_* tools by requiring their paths. An agent can immediately tell this fetches a single page's content rather than enumerating content.

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?

Explicitly names the prerequisite: use list_services, list_case_studies or list_articles first to obtain a valid path. This is clear routing guidance, though it does not state when NOT to use it (e.g., for non-public or contact pages, which siblings cover).

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 exist, so the description carries the full burden. It usefully discloses a real behavioral constraint — only titles and summaries are searched, not full page bodies — which helps scope expectations. However, it omits matching behavior (substring vs exact phrase), case sensitivity, result format, and any result limits, so it is not complete.

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 front-loaded sentence with no filler; the scope constraint is stated immediately. Nothing wasteful.

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 over a small content set, the description covers what is searched, which is the key unknown. Since there is no output schema, it could have said something about what results look like or whether all matches are returned, but this is a minor gap for a tool of this complexity.

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?

Single parameter with 100% schema description coverage ('The phrase to look for.'), which already matches the description's wording almost verbatim. The description adds little syntax or format detail (no quoting, operators, or false-positive guidance), so 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?

States a specific verb (Search) and resource scope (titles and summaries of services, case studies, articles), which is enough to distinguish it from the list_* siblings at a glance. It stops short of explicitly contrasting itself with list_articles/list_services, but the verb choice makes the distinction inferable.

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 is only implied: an agent can infer 'use this when you have a phrase to look up' versus browsing with the list_* tools. There is no explicit when/when-not guidance or named alternative, so it lands at the minimum-viable level.

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