AIsa Crypto Market Data

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

Annotations already declare destructiveHint=true and openWorldHint=true, so safety is covered. The description adds valuable behavior: independence of items (one failure doesn't cancel others) and per-call billing. These are not derivable from annotations and help the agent set 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?

Three short sentences with zero filler. The action and limit are front-loaded. The phrase 'tool-router's batch_use' is redundant since it restates the tool name, but it's a minor flaw. Overall it is concise and well-structured.

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 annotations covering destructive behavior and an output schema presumably describing results, the description covers the key operational aspects: concurrency limit, independence, and billing. It doesn't mention error reporting formats, but those likely live in the output schema. It is sufficiently complete for a batch 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 fully documents each parameter. The description adds no parameter-specific details. The calls parameter's description already explains the structure and batching context, so the baseline of 3 applies; the description doesn't need to compensate.

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

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

The description states a clear action (execute) and resource (operations) with a concrete limit (up to 20) and concurrency. It doesn't explicitly name the sibling 'use' for single operations, but the distinction is clear enough from the concurrency and limit. The redundancy of 'tool-router's batch_use' is minor.

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

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

The description gives no guidance on when to use this tool versus the sibling 'use' tool. The schema note about 'steps at the same execution_level of a plan go in one batch' is helpful, but it lives in the schema, not the description. The description only implies batching via concurrency but doesn't state when to choose it over the single-operation 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?

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond that: the approximate data volume ('Roughly 749'), the supported sort dimensions, and the performance/size comparison with the sibling tool. It doesn't mention defaults or pagination, but annotations lower the burden.

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

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

Three focused sentences: returns + fields, sorting usage, and sibling alternative. Every clause earns its place, and the key value proposition (which sectors are moving) is front-loaded.

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

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

With one optional parameter, existing output schema, and annotations covering the safety profile, the description is sufficient. It tells the agent what data comes back, how to sort, and when to use a better-suited alternative. Nothing required for correct invocation is missing.

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

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

The only parameter `order` is fully enumerated in the schema with self-explanatory enum values. With 0% schema description coverage, the description compensates by explaining the parameter's purpose: 'Sort with `order` by market cap, name or 24h market-cap change.' This maps directly to the enum options and adds meaning beyond bare names.

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

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

The description states exactly what the tool returns: 'Roughly 749 crypto categories with market data attached' and enumerates the fields. It also differentiates itself from the sibling by contrasting with 'get_coingecko_coins_categories_list' which returns a plain identifier list.

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?

Explicit usage guidance is present: 'Use it to see which sectors are moving' and a clear alternative for a different need: 'For the plain identifier list that the `category` filter expects, get_coingecko_coins_categories_list is smaller and faster.' This tells the agent exactly when to choose one tool over the other.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful behavioral context: it states the output is a flat identifier map and explicitly says it carries no market data at all, which clarifies what the tool does not return. This goes beyond the annotations.

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 with no wasted words. It front-loads the core definition ('flat identifier map'), then immediately explains its practical use and the alternative. Every sentence earns its place, and the structure is efficient.

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

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

For a simple list tool with no parameters and an output schema present, the description is fully adequate. It states what is returned, how to use it, what it does not include, and which sibling tool to use for related but different data. No critical information is missing for an agent to correctly invoke 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?

The tool has zero parameters and the input schema is empty, so there is nothing to document about parameters. The description adds value by explaining the output structure (category_id and name) and their purpose, which is relevant to using the result. With 0 params, the baseline is 4, and the description adequately covers the context.

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

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

The description clearly states the tool's function: it returns a flat identifier map of CoinGecko categories with `category_id` and `name`. It explicitly distinguishes itself from the sibling `get_coingecko_coins_categories` by noting it carries no market data, so an agent can tell them apart without inspecting schemas.

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

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

The description gives explicit usage guidance: use this tool to turn a theme into a category id for the `category` filter on `get_coingecko_coins_markets`, and use `get_coingecko_coins_categories` instead for market caps and leading coins. It clearly specifies when to use this tool versus the 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?

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond that by warning that the full payload is large and that `market_data`, `community_data`, `developer_data`, `tickers`, `sparkline`, and `localization` are heavy sections that should be left off unless needed. This is valuable operational transparency that the annotations do not provide.

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 longer than average but earns its length: it front-loads the primary return contents, then provides differentiation guidance and payload-size advice. It could be slightly tighter, but no sentence is filler and the structure flows logically from what-the-tool-returns to when-to-use-it.

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 complex read tool with an output schema, the description is complete enough: it covers the full scope of returned data, warns about payload size, suggests which flags to disable, and routes to the correct siblings. The existing output schema handles return-value structure, so the description does not need to restate that. No critical calling context appears missing.

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

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

Schema description coverage is low (14%), so the description carries a heavy burden. It identifies the boolean parameters as controlling heavy sections and advises disabling them unless needed, but it does not explain what each flag semantically includes (e.g., what `community_data` or `developer_data` contains). The `id` parameter's meaning is largely left to the schema, which already documents the coin ID and example. Overall, the description partially compensates but does not fully fill the gap left by the sparse 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 returns everything CoinGecko holds on a single coin selected by `id`, and enumerates the key sections (`description`, `links`, `image`, `categories`, `platforms`, `market_data`, etc.). It differentiates itself from sibling tools by naming alternatives for price tables and contract-address lookups, so an agent can identify it confidently.

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

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

It explicitly says 'Use it for a coin profile' and gives concrete routing guidance: for a price table across many coins use `get_coingecko_coins_markets`, and for lookup by contract address use `get_coingecko_token_data`. It also advises leaving heavy optional sections off unless needed, which is actionable usage 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so safety is covered. The description adds behavioral context by specifying the returned data structure (market_data, community_data, etc.) and the date format requirement, which goes beyond the schema. However, it doesn't discuss error handling or rate limits, but that's acceptable given the simplicity.

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, no filler. The first sentence defines the tool and its key constraint (date format), the second gives usage direction and alternatives. Well-structured and front-loaded.

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

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

Given the output schema exists, the description need not detail return fields exhaustively, but it still lists the main categories. It covers the required parameter, format, and usage distinction. It is complete for a read-only snapshot tool, leaving nothing essential for an agent to call it correctly.

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

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

Schema coverage is 67% (id and date have descriptions). The description reinforces the date format (dd-mm-yyyy) and that date is required, but this is redundant with the schema. It adds no new information about localization (which has a default). Thus it provides minimal additional value over 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 it provides a snapshot of one coin on a single calendar day, with a specific date format. It distinguishes itself from sibling tools by naming the continuous series alternatives, making its purpose unambiguous.

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

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

It explicitly instructs when to use this tool ('Use it for one fixed point in time') and directs to market_chart or market_chart_range for continuous data. This provides clear selection criteria among 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavior beyond annotations: output shape (three parallel arrays), timestamp unit (milliseconds), auto-granularity based on `days`, and the optional `interval` override. It does not mention rate limits or error cases, but those are not critical given the strong annotation coverage.

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

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

Four sentences with no filler. The most important output-shape and scope information is front-loaded, followed by sibling routing. Every sentence earns its place and the description is compact relative to the tool's complexity.

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?

Combined with a fully described input schema, rich annotations, and an output schema, the description provides everything an agent needs to call this tool correctly: scope, output structure, timestamp units, granularity behavior, and explicit alternatives. No critical call prerequisite or expected-return detail is missing.

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

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

Schema description coverage is 100%, so the input schema already documents every parameter. The description adds meaning beyond the schema by clarifying that `days` defines a trailing window, that granularity follows `days` automatically, and that `interval` can force `daily` or `hourly`. It doesn't add detail for `precision` or `vs_currency`, but those are fully described 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 states a specific verb and resource: 'Historical series for one coin over a trailing window set by `days`.' It also distinguishes itself from siblings by emphasizing the trailing-window scope and by naming what it is not (range, OHLC, history). An agent can tell it apart without opening another schema.

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

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

The description explicitly says when to use this tool: 'Use it to chart a trend ending now.' It then names the alternatives for explicit start/end (market_chart_range), candlesticks (ohlc), and a specific past day (history). This is clear, direct routing 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?

Annotations already declare the tool read-only and idempotent. The description adds valuable behavioral context beyond that: input timestamps are in seconds while response timestamps are in milliseconds, the response contains three named arrays, and CoinGecko chooses granularity based on window length. This is exactly the kind of non-obvious behavior disclosure that prevents empty or misaligned results.

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

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

The description is three sentences, front-loads the core purpose, and spends no words on unnecessary detail. Every sentence earns its place: the unit warning, the return structure, and the sibling routing all add practical 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 rich output schema and fully covered input schema, the description covers the critical gotcha, names the output arrays, and points to the correct sibling tool. There are no obvious gaps that would prevent an agent from selecting or invoking this tool correctly.

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

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

The schema already provides 100% description coverage for all five parameters, including examples and units. The description reinforces the from/to unit distinction but adds limited parameter-level meaning beyond that, 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 identifies the resource and action: it returns a historical series for one coin between two explicit timestamps. It also distinguishes itself from the sibling market_chart tool by contrasting explicit from/to points with a trailing days count, making the purpose unambiguous.

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

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

It gives explicit guidance: use this tool to align a series with a known event window, and use get_coingecko_coins_id_market_chart instead when you need a trailing window ending now. This directly routes agents to the correct alternative and prevents common misuse.

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

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

Annotations declare readOnly/idempotent/non-destructive, and the description adds critical response-shape behavior beyond them: bare array, positional rows, timestamps in milliseconds, no field names, no volume, and candle width derived from days. This anticipates common parsing mistakes and sets accurate 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?

Three sentences with no fluff: it front-loads the unusual response format, then the key derivation rule, then the alternative tool. Every sentence adds unique value and the length is appropriate for the tool's complexity.

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

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

Given a read-only, idempotent tool with an output schema and fully documented parameters, the description covers the non-obvious response format, the required days parameter role, and the main sibling alternative. Nothing critical is missing for an agent to call it correctly.

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

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

Schema has 100% parameter description coverage, so the baseline is 3. The description adds the semantic insight that candle width is derived from the `days` parameter, which is useful context not present in the schema, justifying a slight bump. It does not redundantly restate parameter names or formats.

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

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

The description states a specific output: OHLC candlestick data for one coin in a bare positional array, with explicit mention of timestamp, open, high, low, close. It distinguishes itself from the sibling market_chart tool by noting what it does not provide (volume) and what it is used for. No ambiguity about what resource and verb are involved.

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

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

It explicitly says when to use this tool ('for candle or technical analysis') and names the exact alternative tool to use when price line plus market cap and traded volume are needed. This is direct routing guidance with a named sibling, leaving little to inference.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the description doesn't need to restate safety. It adds behavioral context beyond annotations by enumerating the returned fields, including anomaly flags, and noting that setting 'depth' adds cost_to_move fields, which an agent would not infer from the annotations alone.

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 four sentences, each serving a distinct purpose: field inventory, depth behavior, parameter controls, and sibling distinction. It is front-loaded with the core purpose and contains no filler or redundant restatement of the tool name.

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

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

For a read-only tool with a full output schema and comprehensive annotations, the description covers the key aspects: what the tool returns, how to narrow and sort, and when to use an alternative. The only missing details are pagination limits and potential rate limits, which are minor given the output schema and clear safety hints.

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%, with page, depth, and order lacking schema descriptions. The description partially compensates by explaining depth's effect and that order sorts by trust score or volume, but for page it only says 'page with page', which adds no meaning. It does not fully clarify the exact semantics of all undocumented 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 opens with 'Every trading pair for one coin across venues', which clearly identifies the resource (trading pairs) and scope (one coin). It also explicitly names the sibling tool 'get_coingecko_exchanges_id_tickers' to differentiate the two, removing any ambiguity about which tool to select.

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

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

It explicitly states the use case: 'Use it to compare where one asset trades and how deep each book is' and provides a direct alternative: 'For every pair on one venue regardless of coin, use get_coingecko_exchanges_id_tickers.' This gives clear when-to-use and when-not-to-use guidance with no need for inference.

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

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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds meaningful behavioral context: it warns of the large payload ('roughly 18,000 entries'), the latency ('takes several seconds'), and recommends caching. This goes beyond the annotations by exposing performance and resource implications, though it could also mention rate limiting or response size caps.

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

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

The description is compact yet information-dense. It fronts the core purpose, then naturally flows into usage guidance, a concrete example ('bitcoin, not BTC'), performance caveats, and alternatives. Every sentence adds distinct value; there is no filler or redundancy.

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

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

For a tool with a single optional parameter and an existing output schema, the description is complete. It covers what the tool returns, how to use it, why caching is needed, and which sibling tool to use instead in different scenarios. Nothing an agent needs to invoke it correctly is missing.

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

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

The schema already covers the single parameter with a description ('Include platform + contract addresses.') and 100% schema coverage. The description's mention of include_platform ('Set include_platform to also get each coin's contract address per chain') reinforces the schema but does not add new semantic detail. This matches the baseline of 3 for high schema coverage.

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

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

The description states a specific verb and resource: 'The full CoinGecko identifier map: every listed coin as id, symbol and name.' It clearly distinguishes itself from siblings by explaining that it resolves tickers to ids, and explicitly contrasts with get_coingecko_simple_price and get_coingecko_token_data. An agent immediately knows what this tool produces and how it differs from related 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 gives explicit guidance on when to use this tool ('Use it once to resolve a ticker into the id') and when not to ('If you already know the ids and only want numbers, call get_coingecko_simple_price directly; to identify a coin from a contract address instead, use get_coingecko_token_data'). It also advises caching due to the large response. This leaves no ambiguity about the correct invocation 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context: pagination, sorting, filtering, and the conditional field addition when price_change_percentage is passed. It doesn't mention rate limits or response size, but the output schema exists and the annotations carry the safety burden.

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 dense but well-organized: it front-loads the core value proposition, then lists fields, then parameters, then use cases. Every sentence earns its place, and the sibling routing is at the end where it belongs.

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 list/market tool with an output schema and rich annotations, the description covers the main behaviors: pagination, sorting, filtering, and conditional fields. It also names the lighter alternative for simple price queries. Nothing critical is missing for an agent to select and invoke this tool correctly.

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

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

Schema coverage is 64%, so the description compensates by explaining the effect of key parameters: per_page/page for pagination, order for sorting, ids/category for narrowing, and price_change_percentage for adding a field. It doesn't detail every parameter, but the schema already covers most of them. The description adds meaning beyond the schema for the most important 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 states the tool returns a ranked market table with one row per coin and enumerates the exact fields. It distinguishes itself from siblings by naming get_coingecko_simple_price and get_coingecko_coins_id as alternatives for different use cases.

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 says when to use this tool ('leaderboards and segment scans') and when not to ('for the price of a few known coins... far lighter; for one coin in full use get_coingecko_coins_id'). This is strong routing 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context beyond these: it specifies the tool is a paged directory, lists the returned fields, and notes it deals with active exchanges. It doesn't describe pagination mechanics in detail, but the annotations lower the bar and the description still adds meaningful 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 three sentences with zero fluff. It front-loads the core purpose and data fields, then provides usage guidance, then alternatives. Every sentence earns its place, and the structure is clear 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 the tool's simplicity (two optional pagination params) and the presence of an output schema that likely documents the response structure, the description covers all essential aspects: what it returns, how to page, when to use it, and alternatives. It doesn't need to explain return values because the output schema handles that. The description is complete for an agent to decide when and how to call 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 0%, so the description must compensate. It mentions 'Page with `per_page` and `page`' which clarifies the purpose of both parameters as pagination controls, but it doesn't provide additional details like acceptable ranges or how they interact. The schema provides defaults and a maximum for per_page, so the description adds minimal semantic value beyond naming the params. A score of 3 is appropriate given the partial compensation.

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 returns a paged directory of active exchanges and enumerates the specific fields included. It distinguishes itself from sibling tools by naming get_coingecko_exchanges_list and get_coingecko_exchanges_id as alternatives, making its purpose unambiguous.

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 this tool ('Use it to rank or filter venues by trust and volume') and when not to, with specific alternatives and conditions: 'If you only need the identifier mapping, get_coingecko_exchanges_list returns all of them with no market data and no paging; for one venue in full use get_coingecko_exchanges_id.' This leaves no ambiguity.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world). The description adds useful behavioral context beyond those hints by clarifying that the embedded tickers are only a sample and status_updates are included, which shapes agent expectations about the response without contradicting the annotations.

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

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

The description is front-loaded with the core identity ('The full profile of one exchange') and then lists concrete fields, followed by succinct routing to alternatives. Every sentence contributes value; there is no repetition 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?

With only one well-documented parameter, an output schema present, and annotations covering behavior, the description supplies everything needed to select and invoke the tool correctly. It also covers the key decision boundaries against sibling tools, so no critical information is missing.

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

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

The input schema already fully documents the single id parameter with an example and explanation, so schema coverage is 100%. The description does not add new parameter-level meaning beyond reinforcing that the call targets one exchange, so the baseline of 3 is appropriate.

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

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

The description states a specific action and resource: retrieving the full profile of one exchange by its CoinGecko ID. It enumerates the contained fields and differentiates itself from sibling tools by naming what it is not, so an agent can distinguish it from list-style and ticker-specific 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 gives an explicit intended use ('Use it for venue due diligence') and names the exact alternatives for different needs: get_coingecko_exchanges for ranked lists and get_coingecko_exchanges_id_tickers for the complete paged pair list. This is clear routing guidance with no ambiguity.

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

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

Annotations already declare readOnly, idempotent, and non-destructive semantics, so the bar is lower. The description adds genuinely useful behavioral detail: results are paged, depth adds order-book move costs, and anomaly/stale flags are included. No contradiction with the annotations.

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

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

The description is front-loaded with the core purpose and keeps the alternative routing at the end. The field enumeration adds length but is informative; still, some of it is redundant with the output schema, so it is not maximally concise.

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 is complete for a read-only, paginated exchange-ticker tool. It covers scope, key parameters, use cases, the sibling alternative, and behavioral details like anomaly/stale flags. Since an output schema exists, the field list does not need to explain return values further.

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 50%, so the description must compensate. It adds meaning for depth ('add order-book move costs'), order ('sort'), coin_ids ('narrow to specific assets'), and hints at page via 'paged'. It does not mention include_exchange_logo or fully describe pagination, but it covers most of the gap.

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

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

The description clearly states it lists every trading pair listed on one exchange, with a specific scope and verb. It also differentiates itself from get_coingecko_coins_id_tickers by contrasting one-venue coverage with one-coin-across-venues, so an agent can select it correctly.

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 says to use it to audit one venue's coverage or liquidity, and names the alternative for the opposite use case. This gives an agent a clear decision rule between 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?

Annotations already declare readOnly, idempotent, non-destructive, and open-world behavior, lowering the bar. The description adds meaningful context beyond annotations: it discloses the flat map shape, approximate scale (1,500 exchanges), that it contains only `id` and `name`, and explicitly disclaims market data. With an output schema present, the lack of return-format detail is acceptable.

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

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

Two tight sentences with no filler: the first sentence defines the resource and scope, the second routes to dependent tools and the alternative. Every clause earns its place, and key facts are front-loaded.

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

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

For a simple, zero-parameter map tool with annotations and output schema already present, the description is complete. It covers what the tool returns, how it relates to downstream required IDs, what it excludes, and which sibling to use instead for richer data. Nothing needed for correct invocation is missing.

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

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

The tool has zero parameters, and the schema coverage is 100%, so the baseline is 4. The description reinforces this by stating 'It takes no parameters,' which prevents the agent from hunting for required inputs. There is nothing more to add at the parameter level.

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

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

The description states a specific verb and resource: it is a 'flat identifier map of roughly 1,500 exchanges as `id` and `name`' and distinguishes itself from siblings by naming what it is not (market data) and what it feeds into. An agent can tell it apart from `get_coingecko_exchanges`, `get_coingecko_exchanges_id`, and `get_coingecko_coins_id_tickers` without opening schemas.

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

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

It explicitly tells the agent when to use this tool: to 'resolve a venue name into the `id`' required by two named sibling tools. It also gives an exclusion—'carries no market data'—and points to `get_coingecko_exchanges` for trust scores and volumes. This is clear and actionable routing 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?

Annotations already establish this as a safe, read-only, idempotent operation. The description adds meaningful behavior beyond that: it clarifies that "trending" is attention-based rather than price-based, states the tool "Takes no parameters," and discloses the entry counts per category. This gives an agent an accurate mental model of what the response means.

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

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

The description is front-loaded with the core purpose and immediately gives concrete counts, then adds the key usage distinction. Every sentence earns its place, and no filler or redundant restatement of the title appears.

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

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

For a zero-parameter, read-only endpoint with an output schema available, the description is complete: it explains what the data means, what it contains, when to use it, and which sibling to prefer for a different need. Nothing an agent needs to make the correct invocation is missing.

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

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

The tool has zero parameters and the input schema is empty, so there is no parameter burden to carry. The description explicitly says "Takes no parameters," which removes any doubt, though the schema alone is already sufficient here. This is at the baseline for a no-parameter tool with a slight confirmation benefit.

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

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

The description states a specific verb and resource: "CoinGecko's current trending board, ranked by search activity on CoinGecko itself." It enumerates the exact contents (`coins` 15, `nfts` 7, `categories` 6) and explicitly separates this tool from `get_coingecko_coins_markets`, so an agent can tell it apart from siblings without ambiguity.

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

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

The description gives an explicit when-to-use rule: "Use it as a discovery entry point when the user named no specific asset." It also names the alternative for price-driven rankings: "for movers ranked by market data use `get_coingecko_coins_markets` ordered by volume," making the selection criteria unambiguous.

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

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds useful behavioral detail beyond those annotations: response is keyed by coin id, field names derive from the quote currency, and optional include flags control which extra fields appear. It does not discuss rate limits or the precision parameter, but the existing annotation coverage lowers the burden.

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 dense but well organized: purpose first, response behavior second, usage guidance and alternatives last. Every sentence carries operational value, and the alternatives are stated without excess wording.

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

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

For a simple read-only price lookup, the description covers output structure, flag behavior, when to use it, and sibling routing. The only material omission is precision, and since an output schema exists, the return-value burden is reduced. Overall it is nearly complete for correct tool selection and 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 coverage is low (29%), but the description compensates well: it clarifies ids and vs_currencies usage, explains how quote-currency field names are built, and maps each include flag to the corresponding output field. The only notable gap is the undocumented precision parameter, which is not mentioned in either the schema description or the tool description.

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

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

The description names a specific operation (price lookup by known CoinGecko ids and vs_currencies) and states the response shape: a map keyed by coin id. It also differentiates itself from sibling tools by pointing to get_coingecko_coins_markets for rank/supply/ATH data and get_coingecko_simple_token_price_id for contract addresses.

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

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

It gives an explicit use condition: use whenever ids are already known and only current numbers are needed. It also names two concrete alternatives with their distinguishing conditions (rank/supply/ATH vs contract address), so an agent can route correctly without further inference.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context: it returns a flat array of lowercase strings, has exactly 63 entries, and takes no parameters. It doesn't contradict the annotations and provides sufficient detail for a simple read-only list 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 three sentences, each earning its place: the first defines the resource, the second specifies the output format and parameter absence, and the third gives usage guidance and an alternative. No fluff, and key information is front-loaded.

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

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

For a no-parameter tool with an output schema (provided separately), the description is complete: it states what is returned, the count, examples, when to use it, and the alternative for a related purpose. An agent can correctly decide to call this tool without needing additional details.

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

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

The tool has zero parameters, and the schema shows an empty object. The description explicitly states 'takes no parameters', which reinforces the schema. Since there are no parameters to explain, the description appropriately focuses on the output and usage context.

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

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

The description clearly states that the tool returns the list of quote currencies accepted by the vs_currency parameter of other CoinGecko tools, and explicitly distinguishes it from the coin-side list tool (get_coingecko_coins_list). It names specific currencies and the return format, leaving no ambiguity about what the tool does.

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

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

It provides explicit guidance: call this before using a non-obvious quote currency rather than guessing, and names the sibling tool to use for coin identifiers. This clearly defines when to use this tool versus alternatives.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful behavioral detail beyond those annotations: response is keyed by lowercase contract address, field names derive from the quote currency, and inclusion of market cap, volume, change, and last-updated fields depends on the corresponding include flags.

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

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

Four sentences, each with a distinct purpose: core operation, key parameter semantics, response shape, and alternative routing. It is dense but not redundant, and front-loads the most important distinguishing fact.

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 annotations, output schema, and the description's coverage of required parameters, response format, and sibling tool alternatives, nothing essential is missing. An agent has enough to select and invoke the tool correctly.

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

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

The description adds real meaning to id, contract_addresses, and vs_currencies, and explicitly ties all four include_* booleans to response fields. Precision is not covered in the description, but the schema documents it adequately, so the description still adds value above the structured data.

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

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

The description identifies a precise operation — price lookup keyed by contract address rather than CoinGecko id — and clearly differentiates it from siblings like get_coingecko_simple_price and get_coingecko_token_data. The first sentence immediately distinguishes it on the key dimension that matters.

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

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

It explicitly states when to use the tool: when you hold an address and no id. It also names the two alternatives and the conditions that select them, so an agent receives direct routing guidance rather than having to infer 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?

Annotations declare readOnly, openWorld, idempotent, and non-destructive, which already establish the safety profile. The description adds value by specifying the exact return shape (listing all fields and tickers array), and notes the relationship to get_coingecko_coins_id without contradicting annotations.

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

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

The description is compact and well-structured: it opens with the core purpose, clarifies the parameter requirement, details the return value, gives a use case, and ends with a comparison to a lighter alternative. Every sentence carries information without 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 output schema is present, the tool's return values are already documented, and the description adds necessary context about the lookup method, alternate tools, and use case. For a 2-parameter tool with high schema coverage and rich annotations, this is complete and 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?

Schema coverage is 100% and describes each parameter adequately (id as asset platform, contract address as token address). The description reinforces that both are required and no others, but adds little beyond the schema's clear definitions. Baseline 3 is appropriate given high 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?

Clearly states the tool looks up a coin profile by contract address instead of CoinGecko id, distinguishing it from get_coingecko_coins_id. It lists the specific fields returned and the use case of identifying an unknown token, making its purpose unambiguous and well-differentiated from 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?

Explicitly states both parameters are required and no others, and gives a strong routing hint: for current price only, use the far lighter get_coingecko_simple_token_price_id. This provides clear when-to-use and when-not-to-use guidance, and implicitly contrasts with get_coingecko_coins_id for id-based lookups.

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

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds meaningful behavioral context: it returns `prices`, `market_caps`, and `total_volumes` as timestamp-and-value pairs in milliseconds, and clarifies the trailing-window semantics. No contradiction.

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

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

Three sentences with no filler: core function, parameter roles, return shape, and selection guidance are all present. Every clause contributes to the agent's understanding.

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?

Covers the essential calling context: token identification, trailing window, output structure, and when to choose the range sibling. An output schema exists, so deeper return details are available there, and nothing important is missing.

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

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

Schema coverage is 100%, so the schema already documents all parameters. The description adds value by relating `id` to asset platform and `contract_address` to the token, and by clarifying that `days` sets the trailing window, which is slightly more semantic than the schema entries alone.

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

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

States a specific verb and resource: retrieves historical price/market-cap/volume series for a token identified by contract address over a trailing window. It distinguishes itself from siblings by naming the id-based market chart and the range-based chart, so an agent can tell them apart.

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

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

Explicitly instructs 'Use it when you have an address rather than a CoinGecko id' and points to `get_coingecko_token_market_chart_range` for explicit start/end. Also references the same shape as `get_coingecko_coins_id_market_chart`, clarifying when the id-based alternative 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?

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context by clarifying that from/to are Unix seconds while response timestamps are milliseconds, and by detailing the returned series fields. This goes beyond the annotations without repeating them.

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

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

The description is compact and front-loaded, with the core purpose stated first, followed by necessary unit details, return format, and alternatives. Every sentence contributes value without 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 an output schema exists and annotations cover the safety profile, the description covers all essential invocation details: identification method, time units, response fields, and alternatives. No critical gaps remain, though it could mention pagination or limits if any, but none appear relevant.

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

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

The schema already provides 100% coverage with descriptions and examples for every parameter, so the description does not need to add much. It does reinforce that `id` is the asset platform and `contract_address` is the token, but this information is already present in the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool fetches historical series between two specified time points for a token identified by contract address. It uses specific verbs and resources, and differentiates itself from the sibling tools such as get_coingecko_token_market_chart and get_coingecko_coins_id_market_chart_range.

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

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

Explicitly states when to use this tool: 'when you have an address and a fixed window.' It also names two alternatives and their use cases, providing clear routing guidance for an agent.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context: it is free, stops before any spend, and explains how price.model varies (quoted, list, dynamic, composed). It also clarifies that suggested_max_price_usd has headroom. This goes beyond the annotation flags and gives the agent a clear model of what happens.

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 moderately long but well structured: it opens with the core purpose, then explains the price model in a dedicated paragraph. No redundancy or filler. It front-loads the most critical information (contract fields) and then gives necessary detail about price semantics. Slightly dense but not overly 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?

The tool has an output schema, so return values need no description. The description covers the key behavioral aspects (no spend, pricing models, max_price headroom) and clarifies edge cases like routes without a price. For a read-only informational tool, this is complete enough for an agent to use it correctly.

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

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

Schema description coverage is 100%, so parameters are already documented. The description adds some nuance, such as how arguments affect pricing and that required parameters may be needed before a price can be quoted. It also clarifies with_quote's purpose (one round trip, spends nothing). These are useful but not essential given the schema's completeness.

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

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

The description states a specific purpose: returning the full contract of one or more operations, including schemas, read_only, side_effects, price, and known_pitfalls. It clearly distinguishes this from executing operations (use, batch_use) and from discovery (search, list_categories). The verb 'get' and the noun 'details' align with the title, and the first sentence is explicit.

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

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

The description implies the tool is used to assess an operation before spending (e.g., 'A quote authenticates like a call but stops before any spend'), and the schema says 'One operation_id from search', hinting at a flow. However, it never explicitly states when to choose this over siblings like use or search, nor does it give exclusions. The guidance is implied, not stated.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond annotations: the tool is free, requires no key, and can direct users to a category-specific endpoint that lists tools directly rather than through search.

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 moderately detailed but every sentence adds useful information: output scope, cost/auth, sibling differentiation, and endpoint usage. It is slightly longer than strictly necessary but remains well-structured and front-loaded with the core purpose.

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

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

For a zero-parameter, read-only tool with an output schema and safety annotations, the description is complete. It covers what the tool returns, the free/no-key access model, and provides the category endpoint for specialized use, leaving no essential gap for an agent to call it correctly.

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

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

The tool has zero parameters, so the baseline is 4. The description includes a <category> placeholder only in the endpoint examples, not as a tool parameter, which is appropriate supplementary guidance rather than a parameter-semantics gap.

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

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

The description clearly states what the tool does: it presents the AIsa catalogue at a glance, including categories, servers, tool counts, and a dedicated category endpoint. It also distinguishes itself from search by explaining that the endpoint lists tools directly instead of via search.

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: use list_categories for a catalogue overview, and use the provided endpoint when you only need one category. It explicitly contrasts with search ('instead of via search') and notes tool-router has no equivalent, although it does not exhaustively cover all sibling alternatives.

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 discloses meaningful behavior beyond annotations: search spans the entire AIsa catalogue, candidates may belong to modules other than the current one, multiple providers for the same metric are surfaced, and no API key is required. This gives the agent a clear picture of scope and output 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 front-loaded with the core purpose and is dense with useful information: scope, no-auth requirement, response shape, and relationship to the catalogue. Each sentence adds operational value, and the structure makes the tool's behavior predictable.

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 complex discovery tool with output schema, the description is unusually complete: it explains the response modalities, candidate fields, direct pass-through to `use`, full-catalogue search behavior, and cross-provider visibility. An agent has enough context to invoke and interpret the tool correctly.

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

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

Schema coverage is 100%, so the schema already documents all parameters. The description adds value by explaining that the category parameter is not a hard boundary—search spans the full catalogue—and that queries are plain-language task descriptions, which clarifies how to use the tool 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 finds AIsa data operations across many categories via a plain-language query. It distinguishes itself from siblings like get_details and use by emphasizing that search covers the full catalogue, not just the pinned category.

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 conveys when to use search: when you need to discover operations across the full catalogue, even those not in the current tools/list. It also implicitly contrasts with get_details by noting that returned candidates already include input_schema, so they can be passed directly to `use` without an extra call.

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

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

Annotations already provide readOnly=false, openWorldHint=true, and destructiveHint=true. The description adds valuable behavior beyond that: billing per call, the BatchCallResult response shape, and the error structure with retryable status. It does not spell out side effects, but the destructive flag is already carried by annotations, so the additional context is sufficient.

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

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

Three short sentences, each earning its place: purpose, cost, response shape, and routing guidance. Key behavioral facts are front-loaded, and nothing is redundant with the schema or annotations.

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 that an output schema exists and all parameters have descriptions, the tool description is complete enough for correct invocation. It covers cost, return/error contracts, and how routing to this tool differs from calling pinned tools directly, leaving no practical gap.

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

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

Schema description coverage is 100%, and each parameter is already clearly documented: operation_id as returned by search, search_id provenance, arguments matching input_schema, and max_price_usd as a spend guard. The description does not need to add parameter detail, 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 opens with 'Execute one AIsa operation,' a specific verb+resource statement. The word 'one' distinguishes it from the sibling batch_use, and the closing note distinguishes it from calling pinned tools directly. An agent can tell what this tool is for immediately.

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

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

It explicitly states when to use the tool: 'this is the way to call anything found through search.' It also gives the alternative: 'Pinned tools in tools/list can also be called directly.' This is clear when-versus-alternative guidance with no ambiguity.

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