Misar.Blog MCP Server

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

No annotations provided, so the description carries the burden. It discloses the idempotency behavior (no-ops if already reacted) and auth requirement (API key), which is genuinely useful. However, it doesn't mention whether reactions are reversible (via remove_reaction), mutation effects, or any 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?

Two concise sentences with zero wasted words. The no-op and auth information are front-loaded and earn their place. An exemplar of minimal efficient description.

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 2-param mutation tool with full schema coverage, the description covers the essentials. However, no output schema exists and no annotations are provided, so the description could usefully note the return value or error behavior—a modest gap for a write operation.

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 both parameters well-documented (type with enum, article_id as UUID). The description adds minimal beyond the schema—no additional constraints, relationships, or usage context for the parameters. 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?

Clear verb+resource: "Add a reaction to an article." Distinguishes from sibling remove_reaction, and the no-op idempotency note adds specificity. However, it doesn't enumerate the reaction types or how this differs from other article-modification 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 no-op on already-reacted behavior gives useful implicit context about idempotent retries, and requires API key mentions a prerequisite. But it doesn't explicitly state when to use this over get_reactions or remove_reaction, or alternatives for different reaction behaviors.

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 of behavioral disclosure. The description gives no information about side effects (e.g., does adding affect position ordering of other articles?), idempotency (can an article be added twice?), permissions required, or whether the operation is reversible. For a mutating tool with zero annotation coverage, this is a significant gap.

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 efficient sentence with zero filler. It is appropriately sized for what it conveys, though it could have included more behavioral detail without becoming bloated.

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?

This is a mutating operation with no annotations and no output schema. The description should disclose what happens on success (return value), failure conditions (e.g., article already in series, series not found), and side effects. With only a one-clause sentence, the description is incomplete relative to the tool's complexity and the absence of supporting annotations.

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 all three parameters are already documented in the schema. The description itself adds no parameter-level meaning beyond the tool name. The `position` parameter's schema even provides '(optional, appends if omitted)' context, so the schema already does the heavy lifting. 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 verb (add) and resource (existing article) with target (series). It distinguishes from siblings like create_series (creating a series) and create_draft (creating an article), and from get_series (reading). The phrase 'existing article' clarifies it operates on an already-published/non-draft article, adding useful scope context beyond just the tool name.

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 explicitly state when to use this tool versus alternatives like create_series or update_article. There's no context about prerequisites (e.g., must the series already exist? must the article be published?), nor exclusions (e.g., cannot add drafts). It provides no guidance on when NOT to use it, leaving the agent to infer from the tool name alone.

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 behavioral disclosure burden. 'Save' implies a non-destructive create operation, which is a reasonable signal, but the description doesn't disclose whether saving creates a new draft each time, whether a draft with the same title gets replaced, or whether there are publishing constraints. For a create operation this is acceptable but could clarify uniqueness behavior and the returned artifact (draft ID, etc.).

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 concise sentence with a useful parenthetical qualifier. Every word earns its place, no filler or redundancy. It's front-loaded with the core action and resource.

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 fairly simple creation tool with 3 parameters, full schema coverage, and no output schema or nested objects, the description covers the essentials. It lacks some detail like whether the draft is immediately listable, whether review is a manual process, or uniqueness constraints, but given the tool's simplicity and rich schema, this is adequate.

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 all three parameters (tags, title, body_markdown) are described in the schema. The description adds the context that this is for drafts and markdown format, which slightly supplements the schema. However, it doesn't add meaningful information beyond what the schema provides, meeting the baseline of 3.

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 (save) and resource (article as a draft on Misar.Blog) with a specific purpose (for review before publishing). It distinguishes this from related tools like publish_article and update_article by framing the draft as a pre-publication state. It could be slightly more explicit in contrasting with publish_article, but the purpose is clearly conveyed.

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 parenthetical '(for review before publishing)' implies this is the creation step before publishing, which gives some usage context. However, it doesn't explicitly state when to use this versus update_article or publish_article, nor does it mention that it creates initially while update_article modifies existing drafts. No explicit when-not-to-use or alternative tool guidance is given.

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 of behavioral disclosure. 'Create' implies a mutation, but the description doesn't state side effects, whether it requires authentication, whether series are immediately publishable, or what happens on duplicate titles. It doesn't disclose uniqueness constraints or any limits on series creation.

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 clear sentence that states the action, the resource, and the purpose. Zero wasted words. Efficient and appropriately sized for a simple 2-parameter creation tool.

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?

As a simple creation tool with 2 well-documented parameters and no output schema or nested objects, the complexity is low. The description is sufficient for identifying the tool but lacks richer behavioral context such as error conditions, duplicate handling, or return values that an agent might need for robust 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%, so both parameters (title and description) have their own schema descriptions. The tool description itself adds no parameter-level detail beyond the schema. However, it reinforces the purpose of the description parameter ('Short description of the series'). Baseline 3 is appropriate since the schema handles documentation adequately.

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+resource ('Create a new series') and adds the purpose of grouping related articles, making the action clear. It's distinguishable from siblings like add_to_series (which adds articles to an existing series) and get_series (which retrieves), though it doesn't explicitly name these alternatives. The 'group related articles' clause provides useful context beyond the bare name.

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 given on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., required roles, whether series creation requires an existing profile), nor does it contrast with add_to_series or update_article. Context is only implicitly inferred from the tool name and sibling names.

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 discloses the side effect of uploading to CDN, which is useful. However, it doesn't mention likely behavioral traits such as cost/credits consumption, asynchronous generation time, whether the operation is reversible, or whether existing cover images get replaced. For a tool that creates external resources, more behavioral disclosure would be valuable.

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 concise sentence that delivers the core purpose efficiently. It's appropriately front-loaded with the action verb and includes the key destination detail. Minimal waste, though it could arguably mention cost or timing in the same space.

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?

Despite 100% schema coverage and just 2 params, this is a 'generate' tool with side effects (CDN upload) and potential cost implications. With no annotations and no output schema, the description should disclose what the upload returns, cost implications, typical generation time, and whether the image is immediately usable. For a tool of moderate complexity involving AI generation and external storage, this is under-specified.

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% with both parameters documented (prompt and size, including the enum values). The description adds the CDN upload context which hints at purpose but doesn't add parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate given full schema coverage.

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+resource: 'Generate a cover image using AI and upload it to the Misar.Blog CDN'. It clearly identifies the action (generate), method (AI), and destination (CDN upload). It doesn't explicitly differentiate from siblings, but the purpose is distinct enough given sibling names like generate_title_seo and research_topic.

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, or when not to use it. There's no mention of whether this should be used before creating drafts, cost implications, or constraints around image generation. The description is purely declarative with no usage context.

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 transparency burden. It discloses the output count (5 titles), optimization targets, and that each title includes a keyword strategy hint — decent behavioral context. However, it doesn't disclose limitations (e.g., no guarantee of rankings, no indication of whether this mutates anything or is read-only, or how the keyword-selection logic behaves).

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 the core verb+action, and additional detail on optimization targets and output characteristics. No wasted words, though slightly dense with jargon (SEO/AEO/GEO acronyms without expansion).

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 2-param text-generation tool with 100% schema coverage and no output schema, the description adequately explains what the tool produces. The schema handles parameter details well. Minor gaps: doesn't describe the return format structure for the 5 titles or the keyword strategy hints, but this is acceptable given text-generation output variability.

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 both parameters (prompt and optional context), including a strong example for prompt. The description adds value by noting the prompt is a 'topic or keyword prompt' and that titles are long-tail focused, but doesn't add format/semantic depth beyond what the schema's example and descriptions provide. 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?

Clear verb+resource: generates article titles from a topic/keyword prompt. Distinct from sibling suggest_titles (broader) and research_topic (research-focused) by specifying SEO/AEO/GEO optimization, but doesn't explicitly differentiate itself in the description text — differentiation is only inferable from sibling names.

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 text-generation usage via 'from a topic or keyword prompt' and details title characteristics (high-volume, low-competition long-tail). However, it doesn't explicitly state when to use this over suggest_titles or when not to use it (e.g., for non-keyword-based brainstorming), and no exclusions or alternatives are named.

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 transparency burden. It names the three metric categories returned (views, revenue, subscribers), giving some transparency about output content. However, it doesn't disclose the aggregation behavior (grouped by day vs single totals), whether revenue requires special setup (e.g., monetization), or any rate limits. With zero annotations, more behavioral disclosure would be warranted.

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 efficient sentence that conveys the tool's purpose and metric scope. No wasted words or redundant claims. Front-loaded with the key verb and resource. Could be slightly more structured but is appropriately minimal for a single-parameter tool.

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 analytics tool with one well-documented parameter, the description is largely adequate — it names the metrics and time scope. However, with no output schema and no annotations, it doesn't clarify the return format (e.g., date-bucketed series, percentage changes, totals) which an agent would need to interpret results. Given the tool's simplicity, this is a minor-but-real 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?

Schema coverage is 100% — the single 'days' parameter is fully documented in the input schema with default, min, and max. The description mentions 'time period' which maps to the days parameter, providing consistent context. Since the schema fully covers the one parameter, baseline 3 is appropriate; the description adds little beyond what's structured.

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?

Clear verb+resource+scope: 'Get analytics summary' with specific metrics listed (views, revenue, subscribers) for a time period. Distinguishes from siblings like get_profile, get_reactions, get_article which are different resources. Slightly lower because the summary metrics are parenthetical rather than fully elaborated, but purpose is well stated.

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 retrieving aggregated analytics over time frames, but provides no explicit guidance on when to prefer this over sibling analytics-adjacent tools or alternatives. No exclusions or prerequisites stated. The single-parameter design makes usage fairly self-evident, so a mid score reflects adequate but not explicit guidance.

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 of behavioral disclosure. The description states it returns markdown content, which is helpful. However, it doesn't disclose whether the full article body is included, whether drafts/non-published articles are returned, error behavior for nonexistent slugs, or any request constraints. For a read tool without annotations, more behavioral context would be valuable.

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 sentence that conveys the core purpose and a key behavioral detail (markdown content). Zero wasted words, front-loaded with the action verb. This is appropriately concise for a single-parameter read tool.

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?

Tool complexity is low: 1 parameter, no output schema, no nested objects. The description covers the basics — what it does and what it returns. However, with no annotations and no output schema, the description is the only source of behavioral information. It could benefit from noting whether this returns the same data as list_my_articles items, and whether unpublished drafts are accessible. For a low-complexity read tool this is adequate but not complete.

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%, with the single 'slug' parameter described as 'The article slug'. The description adds the format hint 'including full markdown content' but doesn't specify slug format requirements (e.g., case sensitivity, URL-encoded format, required format). With 100% coverage, the baseline of 3 applies, and the description does slightly more by indicating what the returned content will include, though it doesn't add meaningful precision about the slug parameter itself.

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 'Get a single article by slug, including full markdown content' clearly states the verb (get), resource (single article), and the identifying mechanism (slug). It distinguishes from sibling list tools like list_my_articles and search_articles by specifying single-article retrieval, and adds the markdown content detail. It's clear but doesn't explicitly differentiate from potential similar single-item tools like get_series, though the resource is obvious.

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 context (retrieve one article when you know its slug), but provides no explicit when-to-use versus alternatives guidance. No exclusions or alternative tool references are given. For a simple retrieval tool this is acceptable but could mention that search_articles or list_my_articles are the alternatives when the slug is unknown.

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 safety burden. 'Get' implies a read operation, and the description explicitly says 'public follow status' and 'no API key required', which signals low-risk read-only behavior. However, it doesn't disclose what happens for non-existent UUIDs or whether follow status is a boolean vs a direction (following/follower) field. The 'public' qualifier adds meaningful transparency.

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 efficient sentence that conveys purpose and access requirements with no wasted words. It's slightly thin in behavioral detail but well-structured and 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 simple single-parameter read tool, the description is mostly adequate. It covers the lookup key, returns follow status plus follower count, and clarifies no auth needed. Gaps include no output format description (though no output schema exists), and no error/edge-case behavior. For a low-complexity tool this is acceptable but not exceptional.

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%, with the single user_id parameter well-described in the schema. The tool description references it ('by their profile UUID') reinforcing that it expects a UUID format, which matches the schema's format constraint. Baseline 3 is appropriate since the schema fully handles the parameter documentation.

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 gets public follow status and follower count for a user by profile UUID. The verb 'Get' plus the resource (follow status) and input (profile UUID) are specific. It doesn't explicitly distinguish from siblings, but none of the siblings appear to be follow-status related, so differentiation isn't needed.

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 notes 'No API key required' which is useful access guidance, but doesn't explicitly state when to use this vs alternatives. There's no mention of prerequisites, exclusions, or alternative tools. Since follow status is fairly unique in the sibling set, the guidance is adequate but basic.

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 of behavioral disclosure. It doesn't state what data the profile returns, whether it fails without authentication, or what the response format looks like. For a read operation with no annotations, the description gives minimal behavioral context beyond 'get'.

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 concise sentence with zero wasted words. It's appropriately short for a simple parameterless retrieval tool. The brevity is appropriate given there are no parameters or complex behaviors to document.

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 get operation with no output schema, the description is reasonably complete. It names the exact resource and platform. However, it doesn't describe what the returned profile contains (name, bio, avatar, stats, etc.), which would help the agent know if this satisfies its need. Given the simplicity of the tool, this is a minor 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?

Tool has 0 parameters and schema coverage is 100% (there are no properties to describe). With no parameters, a baseline of 4 is appropriate per the rubric. The description doesn't need to explain any parameters since none 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 uses a specific verb+resource ('Get your Misar.Blog creator profile') that clearly states what the tool does. It identifies the resource as the creator's profile on Misar.Blog. However, it doesn't explicitly distinguish from sibling tools like get_article or get_follow_status, though 'creator profile' is fairly distinctive on its own.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when this would be preferred over get_article, get_analytics_summary, or other retrieval tools. The 'creator profile' distinction is implied but no explicit context or exclusions are given.

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 states 'Requires API key', which is a mild auth disclosure, but doesn't describe return format, whether counts are aggregated globally or per-reaction-type, or what 'your reactions' entails. For a read-only data tool with zero annotation coverage, this is minimal behavioral disclosure.

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 efficient sentence, zero wasted words. Statement of purpose plus a prerequisite note, no filler.

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-param read tool, this is reasonably complete. However, with no output schema and no annotations, the description doesn't clarify what data shape is returned (e.g., are reactions summed across types, broken down by emoji/kind, etc.), and it doesn't address the auth requirement's scope beyond 'API key'.

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 the single article_id parameter clearly documented as 'UUID of the article' in the schema. The description adds the 'reactions for an article' context but doesn't add format or semantics beyond the schema. 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 specifies a clear verb+resource+scope ('Get reaction counts and your reactions for an article'), which is specific and distinguishes it from add_reaction/remove_reaction siblings. The scope of 'counts and your reactions' adds useful granularity beyond just 'get reactions'.

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 mentions 'Requires API key', which is a prerequisite hint. However, it does not contrast with sibling tools (add_reaction, remove_reaction) or explain when to use this versus other read tools like get_article. Implied usage but no explicit exclusions or alternatives given.

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 of behavioral disclosure. It doesn't state return format, pagination behavior, whether it's a read-only operation, ordering of results, or any error conditions. For a list operation with no annotations, this is minimal behavior disclosure.

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, efficient sentence with no wasted words. However, it's arguably under-specified rather than appropriately concise, and could include additional useful context (return format, scope) without becoming bloated.

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?

This is a zero-parameter list tool with no output schema, so the requirements are modest. The description states the basic purpose. However, it doesn't mention key operational details like whether series include draft items, ordering, or what fields are returned per series. Given the simplicity, it's adequate but has minor gaps.

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 parameter count is 0, which gives a baseline of 4. With no parameters to document, the schema has nothing left unexplained. The description adequately covers the zero-parameter case, and there's nothing ambiguous for the agent to misinterpret.

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 (List) and resource (all your series on Misar.Blog). It distinguishes this from sibling tools like create_series and add_to_series, though it could be more explicit about what a 'series' is. The phrase 'all your series' establishes scope as user-owned 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?

The description provides no guidance on when to use this tool vs. alternatives. It doesn't mention when to choose list_my_articles vs. get_series, or note any prerequisites (e.g., must be logged in, must have series created). No exclusions or alternative tool references are given.

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 some burden. It discloses rate-limiting by IP and that no API key is required, which is useful auth context. However, it doesn't describe pagination behavior, whether deleted/hidden comments are excluded, ordering semantics, or what fields each comment contains. The rate-limit disclosure is helpful but more behavioral detail would strengthen this.

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, zero waste. Front-loads the core purpose and adds one relevant operational detail (rate limiting/auth). Highly 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 read-only list tool with 3 params, this is reasonably complete but has gaps. No output schema, no description of return shape, no pagination guidance beyond schema defaults. The rate-limit and no-auth disclosures are valuable, but the missing pagination/page-size semantics and output format leave the agent guessing about behavior for limit/offset usage.

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 only 33% — only article_id has a description in the schema. The description adds nothing about limit/offset semantics beyond their schema types/defaults. Since limit and offset have defaults and ranges in the schema but no prose explanation, and the description doesn't compensate for the low coverage gap, this sits at baseline 3.

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?

Clear verb+resource: 'Get public comments for an article.' Distinguishes from siblings (get_reactions, get_article) by specifying 'public comments' for articles. Though it doesn't explicitly contrast with sibling comment-related tools, the purpose is specific and direct.

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?

States rate-limited by IP and no API key required, which gives context but doesn't say when to use this vs alternatives. No mention that get_reactions handles reaction counts vs this tool handling comments. No exclusions or when-not-to-use guidance provided.

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. However, it provides no behavioral disclosure: no mention of read-only nature, pagination behavior, ordering (e.g., latest first), defaults beyond schema, or whether archived/drafts are included by default. The status parameter description hints at default behavior (omit for all published) but this is schema-level context, not description-level.

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, efficient sentence with no wasted words. It's front-loaded with the verb and resource. While terse, it achieves the essentials for a simple list tool.

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 list tool with no output schema and no annotations, the description should clarify return format, pagination, default behavior, and ordering. None of these are addressed. The schema covers the 2 parameters well, but the overall tool context is under-specified for an agent to confidently invoke it and interpret results.

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 both parameters (limit and status). The description adds minimal value beyond this; the status enum and limit constraints are fully described in the schema. Baseline 3 is appropriate since schema does the heavy lifting and the description adds nothing meaningful.

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 'List your articles on Misar.Blog' uses a specific verb ('List') with a clear resource ('your articles') and platform context. It distinguishes from siblings like get_article (singular) and search_articles (search-based). However, it doesn't explicitly clarify 'own articles only' vs all articles, though 'your' implies ownership.

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 explicit when-to-use guidance or alternatives are mentioned. The description doesn't contrast with search_articles or get_article, nor does it state when users should prefer this tool. The schema implies filtering by status, but the description gives no usage context or exclusions.

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's a read operation implied by 'Get' with no mention of destructive effects (which appear minimal). However, it doesn't disclose whether the returned list is paginated, whether issues are ordered chronologically, or whether the response includes body content or just metadata. For a list/read tool, the gaps are mild but present.

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 no wasted words. The auth requirement is front-loaded in sentence two. It's efficiently sized for the tool's simplicity, though it could arguably include a touch more behavioral context without bloat.

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 list tool with one parameter and no output schema, the description is mostly adequate. The auth requirement is mentioned, which is useful. However, given the 0% schema coverage and no output schema, the description could reasonably disclose what information the returned issues contain, how ordering works, or pagination limits beyond the 50 cap. It's functional but leaves the agent to guess about return shape.

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 coverage is 0%, so the description must compensate. The single parameter 'limit' has schema metadata (default 10, max 50, min 1) but the description adds zero meaning beyond what the schema already shows. Since the schema documents default/range but the description does not explain the parameter in operational terms (e.g., how to retrieve more than 50, pagination behavior), the description fails to add value here.

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+resource: 'Get your sent and scheduled newsletter issues.' This clearly indicates what the tool returns (newsletter issues, both sent and scheduled). It distinguishes reasonably from siblings like list_my_articles (articles vs newsletters) and list_newsletter_subscribers (subscribers vs issues), though it doesn't explicitly name an alternative.

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 notes 'Requires API key authentication,' which is a meaningful prerequisite. However, it doesn't provide when-to-use guidance vs alternatives like list_newsletter_subscribers, nor does it explain how the limit parameter affects paging or how to browse all issues beyond the default limit. Usage context is implied but not 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?

No annotations are provided, so the description carries full burden. It states that API key authentication is required, which is genuinely useful behavioral context. However, it doesn't disclose what subset of subscribers is returned, whether unsubscribed/bounced addresses are excluded, pagination behavior beyond the schema defaults, or what data fields are returned per subscriber.

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 concise sentences with zero wasted words. The key functional statement and the auth requirement are both front-loaded. There is room for more detail without bloating, but as written it is tightly structured.

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 list/retrieval tool with 0 params required, no output schema, and no annotations, the description is thin. It never tells the agent what subscriber data the response contains, whether pagination via limit/offset is supported for large lists, or how to interpret the results. Given multiple list_* sibling tools that could be confused, it should clarify 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?

With 0% schema description coverage and two parameters (limit, offset), the schema already documents both parameters clearly through their names, types, defaults, and constraints. The description adds no parameter-specific detail. Baseline 3 is appropriate since the schema handles the semantics well and there are no hidden or ambiguous parameters.

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 clear verb+resource pattern ('Get your newsletter subscriber list') that identifies the purpose. However, it doesn't distinguish from the sibling tool list_newsletter_issues, which one could confuse with subscriber management. There's no mention of scope (all subscribers vs pending/unsubscribed).

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 tool vs list_newsletter_issues or other list_* siblings. The only context is that it requires API key authentication, which is a prerequisite rather than situational guidance. No exclusions or alternatives are named.

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 of behavioral disclosure. 'Publish' implies a write/mutation operation, but the description doesn't state whether this requires authentication, whether scheduling ensures the article is hidden until the timestamp, what happens to visibility defaults, or whether publishing creates vs. publishes-an-existing-draft. The schedule_at parameter implies deferred publication but the description doesn't clarify the exact 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?

Single sentence, front-loaded with the primary verb and resource. Efficient yet covers both immediate and scheduled publishing. Could be slightly expanded but is appropriately concise for the information it conveys.

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 has 6 parameters (2 required) and no annotations. The schema covers all parameter descriptions at 100%, but there's no output schema describing the return value, and the behavioral aspects (auth requirements, confirmation of scheduling, whether publishing replaces create_draft) are unaddressed. Given the description's brevity and the number of parameters, it's minimally adequate but leaves meaningful gaps around sequencing with create_draft and scheduling semantics.

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 every parameter is documented in the schema (title, body_markdown, tags, visibility, schedule_at, cover_image_url). The description adds the 'schedule' clause which reinforces schedule_at, but adds no semantic value beyond what the schema already provides. Baseline 3 is appropriate given full schema coverage.

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 the verb 'Publish' and the resource 'article' on 'Misar.Blog', and adds the scheduling option. It's clear what the tool does. However, it doesn't distinguish from the sibling create_draft or update_article explicitly, though 'publish' vs 'create draft' vs 'update' are semantically 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?

The description implies usage for publishing new articles and optionally scheduling them. The scheduling behavior is explicit, and the sibling name create_draft provides contrast. However, no explicit when-to-use vs when-not-to-use guidance or alternatives are named, and the relationship to create_draft (does publish also create, or must a draft be published?) is not addressed.

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 of behavioral disclosure. It notes API key requirement (useful), but for a mutation tool it doesn't disclose what happens when the reaction doesn't exist (error? no-op?), whether removal is permanent, or what the response looks like. With no output schema and no annotations, this is a significant behavioral gap.

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 short sentence and appropriately front-loaded. However, it's slightly under-specified—the 'Requires API key' clause could be separated or expanded, and there's room to add behavioral context without bloat. It's brief but leans toward under-specification rather than tight efficiency.

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 2-parameter, enum-constrained tool with full schema coverage, the minimal description is borderline adequate. The description establishes the core purpose and auth requirement. However, given no output schema and no annotations, some mention of the response behavior or the need for the reaction to already exist would complete the picture. It's minimum viable.

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 both parameters (article_id with UUID format, type with an enum of like/clap/bookmark) are fully documented in the schema. The description adds essentially nothing beyond what the schema provides. Baseline 3 is appropriate since the schema does the heavy lifting.

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 ('Remove'), the specific resource ('a specific reaction'), and the target ('an article'). It establishes the tool's mutation role. It doesn't contrast with siblings directly, but the purpose is unambiguous enough that an agent can identify what this does at a glance.

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 notes 'Requires API key,' which gives some prerequisite context. However, it doesn't explicitly say when to use this vs add_reaction or when not to use it, nor does it clarify that the reaction must already exist to be removed. The requirement is implicit 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?

No annotations exist, so the description carries full burden. It discloses that the tool produces AI-generated outputs (insights, sources, outline) and signals it's a generation-type tool. However, it doesn't disclose whether this makes network calls, costs credit, has limits, whether results are cached, or whether it writes any state (it appears read-only/generative). Some ambiguity about whether 'sources' are real citations or AI-generated references.

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 convey purpose, deliverables, and usage timing. No wasted words. However, it front-loads the core action well. Slightly more could be added about tool behavior without becoming verbose, but as written it's tight and readable.

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, no-output-schema tool, the description covers the input expectation and the high-level deliverables. However, it's incomplete in that an agent can't anticipate the return shape (text? structured JSON? how many sources? what form does the outline take?) and there's no disclosure of cost, latency, or side effects. Given the tool's 'research' nature, more behavioral detail would help.

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 a well-described query parameter (topic/question, min/max length, specificity guidance). The description's 'Research a topic' adds the conversational framing but doesn't add meaningfully beyond the schema. The schema already tells an agent what to pass and that being specific helps. Baseline 3 is appropriate when the sole parameter is well-documented 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 (research) and resource (a topic), plus what's delivered: AI-generated insights, sources, and a content outline. It distinguishes from siblings conceptually since no other tool seems to do research, though it doesn't explicitly name alternatives. The purpose is specific and clear.

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 states 'Useful before writing an article,' which provides clear context for when to use it. However, it doesn't give exclusions or explicitly contrast with alternatives (e.g., suggest_titles, search_articles, generate_title_seo), which would clarify when NOT to use this tool. The temporal cue (before writing) implies usage but lacks explicit boundary-setting.

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; description carries burden. It implies read-only via 'Search' but doesn't state side-effect-free behavior explicitly, nor describe return format or pagination. Adds scope clarity (published-only) and sibling distinction, but omits behavioral detail a no-annotation tool ideally should disclose.

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-sentence description with no redundancy. Purpose and context delivered in the first sentence, tool-selection guidance in the second. Highly efficient and 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 4-param search tool with 100% schema coverage, the description covers the crucial scoping semantics and sibling distinction. No output schema exists, but for a list-returning search tool this is not a significant gap. Lacks mention of result ordering or absence behavior, but overall complete for the tool's 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?

Schema description coverage is 100%, with each of the 4 parameters already documented (q minLength, tag filter, author filter, limit range). The description adds the distinction of published-only scope and cross-creator search, which reframes how parameters should be used, but does not add per-parameter semantics beyond the schema. Baseline 3 is appropriate given full schema coverage.

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 clear verb+resource+scope: 'Search PUBLISHED articles across Misar.Blog by keyword, tag, or author — including other creators' work.' It explicitly distinguishes the scope (published, all creators) from the sibling tool list_my_articles, which covers drafts and unpublished posts. This precisely differentiates it from 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 explicitly contrasts with the sibling tool: 'Use list_my_articles for your own drafts and unpublished posts.' This is a clear when-to-use vs when-not-to-use directive naming the alternative. The qualifier 'PUBLISHED' plus 'including other creators' work' gives strong context on scope boundaries.

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. It states output quantity (5 titles) and SEO-friendliness, which adds some behavioral context. But it doesn't disclose whether it modifies/saves anything, whether it's purely generative (non-destructive read), or what the output format looks like beyond 'title options'.

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, zero waste. First sentence states the action, second provides alternative routing. Front-loaded and 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?

Single-param tool with full schema coverage and no output schema. The description adequately covers main use case and alternative. Minor gap: no mention of what happens on empty/short content or whether titles are returned in a specific format, but for a simple generation tool this is close to complete.

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 there is only 1 param (context), which the schema already describes well. The description adds the output context ('generate title options from content'), reinforcing the parameter's purpose. With full schema coverage and a single self-explanatory param, the baseline of 3 is slightly exceeded by the description clarifying what the content is used 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?

Specific verb 'Generate' + resource '5 article title options' + source 'from your existing article content'. Distinguishes from sibling generate_title_seo by noting alternative usage for keyword targeting or unwritten 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?

Description clearly implies when to use (when you have written content) and explicitly redirects to generate_title_seo for other cases. However, no explicit 'when-not' beyond the single alternative 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?

The description discloses the partial-update behavior (omitted fields retain values), which is a meaningful behavioral trait beyond what the schema reveals. However, with no annotations provided, the description carries the full burden and doesn't disclose the mutation/irreversibility nature, permission requirements, or whether updates affect published articles vs drafts differently. The update semantics imply mutation but nowhere state the consequence.

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 zero waste. The first sentence states the purpose and targets; the second adds the crucial partial-update qualification. Well front-loaded with the action verb first.

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 mutation tool with 4 params (1 required), full schema coverage, and no output schema needed, the description is largely adequate. The best-practice partial-update semantics are clearly communicated. The only gap is explicit callout that this mutates data (no annotations present), but given the tool's simplicity, the description handles most of the burden well.

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 all four parameters are already documented: id, tags, title, and body_markdown. The description adds the partial-update semantic — clarifying that omitted fields are preserved, which is valuable context beyond the schema. Body is described as 'Markdown' in both schema and description. The description adds moderate value but the schema carries most of the load, warranting the baseline 3.

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-action format: 'Update the title, body, or tags of an existing article or draft.' It clearly identifies the resource (article/draft) and the specific fields it can modify, distinguishing itself from sibling tools like create_draft, publish_article, and get_article. The partial-update semantics ('Only the fields you pass are changed') add meaningful scope clarification.

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 clear that only passed fields are changed while omitted fields keep current values — this is critical usage guidance that prevents accidental deletions. It addresses both 'existing article or draft' as valid targets. It doesn't explicitly name alternatives (e.g., use create_draft for new content), but the partial-update distinction provides clear context on when it applies versus siblings.

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 transparency burden. It discloses that open=true opens a browser page and start_trial starts a trial immediately, which are the key behavioral side effects. However, it doesn't disclose what the tool does when neither open nor start_trial is set (just returns info?), nor whether the trial start is reversible or requires eligibility confirmation. Acceptable but not rich behavioral disclosure.

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, zero waste. The description is front-loaded with the primary purpose, then usage guidance, then the key optional flag. Every clause 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 tool with 3 optional params, no output schema, and no annotations, the description covers the main use cases well: informational display, browser opening, and trial starting. It lacks detail on the output format (what the plan display looks like) and eligibility logic for trials, but for a relatively simple billing tool this is reasonably complete.

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 describes all three parameters well. The description adds value by indicating open=true is the default behavioral mode for opening checkout, subtly framing 'open' as the key toggle. However, the description mostly restates what the schema properties already say; the added value is marginal beyond the schema's high coverage, so not a 5.

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 shows the current plan, quota usage, and what upgrading unlocks, plus optionally opens checkout. The verb+resource (upgrade/show plan) is clear. It doesn't significantly differentiate from siblings (none directly related to billing), but the purpose is well understood. Slight deduction because 'upgrade' as a name suggests an action (performing the upgrade) while the description emphasizes showing/displaying information, creating minor ambiguity.

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 states 'Call it any time — not only after hitting a limit,' giving clear guidance on when to invoke. It also clarifies that open=true opens the checkout page. This is strong usage guidance that disambiguates the tool's role as informational-first with an optional action path.

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