Flicker

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

No annotations are provided, so the description must fully disclose behavior. It mentions it adds to a 'watchlist' and accepts identifiers, but fails to state whether the operation is idempotent (e.g., adding an already favorited asset), what happens on success/failure, or if authentication is required. This is insufficient for a write operation.

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

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

The description is two sentences long, front-loaded with the purpose, and provides an example of acceptable inputs. It is concise but could be slightly more compact.

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?

The tool has a simple interface (one required parameter, no output schema), so the description covers the basics. However, it lacks information about error conditions, rate limits, or idempotency, which would make it 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 coverage is 100% with a single parameter described in both the schema and description. The description adds minimal extra value beyond the schema by clarifying that 'asset_id' can be either a coin/stock id or symbol, but this is also stated in the schema. 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 states 'Add an asset to the user's watchlist,' which specifies the verb (add), resource (asset), and target (watchlist). This distinguishes it from siblings like 'remove_favorite_asset' and 'get_favorites' which are the complement operations.

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 does not provide any guidance on when to use this tool versus alternatives like 'search_assets' or 'get_favorites' before adding. There is no mention of prerequisites, such as needing to have a user account or being logged in.

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 full burden for behavioral disclosure. It discloses that it requires a push device, counts against a plan limit, and only creates price alerts. However, it does not mention idempotency (can it create duplicate alerts?), error behavior (what happens if limit exceeded or device missing?), or whether the alert is created synchronously. It also omits any side effects beyond the alert creation itself. While it provides some relevant behavioral context, significant gaps remain.

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 consists of three sentences, each serving a distinct purpose: first states the core action, second adds prerequisites and limitations, third clarifies usage scope. It is front-loaded with the primary purpose and contains no redundant or filler content. Every sentence earns its place, maximizing 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?

The tool has 3 parameters, no output schema, and no annotations. The description covers the purpose, prerequisites, plan limits, and exclusivity to price alerts. However, it does not describe the expected return value (e.g., alert ID, success message) or any post-creation behavior (e.g., immediate activation, delay). Given that the output schema is absent, the description should clarify what the agent can expect after invocation. This omission limits completeness.

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% (all three parameters have descriptions in the schema). The tool description does not add any additional semantics beyond the schema: it doesn't explain units for 'target', validate allowed values for 'direction' (despite being a free-form string with no enum), or clarify the format of 'asset_id'. Given high schema coverage, the baseline is 3, and the description provides no extra parameter-level guidance.

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 ('Create a price alert') and the resource ('price alert') with a concise explanation of what it does ('notify the user when an asset's price goes above or below a target'). It explicitly distinguishes from sibling tools by stating that only price alerts can be created via this tool, and other alert types require the app, which differentiates it effectively from any potential alert creation tools among 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?

The description provides explicit guidance on when to use the tool (for price alerts) and when not to (other alert types like RSI, breakout, smart zones) with a clear alternative ('require the app'). It also mentions prerequisites (active push-notification device) and constraints (free-plan alert limit of 10, unlimited on Pro), giving clear context for appropriate invocation.

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

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

With no annotations, the description must fully convey behavioral traits. It states the action 'Delete' (destructive) but omits consequences, reversibility, authentication needs, rate limits, or any return value. The reference to get_alerts adds minimal 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 description is extremely concise (one sentence, 9 words). It is front-loaded but may be too terse, lacking details that could aid the agent without being verbose.

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 delete tool with one parameter, the description covers the basic purpose and parameter source. However, it lacks guidance on output, success/failure behavior, and prerequisites, making it minimally adequate.

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 repeats the parameter's source ('from get_alerts') which is already in the schema, adding no new semantic value beyond that.

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 'Delete' and the resource 'an alert by id', specifying the source of the id from 'get_alerts'. This distinguishes it from other tools like create_price_alert or get_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?

The description implies that the alert id comes from get_alerts, suggesting a prior call, but does not explicitly state when to use this tool vs. alternatives like remove_favorite_asset or under what conditions deletion is appropriate.

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 fully disclose behavioral traits. It clearly conveys that this is a non-destructive edit affecting only notes and visibility, and explicitly states that trading/risk parameters are unchanged. This adds valuable information beyond the input schema. However, it does not mention required permissions, error conditions (e.g., position not found or not owned), or whether changes are immediately persisted/reversible.

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

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

The description is two sentences long, contains zero redundant words, and efficiently conveys the tool's purpose and a key behavioral constraint. Every sentence 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 simple 3-parameter tool with no output schema, the description covers the core functionality well. It states what is edited and what is not. Minor gaps: it does not describe the return value (e.g., whether the updated position object is returned) or mention that the position_id must reference an existing, owned position. These are not critical but would improve completeness.

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 baseline is 3. The description mentions the two editable parameters ('notes and/or visibility') but adds no semantic detail beyond what the schema already provides for each parameter. It does not clarify default behavior (e.g., what 'omit to leave unchanged' means in practice) or provide usage examples.

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 'Edit' and the resource 'a position,' specifying the exact fields affected ('notes and/or its visibility on the user's shareable profile'). It also includes a clarifying negation ('Does not change any trading/risk parameters'), which is especially valuable given the presence of sibling tools like position_analysis and get_positions that might be confused with editing operations.

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 implicit usage context by stating what the tool does and does not change, but it does not explicitly guide the agent on when to use it versus alternatives. For example, it does not name a sibling tool for changing trading/risk parameters (if one exists) or mention prerequisites like owning the position. The guidance is adequate but not explicit.

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 burden of behavioral disclosure. The description indicates this is a read-only retrieval of account info with no destructive side effects. For a zero-parameter tool that just returns data, this level of transparency is adequate, though it could mention that it returns static info that changes infrequently.

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, efficient sentence that conveys the tool's purpose and the exact data returned. Every word serves a purpose with no redundancy or filler.

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

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

The tool has zero parameters, no output schema, and is simple in scope. The description covers what the tool returns and its function completely. No additional context is needed for correct invocation or understanding.

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 description coverage is 100%, so no additional parameter documentation is needed. The description provides no param info, but given the absence of parameters, a baseline of 4 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 states the tool retrieves the user's basic account info and explicitly lists the specific fields returned: email, status, member-since date, and subscription plan. This distinguishes it from sibling tools like get_portfolio_summary or get_balances, which have different scopes.

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 clearly defines what the tool does but does not explicitly state when to use it versus alternatives or when not to use it. However, for a tool with zero parameters that returns basic account info, the use case is inherently obvious and no sibling tool overlaps with this specific purpose, so the implicit guidance is sufficient.

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 states it gets alerts and allowance count, which implies a read-only operation, but does not disclose any authentication prerequisites, data freshness, or whether the response includes both active and inactive alerts. Minimal transparency beyond the basic action.

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, focused sentence. It front-loads the main action ('Get the user's configured alerts') and appends the allowance detail efficiently. 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 parameterless getter tool with no output schema, the description is fairly complete: it names the content (alerts with examples) and plan limit. However, it omits whether results are paginated, ordered, or filtered by status. Slight gap in completeness.

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 zero parameters, so schema description coverage is 100% (no parameters to describe). The description adds value by explaining what data is returned (alerts of various types plus plan allowance), which is beyond the empty 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 clearly states it retrieves the user's configured alerts (listing specific types like price, RSI, breakout, smart zones) and also reports the plan allowance count. This distinguishes it from sibling tools like create_price_alert and delete_alert.

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 on when to use this tool versus alternatives. For a read operation, it would be helpful to mention that for modifying alerts one should use create_price_alert or delete_alert. The description lacks any usage context.

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 disclosure burden. It discloses that some timeframes require Pro, but does not mention destructive behavior (it is read-only), rate limits, or error handling (e.g., invalid asset_id). It partially compensates by listing the analysis depth, but lacks explicit safety or mutability statements.

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 dense sentence that efficiently conveys the tool's scope and key constraint (Pro limitation). It is front-loaded with the main purpose. However, the long list of indicators could be structured (e.g., bullet points) for readability without losing conciseness.

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

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

Given the tool's complexity (many indicators, AI summary) and no output schema, the description covers the main output categories (market context, technical indicators, support/resistance, breakout score, fear & greed, trading zones, AI summary). It also mentions the Pro requirement. Missing are error conditions, return format, or behavior when data is unavailable, but the listed components provide sufficient completeness for most usage.

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% (neither parameter described in schema). The description adds meaning for 'timeframe' by noting free vs. Pro tiers, but does not explain 'asset_id' (expected format, e.g., ticker or symbol). With 0% coverage, the description must fully compensate; it only partially does so, leaving a gap for the required 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 is highly specific: 'Get comprehensive market analysis for an asset' followed by a detailed enumeration of components (market context, technical indicators, support/resistance, etc.). It clearly distinguishes from sibling tools like 'get_asset_price' (simple price) or 'get_trading_signals' (likely different scope), with a precise verb+resource combination.

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 clear usage context: 'Timeframe 1h is free; 4h/1d/1w require Pro.' This tells the agent when to use specific parameters based on subscription. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'use get_asset_price for simple price queries'), nor does it mention any prerequisites like required authentication beyond the implicit Pro mention.

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 takes on the burden of behavioral transparency. It explains that market_type filters for spot/derivatives, and that derivatives return additional data (funding rate, open interest). This clarifies the tool's behavior well, though it doesn't mention potential side effects or rate limits.

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

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

Two concise sentences that front-load the core purpose and then clarify the optional parameter. No wasted words or redundant information.

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

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

Given there is no output schema and only 50% parameter schema coverage, the description covers the essential behavior without leaving major gaps. It explains the key parameter behavior and return data expectations. It could mention pagination or sorting, but for a straightforward list tool this is sufficient.

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

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

The schema description covers market_type ('spot or derivatives. Omit to return both'), but the description adds value by explaining that 'Derivatives include funding rate and open interest', which is beyond what the schema says. For asset_id, the description only states it's required, but that's clear from the schema. Overall, the description adds meaning to market_type.

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 specific verb 'Get' and resource 'markets (tickers) for an asset across exchanges', clearly distinguishing it from siblings like get_asset_price or get_funding_rates. The note about including derivatives data sets it apart from spot-only 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?

The description implies usage context (fetch markets for an asset) but provides no guidance on when to use this versus sibling tools like get_asset_price or get_exchange_detail. There are no exclusions or prerequisites 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 bears the full burden. It correctly indicates a read-only operation ("get") and enumerates returned data fields. It does not mention authentication, rate limits, or data freshness, but the scope is limited and the description is honest. No contradictions exist.

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

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

Two sentences delivering purpose and input format with no fluff. Front-loaded with the main action and specific data points. Every word earns its place.

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

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

Given the single parameter and no output schema, the description provides a sufficient list of returned fields. It could clarify '24h range' (likely high/low) and 'volume' (which currency?), but overall covers the tool's capabilities adequately.

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 baseline is 3. The description repeats the same examples as the schema (bitcoin, AAPL, btc) without adding semantic nuance like acceptable id formats or case sensitivity. No additional value beyond 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 clearly states it retrieves price, 24h range, price changes (1h, 24h, 7d), and volume for a specific asset. It specifies how to identify the asset via id or symbol. This distinguishes it from sibling tools like get_asset_analysis (deeper analysis) or get_asset_markets (market pairs).

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 for quick price data but does not explicitly state when to use this tool versus alternatives like get_asset_analysis or get_market_overview. No exclusion criteria or context boundaries are provided.

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

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

No annotations are provided, so description must cover behavioral traits. It names the signal type and factors, but does not disclose mutation behavior (read-only? it's a query, likely safe), rate limits, authentication needs, or what happens on invalid asset_id. For a data retrieval tool, lacking a read-only hint is a notable gap.

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

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

Two sentences, front-loaded with the core purpose. The first sentence covers what and how, second covers important constraint. 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?

Given no output schema, the description hints at return structure (signal, confidence, factors) but is vague. For two parameters with no enums, it adequately covers asset_id and timeframe, but lacks return details and behavioral flags that would help the agent determine if this is the right 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 0%, yet description adds meaning by explaining asset_id implicitly (the asset to get a signal for) and timeframe with free/Pro distinction. However, it does not specify format or constraints for asset_id or enumerate valid timeframe values beyond '1h'. Baseline 3 is appropriate as it adds value over empty schema but doesn't fully 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?

Description starts with 'Get a Buy/Hold/Sell signal for an asset' – clear verb+resource. It distinguishes itself from sibling tools like get_market_sentiment or get_trading_signals by naming the signal output and mentioning weighted factors, though it could more explicitly differentiate from get_trading_signals.

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 timeframe constraint ('1h is free; other timeframes require Pro') implies when to consider a paid feature, but there is no explicit when-to-use vs alternatives statement. No mention of prerequisites (e.g., asset_id must be valid) or when not to use this tool over related tools like get_market_sentiment.

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

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

No annotations are provided, so the description must disclose behavioral traits. It states the tool returns 'total/available/frozen USD, per-asset amounts and each asset's share,' implying a read-only retrieval with no side effects. The description does not clarify whether balances are cached, if there are rate limits, or the freshness of the data. For a data-fetching tool, this provides reasonable transparency but leaves gaps about data latency and potential API costs.

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 efficiently conveys what the tool does, the scope (across connected exchanges), and the specific data returned (total/available/frozen USD, per-asset amounts, asset share). No filler words or unnecessary details; every element adds value.

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

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

Given the tool has one optional parameter, no output schema, and is a simple balance retrieval operation, the description sufficiently covers the expected behavior and return contents. However, it does not address potential edge cases (e.g., what happens if user has no connections, or if a connection fails). This is a minor gap, but overall the description is complete for typical usage scenarios.

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

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

Schema coverage is 100% with one parameter (user_connection_id) already described in the schema. The description does not mention the parameter or its usage, relying entirely on the schema. With only one parameter and full schema coverage, the description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.

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

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

The description uses a specific verb ('Get') and resource ('spot/wallet balances across connected exchanges') with clear scope boundaries (total/available/frozen USD, per-asset amounts, asset share). Among siblings like get_account_info, get_portfolio_summary, and get_positions, this distinctively covers per-exchange balances with portfolio share, not account metadata or aggregated portfolio-level summary.

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

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

The description implies this is the tool to retrieve current balance details across exchanges, but does not explicitly say when to use it versus alternatives like get_portfolio_summary or get_account_info. No exclusions or when-not-to-use guidance is provided. The optional parameter hint ('Restrict to a specific exchange connection') is in the schema, not the description, but the description's omission of it weakens the guidance for filtering scenarios.

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 burden. It describes the return fields (status, sync time, icon, URLs) but does not disclose behavioral traits like authentication requirements, rate limits, or error handling (e.g., what happens if no connections exist). The description is adequate for a simple read operation but lacks depth.

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

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

A single sentence that conveys all necessary information without any wasted words: verb, resource, and included fields. It is front-loaded and 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?

Given no parameters, no output schema, and no annotations, the description is nearly complete. It lists all key return fields. However, it could mention the format (list of objects) or pagination, but the simplicity of the tool makes this acceptable.

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

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

The tool has zero parameters, so schema coverage is 100% trivially. The description adds value by listing the data returned (status, sync time, icon, URLs), which supplements the empty schema. Per guidelines, baseline for 0 params is 4, and the description meets this.

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 'Get' and the resource 'all exchange connections for the user', and lists specific included fields (status, sync time, icon, URLs). This distinguishes it from siblings like 'get_exchange_detail' (single exchange) and 'list_exchanges' (available exchanges, not user connections).

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 tool versus alternatives such as 'get_exchange_detail' or 'list_exchanges'. The description only explains what it returns, not the context or exclusion criteria.

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

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

No annotations are provided, so the description carries the full burden. It uses the verb 'Get' implying a read-only operation, and lists the data returned. However, it does not explicitly confirm read-only behavior, authentication needs, or any other behavioral traits that an agent might need to know, such as rate limits or error conditions.

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

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

The description is a single, front-loaded sentence that first states the purpose and then lists the specific data returned. It is concise and without unnecessary words, though it could optionally be broken into a bulleted list for reduced cognitive load.

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

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

Given the simple tool with one parameter and no output schema, the description sufficiently explains what the tool returns and its basic purpose. It does not mention prerequisites like valid exchange IDs, but that is implied by the parameter. It is complete enough for an agent to understand when to use it.

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 a clear description for the single parameter (exchange_id). The tool description adds no additional information about the parameter beyond what the schema provides, so the baseline score of 3 is appropriate.

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

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

The description clearly states the verb 'Get detail' and specifies the resource 'exchange'. It enumerates the specific data points returned (volume breakdown, spot/futures pair counts, futures open interest, top futures pairs by volume), which distinguishes it from sibling tools like list_exchanges that likely provide summary information.

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 that this tool is for obtaining detailed metrics about a specific exchange, and the sibling list_exchanges suggests a complementary tool for overviews. However, it does not explicitly state when to use this tool versus alternatives, nor provide exclusion criteria (e.g., 'use for detailed analysis, not for listing all exchanges').

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 burden for behavioral transparency. It adequately describes the output: current prices and performance metrics (1h, 24h, 7d). However, it does not disclose other behavioral traits such as whether the tool fetches real-time or cached data, whether authentication is required (implied by 'the user's watchlist'), or if there are any side effects (none expected for a 'get' but not explicitly stated). The description is reasonable but could be more explicit about the data source and latency.

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 packs all necessary information: what it retrieves (watchlist of favorite assets), the scope (coins, stocks, currencies/FX), and the data fields (current prices and performance metrics). Every part is essential and there is no redundant or extraneous text. It is front-loaded with the main action ('Get the user's watchlist') and quickly details the specifics.

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

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

Given the tool has no input parameters and an output schema is not present, the description does a reasonable job of explaining what the tool returns (current prices and performance data). It does not describe the output format or structure (e.g., whether results are sorted, paginated, or limited), but the performance metrics mentioned (1h/24h/7d) provide useful context for the agent. The completeness is high for a simple read operation, but could be slightly improved by noting the expected size or ordering.

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 the schema description coverage is 100% (since there are no parameters to document). The baseline score for 0 parameters is 4, and the description does not add any parameter-related meaning because there are none. The description is clear and concise, and no additional parameter guidance is needed.

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 what the tool does: it retrieves the user's watchlist of favorite assets. It specifies the exact resource ('watchlist of favorite assets') and the verb ('Get'), and distinguishes itself from sibling tools by mentioning the types of assets included (coins, stocks, currencies/FX) and the data provided (current prices and 1h/24h/7d performance).

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 does not explicitly state when to use this tool versus alternatives, but given it has no parameters (a simple retrieval) and is named 'get_favorites', its purpose is self-evident. Sibling tools like 'add_favorite_asset' and 'remove_favorite_asset' imply an alternative for modifying the watchlist, but no direct comparison is made. The description is clear enough that an agent would know to use this when the user wants to view their favorite assets, but it lacks explicit exclusions or when-not-to-use guidance.

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

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

No annotations are provided, so the description must disclose behavioral traits. It states the tool returns assets ranked by score with optional filters, but does not mention whether results are sorted, paginated (beyond limit), or if any authentication is needed. The description is adequate but not comprehensive.

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, front-loaded sentence that clearly states the core function and key optional filters. No waste.

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 4 optional parameters with full schema coverage and no output schema, the description is complete enough for basic usage. It names all filterable fields, though it could slightly expand on the ranking order (e.g., descending/ascending).

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 baseline is 3. The description adds a brief mention of three filters (zone, min_volume, asset_class) in a single sentence, but does not provide additional semantic context beyond what the schema already offers.

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

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

The description clearly states the tool retrieves a leaderboard of assets ranked by per-asset fear/greed score, and mentions specific filter parameters (zone, min_volume, asset_class). This distinguishes it from siblings like get_market_sentiment or get_asset_signal.

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 for fetching sorted sentiment data, and lists optional filters. It does not compare to alternatives or state when not to use it, leaving the purpose clear but lacking explicit guidance versus siblings.

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

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

No annotations are provided, so the description must carry the full burden. It correctly describes what the tool returns ('funding rate, price, open interest and 24h volume per venue'), making it clear this is a read operation. It does not disclose any edge cases, data freshness, or exchange coverage limitations, but the core behavior is transparent for a generic data-fetching 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 two sentences long with zero wasted words. The first sentence states the core action and scope, and the second sentence lists the returned data fields. Every sentence serves a clear purpose.

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

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

The tool has only one optional parameter and no output schema, so the description is largely complete. It covers purpose, optional filtering, and return fields. It could be improved by noting that funding rates are specific to perpetual futures (implied but not explicit), and by mentioning a typical use case like comparing across exchanges, but overall it provides sufficient context 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% (the only parameter, coin_id, is fully documented in the schema). The description adds value by explicitly stating the parameter is optional ('optionally for a specific coin') and that omitting it gives a 'market-wide view,' which paraphrases the schema. Since the schema already does the heavy lifting, a 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 states the tool gets 'perpetual funding rates across exchanges, optionally for a specific coin,' which uses a specific verb ('Get'), identifies the resource ('funding rates'), and defines its scope ('across exchanges', optionally filtered by coin). It distinguishes itself from siblings like get_asset_price or get_market_overview by targeting the niche concept of perpetual funding rates.

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 explicitly notes the optional coin filter via 'optionally for a specific coin' and implies the broad use case (market-wide vs. per-coin). However, it does not mention when not to use this tool or suggest alternatives (e.g., using get_asset_markets for spot markets), but the context is clear enough for most agents.

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 disclose behavior. It lists returned data (e.g., 24h deltas, dominance) but does not mention freshness, real-time vs. lag, rate limits, or any side effects. The description is adequate for a zero-parameter read tool but lacks deeper behavioral 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 description is a single sentence that front-loads the core action ('Get a global market overview') and then efficiently lists the covered metrics. Every phrase adds value; 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?

Given the tool has no parameters and no output schema, the description adequately lists all returned data components. It is mostly complete for a simple overview, though it could mention the return format (e.g., JSON structure) for perfect clarity.

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 are no parameters, so schema coverage is 100%. The description correctly avoids redundant parameter info. Baseline for 0 parameters is 4, and the description adds no unnecessary detail.

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 'Get a global market overview' and enumerates specific data points (market cap, volume, dominance, fear & greed index, AI insight). It distinguishes itself from sibling tools like get_fear_greed_leaderboard and get_market_sentiment by being a comprehensive aggregate.

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 a broad market snapshot but does not explicitly state when to use this versus alternatives. No 'when not to use' or direct sibling references are provided, leaving the agent to infer from the content 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 are provided, so the description carries the full burden of behavioral disclosure. The description only lists return data and does not mention read-only nature, authentication requirements, rate limits, data freshness, or any side effects. For a 'get' tool, the agent needs to know it is safe to call without side effects, but this is not stated.

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 efficient sentence that front-loads the purpose and lists specific data points. It is concise with no wasted words. However, it could be more structured (e.g., bullet points for the list) and could separate the parameter description for clarity.

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?

The tool has no output schema, no annotations, and one parameter with no description. The description lists return data but does not specify the parameter format, behavioral traits, or any usage context. An agent would need additional information to correctly invoke the tool, especially regarding the 'asset_id' parameter and the nature of the output.

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 'asset_id' with 0% description coverage. The tool description says 'Get market sentiment for an asset' but does not clarify what the parameter expects (e.g., symbol, name, ID format). The description adds no meaning beyond the parameter name, leaving the agent to guess the format and allowed values.

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 'Get market sentiment' and the resource 'an asset', then enumerates specific data components (Fear & Greed index, breakdown, trend, historical percentile, signals, recommendation, breakout outlook). This is specific and distinguishes the tool from siblings like 'get_asset_analysis' or 'get_trading_signals', which cover different aspects of asset 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 description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, limitations, or scenarios where another tool would be more appropriate. The agent must infer usage solely from the tool name and listed components, which is insufficient for effective decision-making among 30+ sibling 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 full responsibility. It discloses return fields (source, summary, link), but does not mention rate limits, default sorting, error handling, or whether results are real-time. The read-only nature is only inferred from the verb 'Get'.

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

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

The description is a single, front-loaded sentence that states the purpose and output fields without any filler. Every word earns its place.

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

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

For a simple tool with one optional parameter and no output schema, the description conveys the essential output fields. It could note ordering or empty-result behavior, but the tool is straightforward enough for basic 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?

The schema fully documents the single optional parameter (limit) with type, default, range, and description. The tool description adds no parameter insight beyond what the schema already provides.

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

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

The description uses a specific verb ('Get') and resource ('latest cryptocurrency news headlines') clearly defining the tool's purpose. It is distinct from sibling tools like get_market_overview or get_market_sentiment, with no other news-specific tool.

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 when latest crypto news is needed. However, no explicit when-to-use vs alternatives is provided, and given the large sibling set, mentioning alternatives or exclusions would strengthen this dimension.

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 full burden. It discloses the tool reads preferences (get) and lists categories, but does not mention if any side effects or authentication requirements exist. Adequate for a simple read operation but not fully transparent.

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

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

The description is a single sentence that efficiently conveys the tool's purpose and key detail. Every word earns its place with no 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?

Given zero parameters, no output schema, and a simple read operation, the description is sufficiently complete. It would benefit from indicating that all preferences are returned (not just muted ones).

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% (no parameters), so baseline is 3. The description adds value by clarifying the content of the response (which categories are mentioned), earning an extra point.

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

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

The description clearly states the tool gets the user's notification preferences and lists example categories (price_alerts, marketing, etc.), making the purpose specific and distinguishable from sibling tools like update_notification_preferences.

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 when the agent needs to read notification preferences, but provides no guidance on when not to use it or alternatives. With over 30 sibling tools, explicit exclusions or context would be helpful.

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 burden. It explains the aggregated output (size-weighted avg price, summed size/fee/pnl) and that it is not raw fills. However, it does not disclose pagination behavior, read-only nature, or potential empty results. Given the context, it is fairly transparent but could be more explicit.

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

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

The description is two sentences, front-loaded with the purpose and output format, followed by usage guidance. Every word earns its place; no fluff 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?

No output schema is provided, so the description must explain the return value. It does so by describing the aggregated fields. It also distinguishes from a sibling. However, it does not mention pagination details or edge cases. Given the 9 parameters, the description is reasonably 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 coverage is 100% with each parameter well-described. The tool description does not add additional parameter semantics beyond what the schema already provides. Baseline is 3, and no extra value is added here.

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

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

The description clearly states the tool retrieves 'rolled-up order history' grouped by orders with specific aggregated fields (size-weighted avg price, summed size/fee/pnl). It explicitly contrasts with raw fills, making the purpose distinct from siblings like get_trades.

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 explicit guidance: 'Use this instead of get_trades when the user wants 'trades'/'orders' as a whole, not individual fills.' This directly tells the agent when to choose this tool over an alternative.

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 burden. It discloses the eligibility condition, what is returned when eligible (positions, PnL, track record), and implies eligibility status is returned. It does not mention the response for ineligible users, but the description is otherwise transparent about the tool's 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, well-structured sentence that front-loads the purpose ('Get the Pilot bot's live spectate view') and efficiently details eligibility and return content. Every phrase adds value 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?

Given no parameters, no output schema, and no annotations, the description provides a complete picture: it explains the tool's purpose, prerequisites, and output components. It could be slightly more explicit about the response when not eligible, but the description is sufficient for an agent to understand and invoke 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?

There are zero parameters, so the schema provides complete coverage. The description adds meaning beyond the schema by explaining the context and output based on eligibility. Baseline 4 applies for zero parameters.

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 uses a specific verb ('Get') and resource ('Pilot bot's live spectate view'), clearly stating eligibility conditions and what is returned. It distinguishes from siblings like 'get_pilot_spectate_history' (history vs live) and 'get_positions' (pilot-specific vs general).

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 clear context for when to use this tool (live spectate view of the Pilot bot) and details eligibility prerequisites (affiliate-linked exchange connection with $10k trailing 30-day volume). It does not explicitly list alternatives or when not to use it, but the purpose is sufficiently clear.

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 full burden. It states this retrieves 'closed-trade history' (read operation) and is 'paginated,' which are useful behavioral clues. However, it does not disclose the return format, error conditions, or whether the operation is safe (read-only) beyond the implied nature of a history query.

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

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

The description is two short sentences, front-loading the core purpose. Every sentence adds value, 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?

Given the lack of output schema and annotations, the description omits critical details like the structure of returned trade history, pagination cursor behavior, and eligibility requirements. For a paginated endpoint with no output schema, more context is needed for the agent to interpret results 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 50%: only 'limit' has a description (page size defaults). The description does not add any parameter semantics – it does not explain 'offset,' nor does it clarify the data type or behavior of the parameters beyond what schema provides. The agent lacks clarity on how to paginate effectively.

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

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

The description clearly states the tool retrieves the Pilot bot's closed-trade history and that it is paginated. It also references a sibling tool (get_pilot_spectate) for eligibility context, which helps differentiate their purposes.

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 mentions an 'eligibility gate' tied to get_pilot_spectate, but provides no explicit guidance on when to use this tool versus alternatives, nor any prerequisites or conditions for use. The agent is left to infer usage context from the sibling reference.

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 full responsibility for behavioral disclosure. The verb 'Get' suggests a read-only operation, but the description does not explicitly confirm safety, authentication needs, or rate limits. It adds no behavioral details beyond the listed return fields.

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 single sentence is front-loaded with the action and resource, then efficiently lists the summary components. Every word contributes to understanding what the tool does, with zero 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 tool with no parameters and no output schema, the description fully explains the return content (total value, PnL, exposure, margin usage, top positions). It covers all key aspects a user would need to decide if this tool suits their need for a portfolio overview.

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 0 parameters, so the baseline is 4 per rubric. The description adds no parameter-specific meaning (none needed). It does not explain any implicit defaults or constraints, but that is acceptable given the absence of parameters.

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 uses a specific verb ('Get') and resource ('high-level summary of the user's entire portfolio') and enumerates concrete metrics it returns. This clearly distinguishes it from sibling tools like get_account_info (account details) or get_positions (individual positions).

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 implicitly indicates when to use (for a portfolio overview) but does not explicitly state when not to use the tool or recommend alternatives. Given many sibling tools cover related areas (get_balances, get_positions, get_account_info), explicit guidance would improve decision-making.

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 burden. It correctly implies this is a read operation ("Get") and discloses return detail (entry/current price, margin, leverage, etc.), which is helpful. However, it does not disclose whether filters are mandatory or optional, rate limits, or response size behavior when no filters are applied.

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, front-loaded with the core purpose, and then provides param details. It is efficient but could be slightly more concise by omitting the full list of return fields (which could be documented elsewhere). 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?

Given 4 optional parameters, sibling tools with overlapping domains, and no output schema, the description covers the return structure well (portfolio summary + per-position detail) and param filtering guidance. It lacks guidance on visible_only, but overall is complete enough 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?

Schema description coverage is only 25% (only asset_id has a description). The description compensates by explaining the filter semantics for position_type (spot/futures), direction (long/short), and asset_id with examples. It adds value for the three parameters that lack schema descriptions, but does not address visible_only.

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

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

The description clearly states the tool retrieves trading positions with optional filtering by type, direction, and asset. It distinguishes itself from sibling tools like get_orders, get_trades, and get_portfolio_summary by specifying it returns per-position detail including margin, leverage, PnL, and funding rate — a distinct resource and granularity.

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 for fetching current positions with filters but does not explicitly say when to use this versus alternatives like get_portfolio_summary (which returns only summary) or get_orders/get_trades (which are historical). No when-not-to-use or exclusion guidance is provided.

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

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

No annotations are provided, so the description carries the burden. It discloses the time horizon (last 24 hours) and the three categories returned, but omits details like data freshness, rate limits, or what defines a breakout candidate. It is adequate but not rich.

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

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

The description is two sentences: the first states the core output, the second adds the optional parameter. Every sentence is necessary and front-loaded. 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 simple tool with one optional parameter and no output schema, the description provides the essential information: what data is returned (three categories, each top 5) and the time window. It could mention the return format or sorting, but overall it is fairly 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 coverage is 100%, with the schema already describing the asset_class parameter well. The description restates the parameter and its options, adding no new meaning beyond quick reference. Baseline 3 is appropriate.

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

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

The description clearly states the tool retrieves a market screener with top 5 gainers, top 5 losers, and top 5 breakout candidates in the last 24 hours. The verb 'Get' and specific resource details make the purpose unambiguous and distinct from siblings like get_top_movers or get_market_overview.

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 explicit guidance on when to use this tool versus alternatives such as get_top_movers or get_market_overview. The description implies it is for a quick snapshot of best/worst performers and breakout candidates, but does not state exclusions or preference conditions.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the output (gainers, losers, volume) and the optional filter. It does not mention whether the operation is read-only, any authentication or rate limit implications, or whether the results are cached or real-time. The description is minimal on 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 two sentences: the first states the core purpose, the second details the optional parameter. Every sentence earns its place with no redundancy or fluff. It is front-loaded with the most important 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?

The tool is simple with one optional parameter and no output schema. The description explains the scope (top movers, 24h) and filter. However, it does not describe the return format or structure of the results, which an agent would need to interpret the output. Given the simplicity, it is minimally adequate but not 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?

The input schema has 100% coverage for the single parameter. The description adds 'optional' and 'default all', which roughly mirrors the schema's description and default null. It does not provide additional meaning beyond what the schema already conveys, so baseline 3 is appropriate.

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

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

The description clearly states the verb 'get' and the resource 'top market movers', specifying exactly what is included (biggest gainers, losers, highest-volume assets) and the time frame (last 24 hours). This distinguishes it from sibling tools like get_market_overview or get_asset_analysis.

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 explicit guidance is provided on when to use this tool versus alternatives. It describes what it does but does not mention when not to use it or suggest sibling tools for different contexts (e.g., get_market_overview for broader market data). The description implies usage for market movers but lacks explicit differentiation.

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 partially discloses behavior by listing return fields and filtering options. However, it does not address pagination behavior, ordering of results, rate limits, or state that the operation is read-only. The schema covers parameters but the description adds no behavioral context beyond what is inferred.

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

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

The description is two sentences (22 words) and front-loaded with the main purpose and scope. Every word earns its place; no extraneous information. Ideal conciseness.

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 9 optional parameters, no output schema, and no annotations, the description is moderately complete. It lists return fields (price, size, value, fees, PnL) which is helpful, but it omits crucial context like pagination behavior, ordering, and rate limits. The description does not fully compensate for the lack of 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 description coverage is 100%, so baseline is 3. The description mentions 'filtering by connection, pair and side' but adds no additional meaning beyond the schema's detailed parameter descriptions (including formats, defaults, deprecated aliases). No new semantics are provided.

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

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

The description clearly states the action ('Get'), the resource ('user's recent trade history across connected exchanges'), and optional filtering dimensions. It lists specific return fields (price, size, value, fees, PnL), which distinguishes it from sibling tools like get_orders or get_positions.

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 for retrieving trade fills with filtering but provides no explicit guidance on when to use this tool vs alternatives (e.g., get_orders, get_balances). It does not mention when not to use it or suggest sibling tools for different contexts.

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 burden. It discloses the free/Pro pricing model for filters, but does not describe the response format, pagination, rate limits, or error behavior. For a tool with 11 parameters, this is a moderate disclosure.

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 concise: two sentences covering purpose, required parameter, optional filters, and pricing. Every sentence earns its place with no 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?

Given the complexity (11 parameters, no output schema, no annotations), the description adequately covers the filtering options and pricing. However, it lacks any mention of the return format, pagination, or how to interpret results, which is a gap for a signal 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?

Schema description coverage is 100%, so the schema already documents each parameter. The description adds value by grouping filters and summarizing the free/Pro distinction, but it does not introduce new semantic details beyond what is in 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 clearly states the tool gets trading signals across the market and lists signal types and optional filters. It distinguishes the tool's broad scope from siblings like get_asset_signal (which is per asset), but does not explicitly differentiate in the text.

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 for retrieving a filtered list of trading signals, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., get_asset_signal, get_market_overview). It mentions Pro vs free limitations, which helps with filter selection, but not tool selection.

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 fill the gap. It does disclose the sorting behavior (by volume) and the data aggregation (volume split, asset counts). However, it does not mention whether this is a read-only operation, rate limits, or any potential caching behavior, which would be useful for behavioral expectations.

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

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

A single sentence that efficiently communicates the purpose, output fields, and ordering. Every part of the sentence adds value—there is no wasted text 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?

Given the tool has no parameters and no output schema, the description is nearly complete for an agent to understand what it does and what it returns. It covers the core purpose and data structure. A minor gap is the lack of clarification about the scope (e.g., whether this includes all exchanges the API supports or just user-visible ones), but overall it is sufficient.

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

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

The tool has zero parameters, and the schema coverage is 100% (no parameters to document). The description adds no parameter details, but none are needed. The baseline for zero parameters is 4, and the description adequately describes what the tool does without needing to reference parameters.

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 specifies the verb 'Get', the resource 'all supported exchanges', and the specific data fields included (trading volume split by total/spot/futures, unique asset counts) with a defined ordering (sorted by volume). This distinguishes it well from siblings like get_exchange_detail (which focuses on a single exchange) and other data-fetching 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?

The description implies this is the go-to tool for a broad overview of exchanges, with clear return data (volume and asset counts). It does not explicitly state when NOT to use it or name alternative tools for narrower queries (e.g., get_exchange_detail), but the context is clear enough that an agent would use this for a comprehensive list rather than detailed single-exchange info.

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 clearly states that the tool is 'Descriptive only — it never recommends an action', which is a key behavioral trait. It also discloses the free vs Pro timeframe constraint. Missing details on error handling or output format, but the core behavioral nature is communicated.

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 relatively short (3 sentences) and front-loads the main purpose. The first sentence efficiently lists the aspects of analysis, though it is a dense run-on. No extraneous information, but readability could be improved.

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?

The description covers the input parameters and the purpose, listing the aspects assessed. However, with no output schema, it fails to specify the return format or error conditions. The agent is left to infer the output from the listed aspects, which is a gap for completeness.

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

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

Schema coverage is 100% with detailed descriptions for both parameters. The description adds minimal extra context, such as that the position is open and that analysis is against 'Flicker's published analysis zones'. This is helpful but not substantial enough to raise above the baseline of 3.

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

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

The description clearly states the verb 'assess' and the resource 'one of the user's open positions', and lists specific analysis aspects. It distinguishes from siblings like `get_positions` by focusing on in-depth analysis of a single position rather than listing.

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 clear context: it is descriptive-only and never recommends an action, and notes the Pro requirement for timeframes. However, it does not explicitly compare with alternatives (e.g., `get_asset_analysis`) or state when not to use it.

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?

The description reveals no behavioral traits beyond the obvious removal action. With no annotations provided, the description carries the full burden, but it does not disclose side effects, permissions, reversibility, or return behavior. The tool is simple, so a 3 is adequate.

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

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

Two sentences, front-loaded with the action, minimal waste. Every word earns its place.

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

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

Given the tool has only one parameter, no output schema, and no nested objects, the description is largely complete. It could note the removal is specific to the authenticated user's watchlist, but the word 'user's' already implies that.

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 description does not add semantic value beyond what the schema already provides (both mention asset_id can be id or symbol). A baseline of 3 is appropriate since the schema already covers the parameter meaning fully.

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

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

The description clearly states the action ('Remove'), the target resource ('asset from the user's watchlist'), and acceptable input formats ('coin/stock id or symbol'). This distinguishes it from the sibling 'add_favorite_asset' and other unrelated 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?

The description implies use when the user wants to unfavorite an asset, but does not explicitly state when to use this tool versus alternatives (e.g., when to use delete_alert instead). No guidance on prerequisites or when not to 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?

With no annotations provided, the description carries the full burden for behavioral disclosure. It states the tool returns matching assets with prices and performance, implying a read-only operation. However, it does not disclose pagination, rate limits, or what happens with no results. The information is adequate but not detailed.

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

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

The description is two sentences long, front-loaded with the core action, and every sentence provides value. There is no wasted 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?

Given the tool's moderate complexity (3 parameters, 1 required, no output schema), the description covers the main purpose and key parameters. It lacks mention of the `limit` parameter and does not describe the return format, but it is sufficient for a straightforward search 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 description adds meaning beyond the input schema by explaining that the `query` parameter searches by name or symbol (the schema has no description for `query`). It also restates the `asset_class` parameter's allowed values. The `limit` parameter is not mentioned, but overall the description fills gaps in the schema coverage (33%).

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 'Search', the resource 'assets', and the scope 'across coins, stocks and currencies (FX)'. It also specifies what it returns ('matching assets with prices and performance'). This distinguishes it from sibling tools, none of which are search 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?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention conditions where it should not be used. There is no explicit context or exclusions provided.

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

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

No annotations are provided, so the description carries full burden. It clearly states this is a mutation tool (enable/disable) but does not disclose any side effects, authorization needs, or rate limits. However, the operation is simple and well-scoped, so the agent can infer basic behavioral traits.

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

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

The description is a single, front-loaded sentence with no wasted words. Every part ('enable or disable', 'one notification/email category', reference to sibling tool) serves a purpose.

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

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

With only 2 parameters, no output schema, and no annotations, the description adequately explains the tool's purpose and parameter usage. It could be slightly more complete by mentioning the tool's effect is immediate or that it only affects a single category, but the current depth is sufficient for a simple mutation 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 50%. The description adds value by clarifying the category parameter links to `get_notification_preferences`, but the schema already describes that. For the `disabled` parameter, the description implies its usage via 'enable or disable', adding implicit semantic meaning beyond the schema's bare `boolean` type. Baseline 3 is appropriate as the description partially compensates for low 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 states the action ('Enable or disable'), the resource ('one notification/email category'), and the scope ('for the user'). It also distinguishes itself from the sibling tool `get_notification_preferences` by referencing it as a source for valid category names.

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 explicitly tells the agent to use `get_notification_preferences` to find valid category names, providing clear guidance on prerequisite knowledge and when to use this tool in conjunction with its sibling.

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