Nexqual

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so safety and idempotency are covered structurally. The description adds a genuine behavioral constraint beyond the annotations — coverage is limited to US stocks — which warns the agent about possible empty results. It does not disclose data freshness/update cadence or how many analysts contribute, which would be the remaining useful 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?

A single sentence, front-loaded with what the tool returns, with every clause carrying information (rating, targets, implied move, buy/hold/sell distribution, US-only scope). 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?

With no output schema, the description bears the burden of describing the return shape, and it does so thoroughly by enumerating the target statistics and rating breakdown. Annotations cover the safety profile. Remaining gaps — data freshness and behavior when no analysts cover the symbol — are minor for a single-parameter read 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?

There is only one parameter (symbol) at 100% schema description coverage, so the schema fully documents it; baseline is 3. The description's 'for a US stock' adds a mild constraint hint about what the ticker should identify, but no format examples or validation expectations 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 names the exact resource (Wall Street analyst consensus for a US stock) and enumerates the concrete outputs: consensus rating, 12-month price targets with mean/median/high/low, implied move, and buy/hold/sell counts. No sibling (quote, financials, earnings, insider trades, price history, SEC events, profile, superinvestors) overlaps with this data, so the agent can route unambiguously.

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 data returned — an agent wanting forward-looking analyst sentiment would pick this — and the phrase 'for a US stock' implicitly scopes it to US-listed tickers. However, there is no explicit when-to-use guidance, no stated alternative (e.g., vs. get_stock_quote for current price), and no note on what happens for non-US or uncovered symbols.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description does add genuine provenance context the annotations cannot convey: the strengths/strategy text is quoted from the latest 10-K with a link, and the Nexqual score is a derived 0-10 metric. It omits freshness of market cap and behavior for invalid tickers.

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

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

A single dense sentence with no filler, front-loading the core attributes before the derived score. It reads efficiently, though the telegraphic field-list style slightly 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?

With no output schema, the description carries the return-value burden and does so by enumerating the fields an agent will receive, including the 10-K link and the proprietary score. That is sufficient for a read-only single-param profile tool; only freshness and error behavior are unaddressed.

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% ('Ticker'), so the schema fully documents it. The description adds nothing about symbol format or exchange suffix conventions. Baseline 3 applies when the schema does all the work.

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 is a list of returned data fields (sector, CEO, HQ, market cap, 10-K excerpts, Nexqual score) rather than a statement of what the tool does. The verb 'get' is only implied by the tool name, and nothing distinguishes it from siblings like get_financials or get_stock_quote beyond the field inventory. Purpose is inferable but not 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?

There is no guidance on when to call this tool versus get_financials, get_stock_quote, or get_analyst_consensus, all of which could plausibly surface overlapping company data. No prerequisites, no exclusions, no context about intended use.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the description carries a lighter burden. It adds genuinely useful context beyond them: the source documents, the fact that guidance is included as stated rather than modeled, and the coverage universe (US, ~$10B+). Return shape and pagination behavior are not described.

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

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

Three compact clauses, zero filler, front-loaded with what is returned and immediately followed by the source, the estimate exclusion, and the parameter shortcut. Every phrase adds 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 two-parameter read tool with no output schema, the description covers what is returned, from where, and how to call it with or without a symbol. It leaves minor gaps around ordering, windowing, and what a limit actually caps, which are the only things an agent might still need to guess.

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% (baseline 3), and the description adds real meaning on top: 'Omit symbol for the latest across all' defines the default aggregation behavior of an optional parameter, and the $10B+ US universe hints at which tickers actually resolve.

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 and resource (reported EPS/revenue plus stated guidance) and pins the data provenance (8-K filings and press releases, captured at publication). It also draws the boundary against sibling get_analyst_consensus with 'Actuals only, no estimates', so an agent can route correctly without opening a 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?

Gives an explicit call pattern ('Omit symbol for the latest across all') and an implicit exclusion (no estimates, use the consensus tool instead). It stops short of naming the alternative tool or stating when the historical vs. latest mode should be preferred over get_financials.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is fully covered. The description adds valuable context about data sources (SEC 10-K/10-Q), historical depth (15 years annual, 40 quarters), and specific ratios included. It doesn't mention rate limits, time delays, or data currency, but with annotations covering behavior, this is a moderate addition.

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

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

Single sentence, front-loaded with the core data types, then details on sources and valuation metrics. No wasted words; it efficiently packs substantial information into one sentence.

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 data retrieval tool with no output schema, the description covers what data is returned (income statement, balance sheet, cash flow, valuation ratios) and sources/limits. It lacks explanation of parameter usage and any output format details, but given the simplicity and annotations, it 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 67%, with the 'symbol' and 'limit' parameters having schema descriptions but 'period' lacks one (only enum values). The description does not explain the parameters at all, leaving the 'period' enum semantics to be inferred from the enum values alone. Baseline 3 is appropriate given partial schema coverage, but the description could have added meaning for limit or period.

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

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

The description clearly states the verb+resource: fetching financial statements (income statement, balance sheet, cash flow) from SEC filings and valuation metrics. It distinguishes itself from siblings like get_company_profile or get_analyst_consensus by focusing on raw financial data. However, it doesn't explicitly contrast with siblings or state what it does not do.

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: use this when you need financial statements or valuation ratios. There is no explicit when-to-use guidance, no mention of alternatives (e.g., for analyst estimates use get_analyst_consensus), and no exclusions or prerequisites. An agent can infer the use case but isn't told about boundaries.

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

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

Annotations only cover the safe-read profile, and the description goes well beyond them: dollar thresholds ($250K+ buys, $1M+ sells), explicit exclusions (private placements, IPO allocations, ESPP, DRIP), and derived signals (cluster buying flag, Rule 10b5-1 plan flag plus adoption date). This is exactly the kind of filtering and derivation context an agent needs to trust the output.

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 purpose, then buys, sells, and defaults in a logical order; the parenthetical lists are information-dense rather than redundant. It is longer than a minimal definition, but nearly every clause carries filtering semantics that the agent would otherwise have to guess.

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 query tool with no output schema, the description covers scope, universe, thresholds, exclusions, derived flags, and defaults, which is sufficient to predict what comes back. Remaining unknowns (pagination, limit default) are minor against the rich coverage provided.

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

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

With schema coverage at 67%, the description still adds real meaning: it establishes the default side (buy) and default window (30 days) that the schema does not state, and explains the value thresholds that inform min_value_usd. It does not clarify limit behavior or the days range, leaving modest gaps.

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

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

States a specific verb and resource (insider buys/sells from SEC Form 4) and narrows scope to US companies ~$1B+, which distinguishes it from siblings like get_sec_events and superinvestors. The buy/sell side definitions with transaction codes (P, S) make the tool's domain unmistakable 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?

It discloses the default behavior ('Default: buys, last 30 days') and inclusion thresholds, which implicitly guides invocation, but it never names an alternative tool or states when this is preferable to get_sec_events or superinvestors. Usage is implied rather than explicitly prescribed.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is fully covered. The description adds content scope (dividends reinvested, splits included) and the range boundary, but nothing about latency, adjustment conventions, or response size/limits beyond what annotations give.

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

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

A single dense sentence, front-loaded with the primary output (closing-price series) before the secondary metrics. Efficient, though the long comma list of metrics borders on a data dump rather than guidance.

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, the description sensibly enumerates what is returned (prices, returns, dividends, splits), which is the key missing structured info. It does not state the default range when 'range' is omitted, a minor gap for an otherwise complete read-only 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 coverage is 50%: symbol is documented as 'Ticker' and range carries an enum. The description restates the range boundary ('1mo to max') but does not clarify the enum values (ytd, max) or symbol format beyond the schema. Baseline 3 for a mostly schema-documented parameter 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?

States a specific resource (closing-price series for a US stock or ETF) and enumerates the exact analytics returned: price return, total return with dividends reinvested, annualized return/volatility, max drawdown, high/low, dividends and splits. An agent can distinguish this from get_stock_quote (current price) and get_financials (statements) 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?

Scope ('US stock or ETF') and time span ('1mo to max') imply when this applies, but no explicit when-to-use or when-not-to-use guidance and no named alternatives (e.g., 'for a live price use get_stock_quote'). Usage must be inferred 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral value by stating that 8-K items quote the filing's own text and that ownership entries include holder and percent, but it says nothing about result ordering, limits, or how the days/limit windows affect output.

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 one dense but well front-loaded sentence: the core purpose ('recent SEC filings in plain words') leads, then the parenthetical elaborates the event taxonomy. The long list is informative rather than padding, though it sits at the upper bound of what a single sentence should carry.

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, the description carries the burden of describing returns, and it does so thoroughly — event categories, quoted filing text, holder/percent fields, and filing dates. It is nearly complete; the remaining gap is operational detail (defaults, ordering, result volume) that the agent might want before calling.

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% — symbol, days (default 180, max 1095), and limit (default 30) are all documented in the schema. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the heavy lifting.

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

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

The description names a concrete resource — recent SEC filings for a US company — and enumerates the exact filing/event types returned (8-K categories, 13D/13G stakes, 10-K/10-Q/proxy dates), so the agent knows precisely what comes back. It is clear what the tool does, though it never explicitly distinguishes itself from siblings like get_insider_trades, which is a plausible near-neighbor for the 13D/13G ownership data.

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 enumeration of covered event types implies usage (call this when you need corporate events, ownership stakes, or filing dates), but there is no explicit 'use this when' statement, no mention of when another tool such as get_insider_trades would be preferable, and no stated prerequisites. 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?

Annotations already cover the safety profile (readOnly, non-destructive, not idempotent, non-open-world), so the description's job is to add behavior, which it does: a 10-ticker batch cap and, crucially, that outside regular US hours the returned price is the last close rather than live data. Pointing the agent to follow the `note` field is useful but cryptic since no output schema defines that field.

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

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

Two dense sentences with the returned fields front-loaded and the market-hours caveat placed last where it matters. Minor deduction for the trailing 'follow `note`' reference to an undefined field, which costs a clause without resolving anything.

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, the description carries the return-value burden and does so by enumerating the fields. It also flags the stale-price behavior off-hours. It omits error behavior for invalid symbols and any unit/currency notes, which is the remaining gap.

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

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

With one parameter and 100% schema coverage the baseline is 3, but the description adds a real constraint not present in the schema: the batch is capped at 10 tickers and only US symbols are valid. It does not clarify symbol formatting (e.g. exchange suffixes), which keeps it from a 5.

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

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

States the concrete resource and the exact fields returned (price, change, day range, volume, 52-week range, market cap) plus the US-equity scope, so it is clearly a point-in-time quote tool rather than a historical or profile tool. It does not explicitly contrast itself with get_price_history or get_company_profile, so it stops short of a 5.

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 and no named alternative among the many siblings (get_price_history, get_company_profile, get_analyst_consensus). The 'up to 10 tickers' limit and US-only scope hint at appropriate use but never say when this tool should be chosen over its neighbors.

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

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

Annotations already declare readOnly, idempotent, non-destructive, so safety is covered. The description adds real behavioral context beyond that, notably that portfolio always lists every new/added/reduced position and that the consensus views aggregate across all investors.

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

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

Two dense, well-structured sentences that front-load the resource and then enumerate view semantics via semicolons. Efficient and readable, though the second sentence is fairly packed.

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, the description carries return-value burden but adequately conveys the semantics of each view for correct invocation. The structural format of returns per view is only implied, leaving a minor gap for a 7-view 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 coverage is high (80%), so the baseline is 3, but the description adds meaning by explaining what each view enum value returns and noting the min_portfolio_pct default of 0.5, which the schema does not spell out.

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 resource (latest SEC 13F holdings of ~80 tracked investors) with named examples (Buffett, Ackman, Tepper, Klarman), which is clearly distinct from siblings like get_insider_trades or get_sec_events. It's clear what the tool does, though it doesn't explicitly name a sibling to differentiate from.

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?

Maps each view value to a clear use case (holders = who owns symbol; portfolio = holdings of investor; list = tracked investors; consensus views = aggregated signals), effectively routing the agent to the right mode. It lacks explicit when-not guidance or pointers to sibling tools for overlapping needs.

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