Edgar & Edgarette: SEC Filing Boards

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

No annotations are provided, so the description carries the full burden. It usefully discloses that data is sourced from SEC EDGAR, every row links to its filing, and the data is free and CC BY 4.0. It does not disclose update cadence, whether the data is cached or live, or any rate-limit behavior, but for a simple list-like tool the disclosed traits are reasonably helpful.

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 brief and well-structured: a clear subject line, a short list of content categories, and a final sentence covering source, linking behavior, and licensing. Every sentence earns its place with no filler or 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 single-optional-parameter list tool with no output schema, the description covers the data domain, specific agreement types, data source, row-level filing links, and licensing. It does not enumerate return fields beyond the link or state update frequency, but those are minor gaps for a straightforward retrieval tool.

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 has one parameter, limit, and its description is already 100% complete, explaining max rows, default, ceiling, and response metadata. The tool description adds no additional meaning about the limit parameter, 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 clearly identifies the resource: material agreements under SEC 8-K Item 1.01, with sponsorships, naming rights, and partnerships as examples. It does not state an explicit verb like 'retrieve' or 'list,' but the tool name and noun-phrase description make the action clear. The subject matter is distinct enough from the sibling tools, though it never names or contrasts them.

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 scope is implicit: use this when you need material agreements, SEC 8-K Item 1.01 disclosures, or sponsorship/naming-rights/partnership agreements. However, there is no explicit guidance about when not to use it or which alternative tool might be better, leaving the agent to infer fit from the 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?

With no annotations, the description carries the full burden. It adds useful context: data is sourced from SEC EDGAR, every row links to its filing, and the data is free under CC BY 4.0. It does not disclose freshness, update cadence, rate limits, or explicit read-only behavior, but for a simple GET-style data tool the provided context is reasonable.

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 extremely tight, with each phrase delivering distinct information: content, form type, source, row-link behavior, and licensing. It is front-loaded and contains no filler or repetition.

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

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

For a one-parameter list retrieval tool with no output schema, the description covers the core invocation needs: what data is returned, where it comes from, that rows link to filings, and that access is free. It could mention data coverage or refresh behavior, but nothing essential for calling the tool 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?

The input schema has 100% coverage for the only parameter, limit, including default, ceiling, and response indicators. The description adds no parameter-specific meaning, but it does not need to because the schema already fully documents the parameter.

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 as Annual Meetings backed by SEC Form DEF 14A definitive proxy statements, sourced from SEC EDGAR. This makes the returned data concrete and distinguishes it from sibling tools like get_mergers or get_breaches. It relies on the tool name for the action verb, but the resource 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 implies the tool should be used when an agent needs annual meeting or proxy statement data. It does not explicitly state when not to use it or name alternative tools, but the subject matter is distinct enough to infer the intended use case from the sibling list.

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 must carry behavioral disclosure. It adds useful context: data source (SEC EDGAR), that every row links to its filing, and CC BY 4.0 licensing. It does not disclose response shape, truncation behavior, or access constraints, though the limit semantics appear in the schema.

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

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

The description is concise and dense, with the key subject in the opening phrase and supporting facts (source, row links, license) in short clauses. There is minor redundancy with the tool name, but no wasted sentences.

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 dataset, the description plus schema suffice: it names the data domain, provenance, row-to-filing link, and limit behavior. It lacks an explicit statement of when to use it and typical response fields, but those are not essential for a simple retrieval call.

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 `limit` parameter is already fully described in the schema, including default, ceiling, and returned counters. The tool description adds no parameter information, so the high schema coverage baseline of 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?

Identifies the resource precisely: SEC 8-K Items 4.01 and 4.02 covering auditor changes and non-reliance, sourced from EDGAR. Though it opens with the title-like phrase 'Auditor Watch' rather than an explicit action verb, the domain is unambiguous and clearly distinct from siblings such as get_breaches or get_mergers.

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 prefer this tool over alternatives or when not to use it. The only implicit signal is that it is for auditor-change and non-reliance surveillance, so an agent must infer applicability from the tool name and data domain.

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 burden, and it does well by disclosing the data source (SEC EDGAR), update timeliness ('same day'), row-to-filing links, and usage rights (free, CC BY 4.0). It does not mention rate limits or response shape, but those are less critical for a read-only public feed.

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 remarkably dense: four short phrases deliver brand, regulatory basis, coverage, timeliness, source, linkage, and licensing. Every clause earns its place and the most identifying information ('Breach Clock', SEC 8-K Item 1.05) 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 one-parameter, no-output-schema tool, the description covers the essential context: what data is included, where it comes from, how current it is, how rows link to filings, and re-use rights. It could mention row fields or date coverage, but the 'every filer' and 'same day' phrases sufficiently orient an agent.

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 only parameter `limit` already fully documented including default, ceiling, and response fields (total/returned/truncated/more). The main description adds no parameter-specific meaning, so the baseline of 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 identifies a specific resource (SEC 8-K Item 1.05 breach disclosures), a clear scope ('every filer'), and distinct topical relevance compared to siblings like get_agreements or get_auditor_watch. It lacks an explicit action verb like 'returns' but 'Breach Clock' and the tool name make the retrieval purpose clear 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?

There is no guidance on when to use this versus alternatives, no mention of prerequisite context, and no exclusion criteria. The topic itself implies usage (when a user asks about breach filings), but nothing explicit is stated.

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

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

With no annotations provided, the description carries the behavioral burden. It usefully discloses the SEC EDGAR source, that every row links to its filing, and the CC BY 4.0 license. It does not mention data freshness, rate limits, or coverage limits, but for a read-only list-style tool this is acceptable.

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 compact and front-loaded with the topic name, quickly adding filing type, subject coverage, source, link behavior, and license in a few words. Every segment earns its place, though the telegraphic style is somewhat bare.

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 no required parameters, a complete parameter schema, and a simple list-retrieval purpose, this description provides sufficient context: it names the data source, the filing category, the covered subjects, and the per-row linking behavior. It stops short of explicitly stating the return shape, but the SEC EDGAR and filing-link details make the use case clear.

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 documents the only parameter, `limit`, including its default, ceiling, and the response metadata (total/returned/truncated and `more`). With 100% schema description coverage, the tool description does not need to add parameter details; it adds a row-level fact about filing links but nothing about the 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 clearly identifies the resource as charter amendment filings under SEC 8-K Item 5.03 remain articles, bylaws, and fiscal year terms. Although it lacks an explicit verb like 'retrieve' or 'list,' the domain is specific enough to distinguish it from sibling tools such as get_agreements or get_annual_meetings.

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 scope is precisely stated—SEC 8-K Item 5.03 amendments to articles, bylaws, and fiscal year—so an agent can infer when to use it. However, no alternatives or exclusion conditions are mentioned, leaving routing decisions among the sibling tools to implicit domain separation.

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 burden of behavioral disclosure. It adds valuable context: the data source (SEC EDGAR), the filing linkage per row, and the licensing terms. It does not describe pagination or ordering, but the tool is a simple read-style list with a single optional 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?

The description is compact and front-loaded, using short labeled phrases. Every sentence contributes relevant information about the content, source, linkage, or licensing, with no wasted words.

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 list tool, the description provides sufficient context: what the data represents, the regulatory basis, the source, and row behavior. It is slightly incomplete in not clarifying ordering or recency, but it is otherwise adequate for an agent to invoke correctly.

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

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

The input schema already documents the only parameter, 'limit', with its default, ceiling, and response behavior. The description adds no additional parameter-level meaning, so the baseline score of 3 applies since schema coverage is 100%.

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: officer moves related to SEC 8-K Item 5.02 departures and appointments. This is specific enough to distinguish it from the sibling tools, though the description lacks an explicit action verb and relies on the tool name's 'get' prefix.

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 it should be used for officer departure/appointment data sourced from SEC EDGAR, but it does not explicitly state when to use this tool versus the many sibling event tools such as get_mergers or get_restructuring. 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?

With no annotations, the description carries the full transparency burden. It discloses that the output is reporting, not investment advice, that figures come from SEC EDGAR, and that source links are included. It also describes the analytical nature ('actuarial-style reading') and mentions 'cautions', giving an honest picture of what the tool returns.

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 core explanation is front-loaded with the tool's purpose and content. The sentences are informative, but the trailing 'From POPS4; confirmations: Jenny Huang Goodman MPA MSc MHSA, Principal.' adds provenance/credential detail that is not essential for invocation and slightly dilutes focus.

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 a single parameter, no output schema, and no annotations, the description does a solid job of explaining what the agent will receive: recent filings, a 10-K reading with specific dimensions, a projected range, cautions, and source links. Minor gaps like exact recency or formatting are acceptable at this complexity level.

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 covers the single parameter with 'company name, ticker or CIK' at 100% coverage. The description repeats that same input flexibility in words, but adds little beyond the schema, 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 clearly identifies the tool as producing a performance card for SEC filers, naming the input types (name, ticker or CIK) and outlining the contents (recent filings, 10-K actuarial reading). It is specific about the resource and result, though it does not explicitly contrast with sibling tools like get_auditor_watch or get_ipo_watch.

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

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

Usage context is implied: an agent would use this when it needs a comprehensive performance snapshot of a public company, including filings and 10-K analysis. However, there is no explicit statement of when to prefer this over the many sibling watchlist tools, nor any exclusion criteria or alternative routing.

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. It usefully adds provenance ('Sourced from SEC EDGAR'), row-level behavior ('every row links to its filing'), and licensing ('Free, CC BY 4.0'). It does not mention update frequency, rate limits, or whether the data is read-only, though a watch/list tool strongly implies read-only access.

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 compact and front-loaded, with each clause adding distinct value: domain, filing type, data source, row behavior, and license. There is no redundant or filler text.

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 data-lookup tool, the description plus schema covers the essential invocation context: what data is returned, where it comes from, how rows link to filings, and how pagination works. The lack of an output schema is partially compensated by the parameter description's mention of total/returned/truncated and the `more` link. Minor gaps like update cadence do not block correct use.

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% for the single parameter, and the schema already explains limit's default, maximum, and the response metadata it controls. The tool description adds no parameter-specific meaning, but none is needed because the schema is complete.

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: SEC Form S-1 filers / companies registering to go public, which distinguishes it from sibling watch tools like get_mergers or get_breaches. It lacks an explicit action verb like 'list' or 'retrieve,' but 'IPO Watch' plus the S-1 context makes the purpose unmistakable.

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: use this tool when you want IPO registration data from SEC filings. It does not explicitly state when not to use it or compare it to alternatives such as get_company_performance or get_restructuring, but the domain is specific enough for basic routing.

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 must carry the behavioral transparency burden. It states the data source (SEC EDGAR), that 'every row links to its filing,' and the licensing terms, which is useful behavioral context. However, it does not describe the overall return shape, pagination, or whether any side effects occur, though 'get' implies read-only.

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 concise and well-structured: each clause adds a distinct piece of information—topic, SEC item basis, data source, row-link behavior, and licensing. It is front-loaded with the core subject and contains 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-parameter tool with no output schema, the description covers the essential context: what data is included, the regulatory basis, the source, and a key output behavior (filings linked). It does not enumerate return fields or provide explicit usage exclusions, but given the tool's simplicity these omissions are minor.

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 fully documents the 'limit' parameter, including default, ceiling, and response metadata behavior. The description adds no additional parameter-specific meaning, matching the baseline score 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 clearly identifies the resource as 'Identity Mergers' and specifies 'SEC 8-K Items 2.01 and 5.01 · completed acquisitions and control changes,' which precisely scopes the data. It lacks an explicit verb like 'returns' or 'lists,' but the tool name and context make the action unambiguous. The subject matter is distinct from all listed siblings, so an agent can tell them apart.

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 this tool—when the user asks about completed acquisitions or control changes from SEC filings—and the sibling names are clearly different. However, it does not explicitly state when not to use it or mention alternative tools for related queries, leaving routing mostly to inference.

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 transparency burden. It discloses the data source (SEC EDGAR), that every row links to its filing, and the licensing terms (Free, CC BY 4.0), which is useful context. It does not mention return structure, pagination behavior beyond the schema, or any read-only guarantees.

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 very compact and front-loaded with the core topic, followed by source, row-link behavior, and licensing. The fragmentary style is slightly terse, but every clause contributes 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 single-parameter tool with no output schema, the description is mostly adequate, covering topic, source, and row-link behavior. However, it never states what fields or data each row contains beyond the filing link, which would help an agent understand the result without invoking the tool.

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 fully documents the single `limit` parameter. The description adds no additional semantics about the parameter, but none are necessary 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 identifies a specific resource: SEC 8-K Item 2.05 restructuring events, with a clear data topic around exit/disposal costs. Although it lacks a verb like 'retrieves,' the regulatory reference distinguishes it from all sibling data 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?

Usage is implied through the topic: an agent needing restructuring-related SEC 8-K Item 2.05 data should use this tool. However, there is no explicit when-to-use guidance, no mention of alternatives, and no 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?

With no annotations, the description carries the full burden. It discloses that pricing is 'live from the POPS4 catalogue at wholesale' and specifies the return contents (total, per head, tier band, links, confirming person). It does not explicitly state whether the operation is read-only, but the nature of pricing implies no side effects. The description adds meaningful behavioral context beyond the schema, though it could be more explicit about non-mutating 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?

The description is a single sentence that is front-loaded with the core purpose, followed by examples and return details. It is efficient with no filler, though the inclusion of the contact person's full name and title could be seen as slightly verbose. Overall, it is well-structured and 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 parameters (2 enums, 1 number), no output schema, and no annotations, the description covers the main purpose, provides examples for the board parameter, and lists the output components. It lacks explicit guidance on tier and attendees, and does not explain the output fields (e.g., what 'tier band' means), but these are largely self-explanatory. The description is fairly 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 0%, so the description must compensate. It adds value for the 'board' parameter by providing examples that map board values to program themes (e.g., mergers -> welcoming the new team). However, it does not explain the semantics of 'tier' (enum) or 'attendees' (number). The description partially bridges the gap but leaves two parameters under-explained.

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 a specific action (price) applied to a specific resource (program for a filing) and gives concrete examples (mergers -> welcoming the new team; cmo-moves -> a new leader's launch). It distinguishes from sibling get_* tools by focusing on pricing rather than data retrieval. The purpose is unambiguous and actionable.

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 this tool (when you need to price a program for a filing type) and provides examples that map board values to program types. It does not explicitly state when not to use it or name alternative tools, but the sibling tools are clearly about fetching filing data, so an agent can infer the appropriate context. The guidance is implicit rather than explicit, but adequate.

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

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

With no annotations, the description carries the full burden. It discloses the main side effect (sending an email), the recipient requirement, and the one-click stop link, which is useful. However, it does not mention whether this creates a recurring subscription, how often emails are sent, failure behavior, or any permission/consent considerations.

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 three tight sentences. It front-loads the core action, then gives prerequisites, then adds a useful behavioral detail about the stop link. No filler or 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 side-effecting tool with no annotations and no output schema, this is reasonably complete: it covers the trigger, inputs, and unsubscribe mechanism. However, it omits the meaning of the 'board' parameter and gives no indication of what the agent should expect as a response or confirmation.

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 description adds meaning for 'company' (exact filing name), 'email' (the person's email), and 'cik' (alternative identifier). But schema coverage is only 25%, and the 'board' enum parameter is completely unexplained in both schema and description, leaving a notable gap.

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 ('email a person') tied to a precise trigger ('the day a company files with the SEC'). This clearly distinguishes watch_company from the sibling get_* tools, which retrieve data rather than send email alerts.

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 gives clear context: use this when someone should be notified by email about an SEC filing. It also states the required inputs (email, company name or CIK). It does not explicitly list alternatives or when-not-to-use, but the action is distinct enough from the sibling retrieval tools that the intended use is evident.

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