LexRegPulse: Banking Regulation Brief

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 does disclose the output format (markdown), which is useful, but it does not explicitly state that the operation is read-only, mention any auth requirements, or describe error behavior (e.g., missing slug). For a simple get operation the disclosure is adequate but not rich.

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

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

A single, front-loaded sentence that states the purpose, output, and input format, and includes a concrete example. There is no redundant phrasing or filler, making it 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 one-parameter retrieval tool with no output schema, the description covers the essential context: what it does, what input it needs, where that input comes from, and what the output looks like. It omits error-handling details, but those are not critical for such a simple tool, so the description is sufficiently 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?

The schema already documents the 'slug' parameter with its source, achieving 100% coverage. The description adds value by explaining that the slug is the last path segment of the URL and providing a concrete example, which goes beyond the schema's basic description and clarifies the expected format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('get'), the resource ('one LexRegPulse deep-dive post'), and the output format ('as markdown'). It distinguishes this tool from siblings like get_blog_posts (plural list) and other content-type retrievers, leaving no ambiguity about what it returns.

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 when to use it (when you have a slug and need the full text) and even points to get_blog_posts as the slug source. However, it does not explicitly state when NOT to use it or name alternative tools for different post formats, so it stops short of full 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?

No annotations are present, so the description carries the behavioral burden. It discloses that this is a read-only listing operation, returns newest posts, and names the response fields, which is good transparency for a simple fetch. It does not cover limit/pagination behavior, but that is minor since the schema documents the limit and no auth or destructive concerns apply.

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

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

The description is two sentences and mostly earns its place: the first gives useful content context, and the second states the return contract and sibling routing. The opening brand/author framing is slightly redundant with 'long-form reads,' but it is not distracting and the most actionable 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 list tool with one optional parameter, the description is complete: it explains what the posts are, what fields are returned, and how to get the full text. No output schema exists, but the description supplies the return contract directly, so an agent has everything needed to invoke it correctly.

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

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

The schema already provides 100% coverage for the single `limit` parameter, including default and max values. The description adds no additional parameter meaning, 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 description states a specific operation – returns the newest deep-dive blog posts – and enumerates the exact output fields (title, date, summary, slug, canonical URL). It also explicitly contrasts itself with get_blog_post, which provides the full text, so the agent can distinguish the list-vs-detail tools.

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

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

It clearly says to use get_blog_post for the full text, which indicates this tool is for browsing summaries and metadata. This explicit routing guides the agent to the correct sibling without needing to inspect schemas. Other siblings are different content types and are not likely to be confused with this one.

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

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

With no annotations, the description carries the behavioral transparency burden. It discloses the return format (full edition as markdown), the canonical URL, addressable bullet anchors, QA-scoring, and default-to-most-recent behavior. It does not mention error handling for invalid dates, but for a read-only retrieval tool the disclosed behavior is strong.

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 long but information-dense, front-loading the core identity before listing sections and return details. Some clauses, such as the QA-scoring note, are not essential for invocation, but they add credibility without bloating the description excessively.

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 tool with no output schema, the description compensates well by specifying the markdown return format, canonical URL, bullet addressing, and default date behavior. It is nearly complete, though it does not specify behavior for invalid or unavailable dates.

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

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

The input schema already fully documents the single optional 'date' parameter with format and default behavior, so description-level parameter explanation is unnecessary. The description adds no new parameter semantics, keeping the score at the baseline for 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 clearly identifies the resource as LexRegPulse's daily banking regulatory brief, names its publication cadence, and enumerates its sections. This makes it easy to distinguish from sibling tools like get_weekly_digest and get_daily_podcast.

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 when the tool is relevant ('daily... published every morning at 6:45 AM ET') and clarifies the default date behavior, but it does not explicitly contrast it with the weekly digest, podcast, or blog tools. Usage context is clear, but no exclusions or alternative-selection guidance are 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?

With no annotations, the description carries the transparency burden and discloses the exact return contents (audio URL, RSS feed, matching written edition) and duration. It is clearly a read operation, and no destructive or authentication caveats are implied, though default/error behavior is not described.

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 focused sentence front-loads the resource name, then efficiently adds duration and return contents with no filler. Every element contributes to tool selection and invocation.

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

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

For a single-optional-parameter read tool with no output schema, the description supplies the retrieval target and the return fields an agent needs. It could be more complete by explicitly naming get_daily_briefing as the text-only alternative, but the core information is sufficient.

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

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

The schema fully documents the optional date parameter with format and default, so baseline 3 applies. The description adds little beyond 'day's' and does not need to repeat the schema's date details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource ('LexRegPulse Daily podcast'), clarifies it is the four-minute audio edition of the morning brief, and lists the returned items: audio URL, RSS feed, and matching written edition. This clearly distinguishes it from text-oriented siblings like get_daily_briefing and get_blog_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 gives clear context: use this for the audio podcast edition rather than the written briefing. It does not explicitly name alternative tools or state when not to use it, but the resource is identified precisely enough that an agent can route correctly.

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

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

With no annotations, the description must disclose behavior itself. It implies a read-only get operation ('drafted from...') but does not state side effects, failure modes (e.g., missing brief), or permission requirements. The output is described, but edge-case behavior is omitted, making it minimally transparent.

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, well-structured sentence that front-loads the tool's purpose and lists the output components. No wasted words or redundant 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 simple get tool with one optional parameter and no output schema, the description adequately conveys the expected return (lead, headlines, link). It does not cover error scenarios, but given the simplicity and available schema, 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?

Schema coverage is 100%, so the baseline is 3. The description does not mention the date parameter or its default behavior, but the schema already fully documents it as optional with a YYYY-MM-DD format and default to the most recent edition. The description adds no additional parameter context.

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 retrieves a LinkedIn-ready post derived from the day's sent brief, specifying its contents (lead, headlines, link). This distinguishes it from siblings like get_blog_post or get_daily_briefing, which serve different content types.

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 LinkedIn posts but does not explicitly state when to use it over alternatives like get_blog_post or get_weekly_digest. No when-not-to-use guidance or alternative routing is provided, leaving the agent to infer based on the LinkedIn-specific wording.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context by noting the tracker is deterministic, that data comes from structured Federal Register fields rather than prose, and that the result includes date, kind, title, and agency. However, it does not mention ordering, read-only nature, or any request constraints beyond the schema-covered 'days' parameter.

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, each with a distinct job: the first defines the resource and its source, the second lists the return shape. There is no filler, redundant wording, or restatement of the tool name.

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

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

Given the single optional parameter and lack of output schema, the description sufficiently covers what the tool returns and where the data comes from. Minor details like sorting or empty-result behavior are not mentioned, but this is a simple deterministic query and the description is otherwise 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?

The only parameter, 'days', is fully documented in the input schema with default and maximum values, so schema coverage is 100%. The description adds no additional parameter semantics, but the baseline for high schema coverage is 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 names a specific resource ('upcoming regulatory deadlines'), enumerates the two kinds of deadlines (comment windows, rules taking effect), and identifies the source (Federal Register structured fields). It explicitly states the return fields, making it clearly distinguishable from sibling content tools like get_blog_posts and get_daily_briefing.

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

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

There is no explicit guidance on when to use this tool or when to prefer an alternative. The description does not reference sibling tools or state selection criteria; the only signal is the topic itself, forcing the agent to infer applicability.

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

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

With no annotations, the description carries the burden. It states the return type (markdown) and the canonical URL inclusion, which is a useful behavioral detail. However, it remains silent on side effects, permissions, or any restrictions (e.g., whether the latest digest is always available). For a simple read tool, this is adequate but not rich.

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

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

Two sentences with zero filler. The first sentence front-loads the tool's purpose and content scope; the second covers the return format. Every word 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 one optional parameter, no output schema, and no annotations, this description is nearly complete. It explains what the digest contains, the typical availability (Sundays), and what the caller receives. The only minor gap is not stating that this is a read-only operation, but that is easily inferred from the 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%, and the parameter description already specifies the optional date format and default behavior. The description adds no additional meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's specific verb (get), resource (weekly digest), and scope (Sundays, weekly content categories). It distinguishes itself from siblings like get_daily_briefing and get_daily_podcast by naming the exact content format and frequency.

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 by describing the weekly digest's content and the optional date parameter, but it never explicitly says when to choose this over the daily briefing, podcast, or blog post tools. No alternatives or exclusions are 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?

No annotations are provided, so the description must carry the behavioral disclosure burden. It makes clear this is a read-only index returning metadata (dates, titles, URLs) and that full content must be retrieved separately. However, it doesn't disclose potential pagination, error behavior, or auth requirements. Since it's a benign list operation, a minimal-disclosure score of 3 is appropriate.

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

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

Two sentences, zero filler. The first sentence defines the tool's content, and the second gives a clear usage flow. The most important info (what it lists and how to use the result) is front-loaded.

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

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

For a single-parameter, read-only list tool with no output schema, the description is nearly complete: it states the output fields (dates, titles, URLs), the ordering context ('recent'), and the intended next step. The only minor gap is not explicitly stating that full editions are not included, though this is strongly implied by the follow-up instruction. The schema covers the limit 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 only parameter, 'limit', is already fully described in the schema with its default and max. Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning about the parameter beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear resource (the archive index) and its content ('recent daily briefs and weekly digests with dates, titles and canonical URLs'). It differentiates from siblings by explicitly naming the follow-up content tools (get_daily_briefing, get_weekly_digest), so an agent immediately knows this is the lookup/list tool, not a content fetcher.

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?

Gives direct usage guidance: 'Use it to find the edition that covered a date or a story, then call get_daily_briefing or get_weekly_digest with that date.' This explicitly describes when to use this tool and routes the agent to the appropriate siblings for the next step.

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

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

With no annotations, the description carries the full burden. It discloses the free nature, schedule, welcome email with one-click unsubscribe, and plain confirmation return. This provides a clear picture of the side effects, though it omits duplicate-subscription handling.

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

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

Four sentences, each adding value: the action and schedule, the usage condition, the welcome-email behavior, and the return type. It is efficient and front-loaded with the primary purpose.

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 subscribe tool, it covers the confirmation response, the key subscription details, and the exact condition. It lacks explicit error or duplicate-subscription behavior, but this is a minor gap 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 both parameters are already described (email and optional first name for greeting). The description adds no new parameter meaning beyond what the schema provides, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb 'Subscribe' and the resource 'email address to the LexRegPulse Daily Brief', and differentiates from sibling 'get' tools by its subscribe action. The schedule and welcome-email details add specificity.

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

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

Explicitly states the condition for calling: only when the user has asked to subscribe and provided the address. Does not name alternatives, but the action is distinct from the retrieval-focused siblings, so no exclusions are needed.

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