Edgar & Edgarette: SEC Filing Boards

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

With no annotations, the description carries the full burden and does a fair job: it discloses the data source (SEC EDGAR), that each row links to its filing, the reply shape (one-line answer plus date), licensing (Free, CC BY 4.0), and freshness (this week). Gaps remain on pagination/rate behavior, but the read-only, public nature is clear.

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?

It front-loads the question it answers, which is the most useful framing, and stays short. A few telegraphed fragments ('Material Agreements.', 'Free, CC BY 4.0.') are slightly wasteful but the overall length is appropriate.

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 tool with no output schema, the description covers the return shape, provenance, and licensing, which is what an agent needs to call it correctly. Only the absence of explicit sibling routing keeps it from being fully 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%, and the schema itself documents the limit default, ceiling, and truncation/more-link behavior. The description adds nothing about the limit parameter, so the baseline 3 for schema-documented params 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 states a specific resource and scope — public companies signing a material agreement this week — and pins it to SEC 8-K Item 1.01, which distinguishes it from generic filing tools. However, it never names the closest siblings (get_mergers, get_restructuring, get_charter_amendments), so an agent must still infer the boundary from the 8-K item number.

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

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

There is no explicit when-to-use or when-not-to-use guidance and no alternatives are named, even though many siblings also surface SEC filing events. The 'this week' framing implies a freshness scope but does not tell the agent how to choose this tool over get_mergers.

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 disclosure burden. It adds meaningful context: data is sourced from SEC annual reports, the dataset covers 12 companies, it excludes prices and ratings, and it is openly licensed under CC BY 4.0. It does not mention auth, rate limits, or latency, but for a zero-parameter read-only retrieval these are less critical.

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, opening with the tool's identity and core scope. Every element—scope, source, metrics, exclusions, licensing—adds value, though the dense metric list makes it slightly less skimmable than it could be.

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 tool with no output schema, the description is largely complete: it states what the tool returns, the data source, the size of the dataset, and its limitations. A description of the output shape would add some value, but an agent has enough information to invoke the tool 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 tool has zero parameters and the schema has 100% coverage (an empty properties object), so the baseline is naturally high. The description does not need to explain parameter behavior and none is missing.

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 ('AI Leaders'), its scope (12 US public companies in the AI business), and the data it contains (revenue, growth, operating margin, etc.). It also distinguishes itself from sibling tools by explicitly stating 'No prices, no ratings,' which separates it from price_program and similar offerings.

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 useful context for when to use this tool: when an agent needs AI-company fundamentals from SEC filings, not prices or ratings. However, it does not explicitly name alternative tools or provide when-not-to-use conditions, leaving the agent to infer the routing decision 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?

With no annotations, the description carries the load and does reasonable work: it discloses the data source (SEC EDGAR), the freshness window (this week), that every row links to its filing, and the reply shape (one-line answer plus date). It omits auth needs and rate limits, but the behavioral picture is materially fuller than a bare restatement.

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?

Compact and front-loaded, leading with the user question the tool answers. Slight waste in the fragment 'Annual Meetings.' which restates the topic already conveyed, but overall 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 single-optional-parameter lookup with no output schema, the description supplies the essentials: what it returns, where data comes from, licensing, and the response format. Enough for an agent to call correctly, though it says nothing about limit behavior, which is left entirely to the schema.

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

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

Only one parameter exists and schema description coverage is 100%, so the schema already documents limit fully (default 50, ceiling 200, truncation behavior). The description never mentions limit, so it adds nothing 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?

Opens with a specific interrogative framing a concrete verb and resource: public companies filing annual meeting proxies this week, pinned to SEC Form DEF 14A. The DEF 14A / annual meeting topic cleanly distinguishes it from siblings like get_agreements, get_mergers, or get_charter_amendments.

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 topic and data source imply when the tool is relevant (annual meeting proxy filings this week), but there is no explicit when-to-use or when-not-to-use statement and no named alternative among the many sibling tools. Usage is inferable from subject matter rather than stated.

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

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

With no annotations, the description carries the burden and does reasonably well: it discloses the data source (SEC EDGAR), that every row links to its filing, licensing (CC BY 4.0, free), the shape of the reply (one-line answer plus date), and truncation signalling with a `more` link. It does not discuss auth requirements, but none appear needed.

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?

Front-loaded with the question it answers, then tight fragments on source and scope. Slightly fragmented ('Auditor Watch. SEC 8-K Items 4.01 and 4.02 · auditor changes and non-reliance.') with mild redundancy between the opening question and the fragment line, 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-optional-param read tool with no annotations or output schema, the description covers scope, sourcing, response shape, and truncation. Only the routing vs. sibling tools is left implicit, which is a minor gap given the specific topic.

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 single `limit` parameter is fully documented there, so the schema does the heavy lifting. The description restates the default/ceiling and mentions total/returned/truncated response metadata, which adds marginal rather than new parameter meaning.

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 leads with the exact question the tool answers — public companies that changed auditors or issued non-reliance this week — plus the underlying SEC 8-K Items 4.01/4.02. This is a specific verb+resource framing that an agent can distinguish from siblings like get_breaches or get_restructuring.

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 implies the usage context ('this week', auditor changes, non-reliance) but never says when to prefer it over adjacent tools such as get_breaches or get_restructuring, nor does it state exclusions. Usage is inferable from the topic but not spelled out.

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 behavioral burden, and it does not disclose whether this is a pure read, what data scope or snapshot it covers, auth needs, or rate limits. The 'not advice' disclaimer adds a small amount of context but nothing operational.

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?

It is a single dense sentence built from in-house jargon ('Edgarette's', 'cash cows and cash machines', 'places for cash') that is not front-loaded with a plain statement of purpose. It is not excessively long, but the structure forces the reader to decode rather than understand.

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

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

With no output schema and no annotations, the description must explain what the caller gets back, and it does not — only the scoring concepts are named. Field-level return semantics and the shape of the result are left entirely unspecified.

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

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

The tool takes no parameters, so the baseline is 4. With an empty schema there is nothing to document, and the description does not need to compensate.

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 conveys that this is a scorecard of the boards' past calls scored against real outcomes, but it never states plainly what the tool returns or in what form. The stylized lead ('The boards' own calls, locked at the 6 Oct 2026 close with a SHA-256 receipt') obscures the specific verb+resource. It is distinguishable from siblings like get_cash_leaders only by inference.

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 when-to-use guidance, no prerequisites, and no comparison to any sibling tool. 'A test of the boards, not advice' is a disclaimer rather than an instruction, leaving the agent to guess the trigger condition.

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

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

With no annotations, the description carries the full burden and does well: it discloses the data source (SEC EDGAR via POPS4), the licensing terms (Free, CC BY 4.0), the composite nature of the record, and what each result contains including a one-line answer and citation line. It does not state rate limits or explicitly confirm the read-only/no-side-effect profile, but a 'get_... as filed' retrieval makes that largely self-evident.

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?

Front-loaded with the question it answers, then a single dense sentence enumerating scope and outputs. It is long and list-heavy with some redundancy ('brand record' echoed by 'brand-moving 8-K filings'), but every clause adds substantive content rather than 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?

There is no output schema, so the description must explain return values, and it does: names with dates, rename-vs-style distinction, tickers/exchanges, categorized 8-K filings linked to source, plus one-line answer and citation line. Source, license, and input scope are all covered, leaving nothing material an agent needs to call 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?

Schema coverage is 100% and the single 'company' parameter is fully documented in the schema. The description's '(name, ticker or CIK)' restates the schema description rather than adding format, disambiguation, or edge-case meaning, 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?

States a specific verb+resource ('what is this company's brand record, as filed') and enumerates the concrete contents: filing names with dates, tickers/exchanges, and brand-moving 8-K categories. An agent can distinguish it from narrower siblings like get_charter_amendments or get_mergers, though it never explicitly names those siblings even though their subject matter overlaps with what this tool 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 scopes the input ('for any US SEC filer (name, ticker or CIK)') but gives no when-to-use vs when-not guidance and does not route to alternatives such as get_charter_amendments or get_mergers for single-facet questions. Usage is only inferable from the stated scope, with no 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?

With no annotations, the description carries the full burden and does disclose meaningful behavior: data source (SEC EDGAR), coverage ('every filer'), freshness ('same day'), that every row links to its filing, and that it is free under CC BY 4.0. It also describes the reply shape (one-line answer with date). It does not discuss rate limits or read-only semantics explicitly, but the 'get' framing makes this a low-risk read.

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 tool's purpose is front-loaded in the first sentence, and the remaining fragments (source, cadence, licensing) are informative rather than filler. The middle-dot fragments and branding phrases like 'Breach Clock' are terse but slightly stylistic rather than strictly necessary.

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 lookup with no output schema, the description supplies what an agent needs: the subject matter, the sourcing, the freshness, and the shape of the reply. Nothing essential about calling it 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?

Schema description coverage is 100%, and the single `limit` parameter is already fully documented in the schema, including the total/returned/truncated fields and the `more` link. The description adds no parameter-level meaning beyond that, 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 states exactly what data is returned (public companies that disclosed a cybersecurity incident via SEC 8-K Item 1.05), which is a specific resource and clearly distinct from siblings like get_mergers or get_agreements. It frames the purpose as the question it answers rather than as a verb+resource, so it reads slightly indirect, but an agent can tell what it gets without opening the schema.

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

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

Usage is only implied through the question framing — an agent infers it should call this when it wants breach disclosures. There is no explicit when-to-use/when-not-to-use statement and no named alternative among the many sibling lookup tools, so guidance is adequate but thin.

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

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

With no annotations, the description carries the full burden, and it does add real behavioral context: the data is ranked screens rather than recommendations, prices are latest quarter-end 13F prices, and every company passes a stated soundness screen (no warning filing in 12 months, assets greater than liabilities, 4+ audited years). It still omits return format, pagination, and any auth/rate-limit behavior, so it is helpful but incomplete.

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 purpose is front-loaded, but the description is one dense block that crams three separate data categories (cash leaders, short-term places, monthly dividend payers) plus methodology into a single sentence-heavy paragraph. It is information-rich but poorly structured and longer than it needs to be for a no-argument retrieval 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 zero-parameter tool with no output schema and no annotations, the description thoroughly covers the content categories and screening criteria an agent needs to judge relevance. Format, pagination, and volume of results are unstated, but the substantive return content is well described.

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

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

The tool takes zero parameters, so there is no parameter semantics to explain; the baseline for a no-parameter tool is 4. The description does not need to compensate for any schema 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?

States a specific verb+resource (cash leaders) and enumerates exactly what the screen contains: top 20 US companies by cash returned to owners, operating cash/market value, and expected return, plus short-term funds and monthly dividend payers. It is clearly distinguishable from the parallel get_ai_leaders and get_energy_leaders siblings by content, though it never names them explicitly.

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 describes what is included but gives no when-to-use guidance, no exclusions, and no routing to alternatives. An agent cannot tell from this text when to prefer get_cash_leaders over get_ai_leaders or get_etf_health, so selection is left entirely 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, the description carries the full burden and does reasonably well: it discloses the reply shape (a one-line answer plus its date), that rows link to their filings, the source (SEC EDGAR), and licensing terms. It does not state auth requirements or latency/freshness beyond 'this week', but the read-only, non-destructive nature is clear from context.

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 scoping question is front-loaded and the whole definition is short with no filler. The telegraphic fragments ('Charter Amendments. SEC 8-K Item 5.03 · articles, bylaws, fiscal year · renames flagged.') are information-dense but read as staccato keyword dumps rather than prose.

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 lookup with no output schema, the description supplies the source, temporal coverage, return shape, and license, which is enough to call it correctly. Minor gaps remain around row semantics (e.g. what a 'charter amendment' entry contains) and update cadence.

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 single 'limit' parameter already documents default 50, ceiling 200, and the total/returned/truncated plus `more` link behavior. The description adds nothing about the parameter, 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 states a specific subject (public companies that changed name, charter or bylaws) and scopes it temporally ('this week'), which is enough for an agent to tell it apart from get_mergers or get_agreements. It never names a sibling tool explicitly, so differentiation is inferred 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 framing 'Answers: Which public companies changed their name, charter or bylaws this week?' implies the query this tool satisfies, and the SEC 8-K Item 5.03 / articles, bylaws, fiscal year line hints at coverage. There is no explicit when-not-to-use guidance or routing to any of the many sibling lookup tools.

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; it discloses provenance (SEC EDGAR, Item 5.02), that each row links to its filing, licensing (CC BY 4.0), and the reply shape (one-line answer with date). It is a low-risk read lookup, but it omits auth requirements, freshness/latency, and pagination behavior beyond what the schema mentions.

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?

Front-loads the question it answers, then compresses source, scope, output shape, and license into short fragments. Every sentence adds information with 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, read-only data lookup with no output schema, the description supplies the query intent, data source, recency scope, and the response shape (one-line answer plus date, linked rows). Nothing essential to correct invocation 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?

Only one optional parameter (limit) and schema description coverage is 100%, with the schema already specifying default 50, ceiling 200, and total/returned/truncated semantics. The description adds no limit-related meaning, 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?

States a precise resource and scope: public companies that changed a top officer this week, sourced from SEC 8-K Item 5.02. No sibling tool covers officer changes, so an agent can route to it unambiguously despite the 'CMO' name hinting at a narrower Chief Marketing Officer reading.

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 'this week' framing implies a recency-driven lookup and the question form hints at when it fits, but there is no explicit when-to-use, when-not, or alternative naming (e.g., vs get_agreements or get_mergers). Usage is inferable rather than 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 full burden. It discloses that the tool reports rather than advises, that figures come from SEC EDGAR with source links, and that the optional price is never stored or published. It also names the data source (POPS4) and a confirming principal. It does not disclose rate limits, failure modes, or what happens for non-filers, but the core behavioral traits are well covered.

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, information-dense paragraph that front-loads the core purpose and then adds relevant details. Every sentence earns its place, though the closing attribution ('From POPS4; confirmations...') is slightly tangential for an agent selecting the tool. Still, it is compact and well-ordered.

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 reporting tool with no output schema, the description covers the input (company), the optional parameter (price), the output contents (filings, actuarial reading, source links), and the safety profile (reporting, not advice). It lacks explicit pagination or error-handling details, but the tool's scope is simple enough that the description is largely 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%, so the schema already documents both parameters. The description adds meaning by explaining what the optional price enables (price/earnings, price/book, etc.) and that the price is not stored or published. This goes beyond the schema's basic parameter descriptions, though it doesn't add syntax or format details for the company 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 names a specific verb ('get') and resource ('performance card for any SEC filer'), and enumerates the card's contents (recent filings, actuarial-style reading of 10-K figures, source links). It clearly distinguishes itself from sibling tools like get_agreements or get_auditor_watch by focusing on company-level performance rather than a specific filing type or event.

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 the tool works for any SEC filer identified by name, ticker, or CIK, and clarifies the optional price parameter's role. It does not explicitly name sibling alternatives or state when not to use it, but the context signals and sibling list make the use case clear enough. A small gap: no explicit exclusion like 'for event-specific data, use get_agreements'.

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 of behavior. It discloses the data source (SEC annual reports), the universe (12 US companies), sector coverage, and exclusions, and points to the schema of get_ai_leaders for field semantics. It does not state update frequency or an explicit read-only guarantee, but zero parameters and the described dataset make that less critical.

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, covering scope, source, exclusions, and licensing in a few clauses. Minor redundancy appears in saying 'geothermal' both in the title phrase and the sector list, and it is one dense sentence rather than structured, but no word is wasted.

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

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

For a zero-parameter tool with no output schema and no annotations, the description gives enough information to select and invoke it: what it returns, its source, scope, and non-price nature. The only gap is that 'same fields as get_ai_leaders' defers the exact return structure to another tool's description.

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 no parameters and schema coverage is 100%, so there is no parameter-level gap. The description still clarifies the data content, which is all an agent needs for invocation.

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 dataset of 12 US renewable/geothermal public companies) and scope (solar, wind, grid, fuel cells, geothermal), and distinguishes it from get_ai_leaders by noting same fields. It lacks an explicit action verb like 'returns' or 'lists,' so it is clear but not maximally precise.

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 energy-leader data by naming the sector and comparing it to get_ai_leaders, and it states exclusions ('No prices, no ratings'). However, it never explicitly says when this tool should be chosen over siblings such as get_ai_leaders or price_program, leaving the routing partly 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?

No annotations are provided, so the description carries the behavioral burden. It discloses useful traits: the data source (SEC EDGAR), that each row links to its filing, the reply opens with a one-line answer and date, and that the data is free under CC BY 4.0. It stops short of stating read-only safety or auth/rate-limit details, but the retrieval nature is clear.

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 front-loaded with the core question and is brief. However, some fragments ('IPO Watch', 'SEC Form S-1 · companies registering to go public') partially repeat the first sentence's meaning, so it is not perfectly waste-free.

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 lookup with one optional parameter and no output schema, the description provides enough context: scope, source, cadence, row-link behavior, and licensing. Nothing essential for correct invocation appears 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 schema has 100% description coverage for the single limit parameter, including default, ceiling, response metadata, and a more link. The tool description adds no additional meaning about that 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 states a specific question the tool answers ('Which companies filed to go public this week?') and identifies the underlying source and filing type (SEC Form S-1, SEC EDGAR). This clearly distinguishes it from generic corporate or financial siblings like get_annual_meetings or get_mergers without requiring the reader to open the schema.

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 for when to use the tool by framing it as the answer to a specific IPO-filing question. It does not name explicit alternatives or when-not-to-use conditions, but the intended usage is unambiguous for an agent.

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 does disclose provenance (SEC EDGAR), that every row links to its filing, and licensing (Free, CC BY 4.0), which implies no auth barrier. However it never states access/permission requirements or rate limits, and read-only status is only inferred from the 'get_' naming and license phrasing.

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 front-loaded question immediately orients the agent, and the trailing fragments are information-dense (source, item numbers, licensing). Minor waste in the standalone 'Identity Mergers.' fragment, but overall tight.

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 essential return shape (one-line answer with date, rows linking to filings) and provenance. It is nearly complete, missing only explicit access/refresh-cadence details.

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

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

Schema description coverage is 100% and the single parameter already documents default (50), ceiling (200), and the total/returned/truncated reply plus the `more` link. The description adds nothing about `limit`, so the baseline 3 for fully-covered schema applies.

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

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

The description names a specific verb+resource (completed acquisitions and control changes from SEC 8-K Items 2.01/5.01) in the form of the exact question it answers, which is far more precise than a bare 'get mergers'. It does not explicitly differentiate itself from near siblings like get_restructuring or get_agreements, but the resource scope is distinctive enough to identify.

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?

Framing the tool as answering a concrete question ('Which public companies completed an acquisition or changed control this week?') gives clear context for when to reach for it. There are no explicit exclusions or named alternatives, so it falls short of a 5, but an agent knows the triggering scenario.

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 explicitly states 'Read' and 'Display only, not a rating' indicating a non-mutating, informational operation. It discloses internal behavior (funds looked through to N-PORT holdings) and licensing (CC BY 4.0). Missing details like handling when both CIK and holdings are provided, or error conditions, but these are minor for a display-only 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 detailed but every sentence adds value: purpose, input modes, inner workings, output list, and caveat. It front-loads the core purpose. It could be trimmed slightly (e.g., listing all metrics is long) but remains efficient for the information density.

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 tool with two optional parameters and no output schema, the description is quite complete. It names the input modes, explains the transformation, and enumerates the output metrics. It leaves out error handling and edge cases (e.g., malformed holdings), but these are typical and not necessary for correct 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 baseline is 3. The description adds meaning beyond schema by clarifying the either/or relationship (CIK or holdings) and the interpretation of holdings (ticker and weight). It also explains that funds are looked through to N-PORT, which affects how holdings are processed. This raises it above baseline.

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 clear verb (read) and resource (whole stock portfolio via SEC filings). Distinct from siblings like get_etf_health (portfolio vs ETF) and get_company_performance (single company vs portfolio). The description lists many specific metrics, removing ambiguity about what the tool does.

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 context that it reads portfolios via CIK or holdings, but does not explicitly state when to prefer this over siblings like get_etf_health or get_company_performance. It implies usage for portfolio-level health analysis but leaves exclusion conditions implicit. The 'Display only, not a rating' clarifies it is not a rating tool, but no alternative tool is 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?

With no annotations the description carries the full burden, and it does disclose the data source and its limits (not a rating, ratings/regulatory capital absent from SEC data) plus the covered universe (P&C reinsurers plus RGA). However, it never says how results are keyed or selected, which matters because the tool takes zero parameters, so it is unclear whether it returns all reinsurers or a fixed set.

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 purpose is front-loaded, but the entire body is a single sprawling run-on sentence whose long metric enumeration is hard to parse. Since there is no output schema, documenting the metrics has value, but the lack of any structural break hurts readability.

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

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

For a zero-parameter tool with no annotations or output schema, the description does the heavy lifting: it lists the returned metrics, the source, the covered insurers, and the key limitation. The one real gap is that it never clarifies how the result set is determined in the absence of any input parameters.

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?

Zero parameters, so per the rubric the baseline is 4. The description does not need to explain invocation parameters, though it leaves open how the caller scopes the result set.

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?

Names a specific resource (reinsurer strength metrics) and a specific source (SEC filings), and enumerates the exact metrics returned, so the agent knows precisely what this produces. It is distinguishable from the financial/company-metric siblings by its unique reinsurance focus, though it never explicitly contrasts itself with any of 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?

"for placing reinsurance" hints at the intended context, and the closing caveat ("not a rating; ratings and regulatory capital are not SEC data") usefully sets expectations. But there is no explicit when-to-use vs. an alternative, and no guidance on how this relates to the other financial tools in the set.

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 and does well: it names the data source (SEC EDGAR), license (Free, CC BY 4.0), cadence (this week), and states every row links to its filing plus that the reply opens with a one-line answer and its date. It does not restate read-only/cost characteristics, but a 'get/Answers' framing makes the read-only nature clear.

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?

Front-loads the core question and stays short. Minor waste in the standalone fragment 'Restructuring.' and the choppy separator style, but every remaining clause (source, license, row linkage, reply shape) 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?

No output schema exists, so the description must convey return shape, and it does: a one-line answer with date, rows linking to filings, plus the schema's total/returned/truncated and 'more' behavior. Sufficient for a single-parameter read tool; only minor gaps remain around ordering/recency guarantees.

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 single 'limit' parameter (default 50, ceiling 200, truncation/more link) is fully documented in the schema. The description adds no parameter meaning beyond that, so baseline 3 applies.

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

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

States a specific verb+resource framed as a question: 'Which public companies reported restructuring costs this week?', tightly scoped to SEC 8-K Item 2.05 exit/disposal costs. The niche (restructuring costs) is distinguishable from siblings like get_mergers or get_breaches, though no sibling is named explicitly.

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 by the natural-language question framing, so an agent can infer the query it satisfies. However, there is no explicit when-to-use/when-not guidance and no routing to related siblings such as get_mergers, which may overlap for layoff/exit events.

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 burden and does disclose data provenance (N-MFP3, N-PORT, 10-K), granularity (month by month), and specific metrics such as Rule 2a-7 liquidity, $1 price held, 7-day yield, months without a loss, worst month, compounded return, and dividend years/yield. It does not cover read-only status, rate limits, or pagination, but it adds substantial context beyond 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 information-dense but opens with a metaphor ('Kept its word') that delays the plain purpose, and 'boat signs' is unclear. The remaining sentences efficiently enumerate vehicle types and data points, but the structure could front-load the core retrieval action.

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, one-parameter tool with no output schema, the description adequately explains what data categories are returned and from which filings. It lacks detail on return format or pagination, but the metric-level enumeration compensates for the missing output schema.

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 single ticker parameter is already documented with an example and the empty-for-all behavior. The description repeats the ticker/no-ticker distinction ('for one record, or none for all') without adding format or filtering semantics 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 identifies a specific subject: whether cash-sweep vehicles (money-market funds, short-term Treasury/bond funds, dividend payers) 'kept their word' month by month from SEC filings. It names the filing types and metrics for each, so an agent can tell this is a data-retrieval tool about sweep vehicles, though it does not explicitly contrast with 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?

It only says 'Give a ticker for one record, or none for all,' which mirrors the schema and is about parameter use, not when to choose this tool over alternatives. There is no when/when-not guidance or pointer to siblings like get_etf_health or get_cash_leaders.

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.