Promptafire

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

Annotations already mark it read-only and non-destructive, and the description adds meaningful behavioral context beyond them: free content is always available, Pro lessons require an authorized account, otherwise a locked notice is returned. This is exactly the kind of conditional/permission behavior an agent needs to know.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, with the core operation in the first sentence and the access conditional in the second. No filler or repetition; each sentence adds necessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with a full output schema and safety annotations, the description covers the return behavior, the id source, and the main conditional case (Pro access). Nothing essential for invoking the tool correctly 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?

There is only one parameter, id, and the input schema already documents it as 'An id returned by search' with 100% coverage. The description reinforces that the id is a search-result id but adds no new syntax or format details, so the schema carries the semantic weight; 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 opens with a specific action and object: 'Return the full Markdown of one search result by id,' and it clarifies content types and access behavior. It gives clear scope, but it does not explicitly contrast with siblings like read_lesson/read_post beyond the 'search result' framing, so differentiation is implied rather than 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 establishes a clear usage context: after a search, by id, to obtain full Markdown, with access caveats for Pro lessons. It does not name alternative tools or state when not to use it, but the 'search result by id' constraint is sufficient guidance for a single-parameter fetch tool.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful return-content context by listing the four fields the agent can expect. It does not mention error behavior, permissions, or what happens when a slug is invalid, but that is minor for a simple read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact phrase with no wasted words and the key output fields are front-loaded. The lack of an explicit verb makes it slightly awkward as a sentence, but it remains quickly scannable and informative.

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, read-only tool, the description plus annotations and schema cover the essentials. There is no output schema, so the field list meaningfully compensates. The implicit 'returns a module by slug' behavior is clear from the title and required parameter.

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 single parameter slug has 100% schema coverage with a clear example, so the schema carries the parameter semantics. The description adds no special parameter meaning beyond implicitly referencing the module lookup. This matches the baseline for high 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 identifies the resource (a module) and the specific fields returned: description, duration, access level, and section list. It lacks an explicit verb, but the title 'Get a module' disambiguates the action. It does not explicitly contrast with sibling tools like list_modules, so differentiation is only implicit.

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 such as list_modules or read_lesson. There are no usage conditions, exclusions, or alternative routing. The need for a slug is only implied by the schema, not the description.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful context about the tool's completeness ('every track and module') and the fields returned, but does not disclose potential pagination, ordering, or authentication requirements. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It efficiently conveys scope and output content 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 no-parameter, read-only listing tool with no output schema, the description is sufficiently complete: it names the resource, the scope, and the key fields returned. An agent can select and invoke it correctly with the given information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema coverage is 100%, so no parameter documentation is needed. The description compensates by explaining what the returned list 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?

The description clearly states the action ('list') and resource ('modules'), and adds scope ('every track and module') plus return content ('access level', 'link to overview'). It is not a tautology, but it does not explicitly differentiate from siblings like get_module.

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 this tool is for obtaining the full curriculum, but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as get_module for a single module or search_curriculum for targeted searches.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context by specifying that only published posts are returned and listing the fields included, but it does not mention ordering, pagination, or whether the result is a full list versus a summary.

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 front-loads the core promise ('every published Promptafire blog post') and packs the output fields into a compact list. Every word earns its place; there is no repetition or 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 parameterless, read-only list tool, the description gives enough to understand the resource and the expected return contents (date, author, link). It does not mention sorting or pagination, but the low complexity and strong annotations make those omissions acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing for the description to explain beyond what the empty schema already shows. The schema coverage is trivially 100% and the description need not compensate for any parameter documentation gaps.

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 identifies the resource ('every published Promptafire blog post') and the output fields (date, author, link), making the tool's purpose clear. It lacks an explicit verb like 'list' or 'returns', but the tool name/title supply that, and 'every...' effectively distinguishes it from single-post tools like read_post.

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 such as read_post, search, or list_modules. It does not state any exclusions or preferred scenarios, so an agent must infer usage from the name and description.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context about access control (free vs Pro) and the Markdown return format, going beyond the annotations without contradicting them.

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: the first defines the purpose and return format, the second gives the access condition. No filler, no repetition, and the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only tool with two string parameters and no output schema, the description covers purpose, response format, and access conditions. The relationship to get_module via the section slug is also present in the schema, so no critical context 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%, with both 'module' and 'section' documented as slugs. The description doesn't add new parameter-level detail, but none is needed because the schema fully handles parameter semantics.

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') and resource ('Markdown body of one lesson section'), and scopes it precisely to a single section rather than a whole module or post. This differentiates it from siblings like get_module and read_post without needing to inspect their schemas.

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?

Provides a clear access-based usage rule: free modules are always readable, while Pro modules require a connected Promptafire account with Pro access. It does not explicitly name sibling alternatives or state when not to use it, so it stops short of a 5.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context by stating the return format is the Markdown body of a single post, but it does not mention error behavior, not-found handling, or any access requirements. With annotations present, this is adequate but not exceptional.

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 communicates the core purpose without filler. It is short, scannable, and contains no redundant content beyond what is needed.

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 tool with one parameter, full schema coverage, and safety annotations, the description is largely sufficient. It specifies the output format and object scope. It could be slightly more complete by mentioning what happens when the slug does not exist, but that is a minor gap given the low 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%, and the slug parameter is documented with its source ('Post slug from list_posts'). The description adds no extra meaning beyond the schema, so the baseline score of 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 title and description clearly identify the operation as reading a single blog post and specify that the return value is the Markdown body. This distinguishes it from listing tools like list_posts, though it does not explicitly contrast with read_lesson or fetch.

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 explicit guidance on when to use this tool versus alternatives such as read_lesson or fetch. The schema hints that the slug comes from list_posts, but the description itself does not communicate usage context, prerequisites, or exclusion criteria.

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

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

Annotations already mark it read-only and non-destructive, and the description adds useful behavioral context: the search is scoped to lessons and blog posts, and results include id/title/url plus exact id formats ('lesson:<module>/<section>', 'post:<slug>'). This helps an agent interpret and use results correctly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, each with a distinct job: state the search scope, list the result fields, and define id formats. No fluff or repetition, and the purpose 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 a single well-documented parameter, a read-only annotation set, and an output schema present, the description is complete enough for invocation. It tells the agent what is searched, what comes back, and how to interpret ids.

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 clear description for 'query' ('What to look for') and length limits. The description adds scope context but no additional parameter syntax or query-format guidance, so the baseline of 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 states a clear verb ('Search'), a specific resource ('Promptafire lessons and blog pots'), and the output payload ('ids for fetch, titles, and web URLs'). This distinguishes it from sibling tools like fetch, list_*, and search_curriculum by resource scope and role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly implies when to use the tool: when searching lessons and blog posts, and the returned ids are meant to feed into fetch. It does not explicitly state when to prefer search_curriculum or list_* instead, so it lacks explicit exclusion 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?

Annotations already declare the tool read-only and non-destructive, so the description only needs to add behavioral value. It does so by listing the returned fields and noting that snippets appear only 'when readable,' which is useful nuance. It does not mention limits or empty-result behavior, but these are minor for a simple search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one efficient sentence that front-loads the core action and then lists the return fields without filler. 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 one-parameter, read-only search tool with no output schema, the description adequately covers both what to pass and what to expect back. Missing details like pagination, result limits, and no-match behavior would be nice but are not critical given the tool's simplicity.

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 the query parameter already has a clear description in the schema. The tool description reinforces that the query is full-text but adds no new format, syntax, or example details 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?

The description states a specific action and resource: full-text search across Promptafire lessons. It distinguishes itself from list/read tools by emphasizing search, though it does not explicitly differentiate from the generic sibling tool 'search'.

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 the tool is for finding lessons by free-text query, but it gives no explicit guidance about when to use it instead of siblings like search, read_lesson, or list_modules. Usage context is inferred rather than stated.

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