Omnicall — Agent Tools Gateway

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

Without annotations, the description should disclose behavior like rate limits, context length, or safety. It only provides cost info and default model, omitting important operational 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 brief and includes cost, but appears truncated and lacks clear structure. It could be more organized but is mostly 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?

Given the complexity of an LLM completion tool and no output schema, the description fails to mention return format, token limits, or usage examples, leaving significant gaps.

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

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

The single parameter 'arg' is not described in schema or description beyond the hint to query models. No instruction on format, expected input, or how to specify model.

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 it returns LLM completions and mentions specific models (DeepSeek V3.1, gpt-5-mini, gemini-flash), clearly defining its function. It is distinguishable from sibling AI tools like ai_image or ai_music.

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. The mention of querying models is a usage hint but lacks context for decision-making. Truncated 'Agents: summ' adds confusion.

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 provided. Description mentions cost range and model options, but lacks disclosure of behavioral traits such as rate limits, error handling, destructive potential, or safety. As a mutation tool (creating a completion), this is insufficient.

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 short with two sentences, but the first sentence is truncated. While concise, the truncation and lack of structure reduce its effectiveness.

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 incomplete given the tool's complexity: it does not explain 'bulk tagging', model selection mechanism, output format, or error handling. No output schema exists to compensate.

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 sole parameter 'arg' has no description in the schema, and the description does not explain its meaning or format. Schema coverage is 0%, so the description must compensate but fails to do so.

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 it returns an LLM completion for bulk tagging, with model options. However, it is truncated ('bulk taggi'), making the purpose partially unclear. It distinguishes from sibling AI tools by mentioning bulk tagging, but lacks explicit differentiation.

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 like ai_ask. Implies bulk tagging use case but does not specify when not to use or provide context for 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?

No annotations are provided, so the description must disclose behavioral traits. It mentions cost and the use of Flux, but lacks details on side effects, safety, rate limits, or idempotency. The description does not state that this is a read-only 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 short but contains a truncation ('visual generat') which harms clarity. The cost information is relevant but could be integrated better. Every sentence serves a purpose, but the truncation reduces effectiveness.

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 partially explains the return value ('hosted image URL') but does not describe the URL format, additional metadata, or error handling. The tool is simple (one parameter) but the description could be more 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?

With 0% schema description coverage, the description must compensate for the undocumented 'arg' parameter. It only hints that the input is a 'text prompt', but does not explain the required format, constraints, or expected length.

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 purpose: 'Returns hosted image URL from text prompt via Flux.' It specifies the verb, resource, and method, distinguishing it from sibling tools like ai_video and ai_music.

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. The mention of 'Agents: content, design, creative bots' implies audience but does not provide usage conditions, exclusions, or comparisons to other 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 must disclose all behavioral traits. It mentions the tool returns a URL, is royalty-free, and includes cost per call. However, it does not cover potential side effects, authentication requirements, rate limits, or failure modes. The cut-off sentence adds ambiguity.

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

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

The description is brief, but it front-loads the core purpose. The cost information is a bonus. However, the sentence structure is awkward with a cut-off line, and the 'Agents:' part seems incomplete, reducing readability.

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

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

For a relatively simple tool (one parameter, returns a URL), the description could be adequate but is missing important context like output format, example inputs, and error handling. Given no output schema, the description should cover these aspects, but it does not.

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 required parameter 'arg' with 0% description coverage. The description implies the parameter is the text prompt but provides no details on format, length restrictions, or style guidance. Some meaning is added, but it is insufficient given the lack of schema documentation.

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 royalty-free instrumental audio track URL from a text prompt via MusicGen. It also mentions target agents (media, content, creative bots), which helps distinguish it from sibling AI tools (e.g., ai_image, ai_speech). However, the sentence is cut off, slightly reducing clarity.

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 specifies that this tool is for media, content, and creative bots, implying use cases. It does not explicitly state when not to use it or compare with alternatives like other AI generation tools. The guidance is implicit but lacks depth.

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 carries full burden. It mentions the tool returns a completion (implying read-only), but does not disclose other behavioral traits such as rate limits, idempotency, or destructive potential. The cost is noted, but safety and side effects are not addressed.

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

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

The description is very short but appears truncated ('complex analy'), making it incomplete. It includes unnecessary line breaks and lacks a clear structure. The cost information is useful, but the overall conciseness is undermined by the cutoff.

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 and a single required parameter with zero schema documentation, the description should fully explain how to use the tool and what to expect. It partially addresses the model query aspect but is incomplete and fails to cover return values, error conditions, or usage examples. The context provided is insufficient for reliable agent 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 input schema has one parameter 'arg' with no description (0% schema coverage). The description hints that 'arg' might involve a model query ('query ?model'), but this is vague and incomplete. The description does not adequately compensate for the missing schema documentation, leaving the parameter's format and possible values unclear.

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 it returns a Claude 4.5 Sonnet completion, giving a specific verb and resource. However, the phrase 'query ?model for gpt-5, gpt-4o, gemini-pro, gemini-3.1-pro' is ambiguous, and the description is truncated ('complex analy'), making the exact purpose unclear. It partially distinguishes from siblings (e.g., ai_ask) but lacks a clear scope definition.

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 its siblings (e.g., ai_ask, ai_eco). Only cost information is provided, but no context about ideal use cases, prerequisites, or scenarios where alternative tools are better.

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 bears full responsibility. It discloses cost ($0.005–$0.05 USDC on Base per call) and the underlying engine (Kokoro), but omits details on potential side effects, latency, or authentication requirements.

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

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

The description is concise, front-loading the core function in the first sentence, then adding use cases and cost. The apparent truncation ('Keywo') slightly detracts but overall it 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 tool with one parameter and no output schema, the description covers purpose, use cases, and cost. However, it fails to explicitly link the parameter to the input text, leaving some ambiguity.

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

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

With 0% schema description coverage, the description must explain the parameter. It mentions 'from text prompt' which implies the 'arg' is the text, but does not explicitly map the parameter or specify format, length, or constraints.

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 'Returns natural AI voice audio URL from text prompt via Kokoro,' which clearly identifies the tool as text-to-speech conversion. It distinguishes from sibling AI tools (ai_image, ai_music, etc.) by specifying the voice modality.

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 lists use cases: 'voice bots, accessibility, narration, TTS.' This provides clear context for when to use the tool, but does not explicitly mention when not to use it or offer 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?

No annotations provided, so description bears full burden. It mentions cost but fails to disclose crucial behavioral traits like rate limits, auth needs, or response structure. Minimal transparency for a model 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?

Description is short and direct, cutting to the tool's purpose and cost. However, brevity comes at the expense of parameter documentation, which is a missed opportunity.

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 top-end reasoning model, the description omits critical details: input/output format, behavior, and the nature of the completion. With no output schema and minimal parameters, the description falls short of 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?

Single parameter 'arg' has zero schema description coverage; description does not explain its purpose or format. Tool relies entirely on the parameter name, which is insufficient.

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 states 'Returns Claude Opus 4.6 completion' (specific verb and resource) and emphasizes 'top-end reasoning model for hardest tasks', distinguishing it from siblings like ai_ask or ai_eco. Truncation slightly detracts but clarity remains high.

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?

Description implies use for 'hardest tasks: deep multi-step analysis, synthesis', offering some guidance. However, it lacks explicit when-not-to-use or alternative recommendations, leaving room for 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?

No annotations are provided, so the description must bear the full burden. It discloses the model (LTX-Video) and cost, but fails to mention whether generation is synchronous/asynchronous, any limits on input length, content policies, or output URL expiry. This is insufficient for a tool with no 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 short and front-loaded with the core functionality. However, the second sentence appears truncated ('video generation, vis'), which may cause minor confusion. Otherwise, it 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?

The description covers the basic input-output semantics (text prompt → URL) and cost, but lacks details on typical video duration, resolution, generation time, or any constraints. Given the simplicity of the tool (1 param, no output schema), 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?

With 0% schema description coverage, the description clarifies that the single parameter 'arg' is a text prompt. This adds meaning beyond the schema, but it does not specify format, length constraints, or examples, which limits its helpfulness.

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 short video clip URL from a text prompt using LTX-Video. It distinguishes from sibling ai_* tools by specifying video generation, and the verb 'Returns' with resource 'short video clip URL' is specific.

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 target agents (creative, media, content bots) and cost, implying use for video generation. However, it does not explicitly state when to use this tool over alternatives or provide exclusions, leaving usage guidance implicit.

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. The description only adds the cost range ($0.005–$0.05 USDC) but does not disclose whether the tool is read-only, required authentication, rate limits, or how the input parameter affects behavior. Behavioral context is minimal.

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 short and includes a useful cost note, but it is truncated ('Agen' suggests incomplete). Every sentence serves a purpose, but the lack of parameter explanation is a critical omission. Adequate but not optimal.

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 parameter and no output schema, the description should fully explain input and output. It covers purpose and cost but fails to specify the input parameter's meaning, which is essential for correct invocation. Incomplete for the tool's simplicity.

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 defines a single required 'arg' parameter with zero description. The tool description does not explain what 'arg' represents (e.g., chain name, filter criteria), leaving the agent with no guidance on how to populate it. Schema coverage is 0% and description adds no value.

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 explicitly states it provides 'blockchain rankings by total value locked (TVL in USD) via DefiLlama' and specifies the use case 'for chain allocation and competitive analysis'. This clearly distinguishes it from sibling tools like crypto_defi_tvl which focus on DeFi protocols.

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 chain allocation and competitive analysis but lacks explicit guidance on when to use this tool over alternatives (e.g., crypto_market, crypto_price). No exclusion criteria or prerequisites are mentioned.

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

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

No annotations exist, so the description must cover behavior. It states 'real-time' and cost, but omits details like error handling, rate limits, data freshness, or what happens with invalid arguments. Barely adds value beyond purpose.

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

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

The description is very concise (two sentences) and front-loaded with purpose and cost. However, it sacrifices critical parameter information for brevity, making it efficient but incomplete.

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, no annotations, and a single required parameter with 0% coverage, the description fails to provide sufficient context. It does not specify input format, output structure, or error behavior, leaving major gaps for agent 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?

The only parameter 'arg' has 0% schema description coverage, and the description does not explain what value it expects (e.g., protocol name). The description adds no semantic meaning to the input 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 retrieves real-time DeFi protocol TVL in USD via DefiLlama for health checks and capital flow tracking. It is specific about the resource (DeFi TVL) and verb (real-time retrieval), but does not explicitly distinguish from siblings like 'crypto_protocols' or 'defi'.

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 use cases ('fast health checks and capital flow tracking') but provides no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Cost is mentioned but not context of usage.

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 full burden. It discloses cost ($0.005–$0.05 USDC per call) and live data, but does not specify read-only nature, rate limits, or authentication needs. The cost information adds partial transparency.

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 defines the tool's purpose and data, the second adds cost. It is front-loaded and contains no extraneous information, earning its place efficiently.

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 parameter (no output schema, no annotations), the description covers the return data and cost but fails to document the parameter, which is critical for usage. It is minimally viable but has a significant 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?

The schema has 0% description coverage for the single required parameter 'arg' (string). The description does not explain what 'arg' represents, leaving the agent without guidance on how to invoke the tool correctly.

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 provides live DEX market data (price, liquidity, volume, FDV, market cap, chain) via DexScreener, with a specific focus on token trading and swaps. This distinguishes it from sibling tools like crypto_price or dex by specifying the data source and context.

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

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

No guidance is given on when to use this tool versus alternatives like 'dex' or 'crypto_market'. The description implies usage for DEX data but does not provide exclusions or context for selecting 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?

No annotations provided; description states data source (CoinGecko) and cost, but lacks details on side effects, rate limits, or authentication. Basic 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?

Two efficient sentences front-loaded with purpose and cost; no redundant 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?

Despite mentioning specific metrics, the lack of parameter explanation and output schema makes the tool incomplete for use.

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

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

The only parameter 'arg' has no description in schema or description; with 0% schema coverage, the agent has no guidance on what to provide.

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 clearly states the tool provides exchange metrics (24h volume, trust score, trading pairs) for venue selection and liquidity routing, distinguishing it from siblings like crypto_price or crypto_market.

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 mentions use case ('for venue selection and liquidity routing'), indicating when to use, but does not provide exclusions or alternative tool names.

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

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

No annotations are provided, so the description must disclose behavioral traits. It mentions the data source and cost, but fails to state that it is read-only, whether authentication is needed, rate limits, or what the output format looks like. The description is also cut off ('ga'), leaving ambiguity.

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 short but incomplete (ends abruptly with 'ga'). It includes a useful cost line, but the lack of structure and the broken sentence lower the score. It could be more concise while still covering essential details.

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 low complexity (one parameter, no output schema), the description should fully cover usage. It explains the purpose and cost but leaves the required parameter unexplained, the output format undefined, and the usage scenario vague. This is insufficient for an agent to use 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 input schema has one required parameter 'arg' with 0% schema coverage and no description. The description does not explain what 'arg' represents (e.g., limit, date range). This omission severely hinders correct parameter usage.

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 the Crypto Fear & Greed Index (0–100 sentiment) plus 7-day history, specifying the data source (Alternative.me). This makes the purpose evident. However, it does not differentiate from sibling tools like crypto_market or crypto_price, which could also be used for sentiment analysis indirectly.

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 hints at usage for 'risk-on/off signals and entry/exit' decisions, implying it helps gauge market sentiment. No explicit guidance on when to avoid or alternative tools is given. The cost information ($0.005–$0.05) sets expectations, but there is no mention of prerequisites or constraints.

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 mentions the cost per call and that data is live, but fails to explain the required 'arg' parameter, any side effects, data freshness, or read-only nature. This lack of disclosure significantly hinders an AI agent's ability to invoke the tool correctly.

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 but ends abruptly with 'batching o', indicating truncation. It front-loads the main purpose but loses points for incompleteness and lack of parameter explanation.

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 unexplained required parameter and no output schema, the description fails to provide a complete picture. It omits return format, update frequency, and parameter semantics, making it insufficient for an AI agent to use 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 0%, yet the description does not explain the single required 'arg' parameter at all. It provides no hint about what values to pass (e.g., chain name, symbol) or its purpose, leaving the agent completely uninformed.

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 live gas prices (in gwei) across five specified chains (Ethereum, Base, Arbitrum, Optimism, Polygon) for transaction-cost prediction and batching. This specific verb+resource statement distinguishes it from sibling tools like crypto_price (price of tokens) or crypto_market (general market 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 implicitly suggests usage for gas price prediction and batching but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternative tools among the many crypto 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?

With no annotations, the description carries the full burden. It discloses the cost per call ($0.005–$0.05 USDC) and data source (CoinGecko), but does not mention read-only status, rate limits, or authentication needs. Cost is a useful behavioral trait, but other aspects are missing.

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, no wasted words. The first sentence front-loads the purpose, the second adds the cost. 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 no output schema, the description would need to explain the return structure. It lists metrics but not their format. Additionally, the parameter is undocumented. The description is incomplete for a tool with one untyped parameter and a multi-field 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 required parameter 'arg' with 0% description coverage, and the tool description does not explain the parameter's purpose, format, or allowed values. The agent cannot know what to pass to this tool.

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 global crypto snapshot with specific metrics (market cap, volume, dominance, coin count, sentiment) via CoinGecko, which distinguishes it from sibling tools that focus on specific crypto data like price or fear-greed index. It's a specific verb+resource description.

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 phrase 'for macro' gives a hint about usage context, but there is no explicit guidance on when to use this tool over siblings (e.g., crypto_price, crypto_market) or when not to use it. No alternatives are mentioned.

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

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

No annotations are provided, so the description carries the full burden. It discloses the data source (CoinGecko) and cost ($0.005–$0.05 USDC per call), but fails to mention rate limits, response format, or any behavioral constraints beyond the cost.

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 short but truncated, and includes an extra line about cost. It could be more concise without the cost detail and should complete the final sentence.

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

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

Given the tool returns historical OHLCV candles, the description is incomplete: it does not specify time range, interval, output format, or limit. With no output schema and no annotations, the description should provide more context for this data retrieval task.

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

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

The schema has one required parameter 'arg' with no description (0% coverage). The description does not explain what 'arg' should be (e.g., coin ID or ticker), leaving the agent without essential information to properly invoke the tool.

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 provides historical OHLCV candles via CoinGecko for backtesting and performance analysis. However, the description is truncated ('performance analy') and does not explicitly distinguish from sibling tools like crypto_price or crypto_market.

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 use cases ('for backtesting, training, and performance analysis') but provides no guidance on when to use this tool versus alternatives, such as crypto_price for current prices or crypto_market for market data.

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 fully disclose behavioral traits. It mentions cost and data source, but does not describe error behavior, response format, rate limits, or mutability. The cost disclaimer is helpful but insufficient for a complete behavioral picture.

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 short but incomplete due to truncation ('for res'). It lists many data points, but the cutoff and lack of structure (e.g., no sentence about parameters or usage) make it feel half-finished. Conciseness is not achieved at the expense of 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?

With no output schema, the description should explain return values well. It lists fields offered, which is good, but fails to describe the parameter, usage context, or how data is structured. For a tool with only one parameter and zero annotations, this is insufficiently 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 one required parameter 'arg' with no description, and the schema description coverage is 0%. The tool description does not explain what 'arg' represents (e.g., coin name, symbol, or ID), leaving the agent to guess. This fails to add meaning beyond the bare 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 lists many data fields (price, cap, rank, etc.) and the data source (CoinGecko), making the general purpose clear. However, the description ends abruptly with 'for res', suggesting truncation, which reduces clarity and completeness. It does not explicitly differentiate from sibling tools like crypto_price or crypto_history.

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 its siblings, such as crypto_price for simple price or crypto_history for historical data. There are no usage examples, prerequisites, or when-not-to-use indications.

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 description bears full burden. It claims ultra-fast low-latency behavior and states cost range, but fails to disclose error handling, data freshness, rate limits, or side effects. The read-only nature is implied but not explicitly 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 short (two sentences) and front-loads key information. However, it contains a typo ('high-freque') and the cost detail, while useful, is secondary. It is not optimally structured for quick parsing.

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 (one param, no output schema), the description partially covers purpose and behavior but omits crucial details: parameter meaning, output format, error cases. While cost is mentioned, the overall completeness is low for an AI agent to reliably 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?

The sole parameter 'arg' has no schema description and is not explained in the tool description. The description mentions 'any coin IDs', suggesting arg should be a coin ID, but does not specify format, how to pass multiple IDs, or if it's case-sensitive. With 0% schema coverage, the description insufficiently compensates.

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 spot price, 24h change, and market cap for coin IDs via CoinGecko. It distinguishes itself as an ultra-fast, low-latency price feed, likely for high-frequency queries. However, it does not explicitly differentiate from siblings like crypto_market or crypto_history.

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 fast price queries with cost mention, but provides no guidance on when to use this tool versus alternatives (e.g., when to use crypto_market for broader market data or crypto_history for historical data). No exclusions or prerequisites 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?

The description discloses cost and data source (DefiLlama) but lacks details on return format, rate limits, authentication, or behavioral traits beyond basic retrieval. With no annotations, the description carries full burden but only partially addresses transparency.

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 short and front-loaded with the core purpose. The cost and agent line add some noise, but overall it is efficient. Each sentence serves a purpose, though clarity on 'Agents: D' is lacking.

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 undocumented parameter and no output schema, the description is insufficient. It fails to specify what the 'arg' parameter accepts (e.g., protocol name, category), making it incomplete for an agent to use 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 single parameter 'arg' is entirely undocumented in the schema (0% coverage) and the description does not explain what value it expects, leaving the agent unable to determine valid input. The description adds no semantic meaning to the parameter.

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

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

The description clearly states it provides DeFi protocol rankings with TVL, category, and 1d/7d change via DefiLlama, and suggests use for portfolio exposure and yield discovery. However, it does not differentiate from similar sibling tools like crypto_defi_tvl or crypto_yields.

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 vaguely mentions 'for portfolio exposure and yield discovery' but gives no explicit guidance on when to use this tool versus alternatives, nor any conditions or prerequisites. No when-not-to-use 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 exist, so the description must disclose behavioral traits. It mentions the data source (DefiLlama) and cost per call, but does not explain data freshness, rate limits, authentication, or the effect of the input parameter. Minimal transparency.

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 short, with two sentences: one for purpose and one for cost. It is front-loaded with the core functionality. However, it could include a brief note on the parameter without sacrificing 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 has one ambiguous parameter and no output schema or annotations, the description is incomplete. It lacks information about the input format, output structure, and any prerequisites or limitations. The cost detail is helpful but insufficient for confident use.

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

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

The input schema has a single required parameter 'arg' with no description or enum, and schema coverage is 0%. The description does not explain what the parameter represents or how to use it, leaving the agent completely uninformed about valid inputs.

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 provides stablecoin rankings (market cap, supply, reserves) via DefiLlama, intended for treasury, risk, and payment strategy. The verb 'rankings' and resource 'stablecoins' are specific, and the use case helps distinguish from generic crypto market 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 mentions intended use cases (treasury, risk, payment strategy) but does not specify when to use this tool over alternatives, nor does it provide exclusions or comparisons to sibling tools. No explicit guidance on 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?

No annotations provided. Description mentions cost and data source (CoinGecko) but does not disclose read-only nature, rate limits, authentication needs, or response format.

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?

Short and front-loaded with purpose, followed by cost. However, the sentence appears cut off ('macro-hedg'), which slightly reduces 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?

Given one required parameter with no schema description, no output schema, and no annotations, the description lacks essential details on parameter usage and output, making it incomplete for effective 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?

The single parameter 'arg' has no schema description and 0% coverage. The description does not explain what value 'arg' expects (e.g., company name, ticker), leaving the agent unable to determine correct input.

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 public company crypto holdings (BTC/ETH quantity and USD market value) via CoinGecko, which is a distinct resource among sibling tools like crypto_price or crypto_market that focus on prices or market 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?

Implies usage for corporate strategy and macro-hedging, but no explicit guidance on when to use this tool versus alternatives or 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 discloses the cost ($0.005-$0.05 per call) and states the data source (CoinGecko), adding context beyond missing annotations. However, it does not mention whether the tool is a read-only operation, rate limits, authentication requirements, or any side effects, leaving some behavioral uncertainty.

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

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

The description is concise with two sentences: the first covers purpose and output, the second adds cost information. It is front-loaded with the main functionality, but the missing parameter documentation is a notable omission.

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 with no description, no annotations, and no output schema, the description is insufficient for an agent to use the tool effectively. It lacks critical details about what input is expected and what the output looks like, resulting in a high risk of misuse.

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 required parameter 'arg' (type string) with no description or enum, and the schema description coverage is 0%. The description fails to explain what 'arg' represents (e.g., coin ID, category, or query), offering no guidance to the agent on how to invoke the tool correctly.

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 returns trending coins with specific data points (price, cap rank, 24h change, sentiment momentum) and names the source (CoinGecko). It distinguishes from sibling tools like crypto_price by focusing on 'trending' rather than individual coin prices, though it doesn't explicitly compare to all 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 phrase 'for market-timing and attention' hints at a use case, but there is no explicit guidance on when to use this tool versus other crypto tools (e.g., crypto_price, crypto_market). No conditions, prerequisites, or exclusions 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 provided, and the description does not disclose behavioral details such as read-only nature, data freshness, sorting order, or any side effects. Only cost info is mentioned but that is not a core behavioral trait.

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

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

The description is very short but truncated, indicating missing content. Cost info is included but not well integrated. Could be more 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 0% schema coverage, no output schema, and a truncated description lacking parameter explanation and sibling differentiation, the description is far from complete for an agent to use effectively.

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 'arg' has no description in schema nor in the tool description. The description mentions fields like chain and protocol but does not explain what 'arg' expects. Schema coverage is 0%, leaving the agent completely in the dark.

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 it returns top yield pools with specific fields via DefiLlama, but the sentence is truncated and lacks a clear action verb like 'List' or 'Get'. It is somewhat clear but not fully precise.

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

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

No guidance on when to use this tool versus alternatives such as crypto_defi_tvl or crypto_dex. Missing context about selection criteria or exclusions.

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

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

The description discloses the cost ($0.005–$0.05 USDC per call) and mentions 'live' data, which provides some behavioral context. However, it does not explicitly state that the tool is read-only, nor does it discuss rate limits or authentication, leaving gaps in transparency for a tool with no 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 concise in its first sentence, but it is truncated ('portfo' is cut off), indicating incomplete information. The cost note is an extra sentence that adds value but is not structurally integrated. Overall, it is mostly to the point but suffers from truncation.

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 parameter and no output schema, the description covers the input and the main output fields (TVL, chain, category). However, it is truncated and does not explain the full return structure or any additional details like 'DeFi allocation & portfo', leaving some ambiguity.

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 required string parameter 'arg' with no description (0% coverage). The description compensates by providing concrete examples of valid slugs (aave, uniswap, lido) and stating that the arg is a protocol slug from DefiLlama, clarifying the expected format.

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 live protocol TVL, chain, and category from DefiLlama for a given protocol slug, with examples like aave, uniswap, lido. This distinguishes it from siblings such as crypto_defi_tvl by specifying the data sources and fields, though explicit differentiation is not provided.

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

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

No guidance is given on when to use this tool versus alternatives like crypto_defi_tvl. There is no mention of prerequisites, exclusions, or use cases, leaving the agent to infer usage context from the description alone.

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 cover behavioral traits. It notes live data from DexScreener, 48 chains, and cost, but lacks details on rate limits, authentication, error handling (e.g., symbol not found), or confirmation that it is read-only. It partially compensates but is incomplete.

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

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

Two sentences plus a cost line, very concise. The key information is front-loaded. However, the structure could be improved by separating parameter guidance and output details.

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 of a multi-chain DEX data tool and no output schema, the description is incomplete. It omits output format, pagination, chain filtering, and how to handle multiple results. Sibling tools like crypto_price have more specific descriptions, making this one feel under-specified.

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 one parameter 'arg' with no description (0% coverage). The description hints that 'arg' accepts a symbol or address, but does not clarify format, chain specification, or how to pass multiple. This leaves ambiguity for an agent.

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 returns live token prices, liquidity, and 24h volume from DexScreener across 48 chains by symbol or address. The verb 'returns' and specific data sources set it apart, though it does not explicitly differentiate from sibling tools like crypto_dex or crypto_price.

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. It mentions queries by symbol or address but does not specify formatting, prerequisites, or context where other tools (e.g., crypto_price) would be better. Cost info is provided but not as a usage rule.

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 the cost ($0.005-$0.05 per call), which is a behavioral trait. However, it does not mention other aspects like read-only nature, required authentication, or rate limits, and annotations are absent.

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 short and front-loaded, but it appears truncated ('MC d') which reduces clarity. While concise, the truncation is a structural flaw.

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 a single undocumented parameter and no output schema, the description should clarify input format and return structure. It lists data fields but not output arrangement, and cost is noted but overall completeness is insufficient.

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 'arg' with no description, and 0% schema coverage. The description does not clarify what value 'arg' expects, leaving the agent without guidance on how to call the tool.

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 an FMCSA/SAFER snapshot for carriers, listing specific data fields. The verb 'returns' and resource 'carriers' are specific, and the tool is distinct from siblings like finance_stock or crypto_market.

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 any prerequisites, exclusions, or scenarios where this tool is preferred over 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. The description discloses the cost range, which is useful, but lacks details on rate limits, authentication, destructive nature, or idempotency. The behavioral transparency is minimal beyond pricing.

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 short and front-loaded with the core purpose, but appears cut off at 'ar'. The inclusion of cost is helpful. It earns its sentences but the truncation hurts readability.

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

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

Given the simple input (one string parameter) and no output schema, the description covers the return value, source, and cost. However, it lacks details like example input/output, error handling, or rate update frequency, leaving gaps for full 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 only parameter, `arg`, has no schema description (0% coverage). The description implies it should be a 6-letter currency pair like 'EURUSD', but does not specify format (e.g., case, separator). Adds limited semantic value beyond the schema.

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

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

Clearly states it returns live FX rates (bid/ask/mid) for any 6-letter pair, and mentions ECB reference rates via Frankfurter. It differentiates itself from siblings like finance_stock or finance_treasury, though no explicit sibling comparison is given.

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. The description starts with 'For treasury, payment, ar' but is cut off, providing no usable context. No mention of use cases or constraints.

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 provided, so description must fully disclose behavior. It mentions monetary cost ($0.005–$0.05 USDC per call) but does not state whether the operation is read-only, destructive, or requires authentication. No mention of rate limits, pagination, or how 'largest' is determined.

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?

Description is short (two sentences plus cost) but appears truncated ('For govcon s'). Front-loaded with key purpose, but missing essential details. Every sentence earns its place, but the cut-off harms completeness.

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

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

No output schema exists. Description lists return fields (amount, agency, type, period, description) which is helpful, but does not explain the meaning of 'largest', sorting, limits, or how to interpret results. Parameter semantics are missing entirely. In context of sibling tools, no differentiation provided.

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

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

The input schema has one required parameter 'arg' with no description. Schema coverage is 0%. The tool description does not explain what 'arg' represents or how to use it. This is a critical gap, making the tool effectively unusable from the description 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?

Description states it returns largest federal contract awards with specific fields: amount, agency, type, period, description. Source is USAspending.gov. This clearly distinguishes it from sibling tools that deal with SEC filings, stock, etc. However, the description is cut off ('For govcon s') and title is null, slightly reducing clarity.

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. Does not mention prerequisites, limitations, or if it should be used for specific types of queries. Sibling tools are not referenced.

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 disclose behavioral traits. It only lists returned data and cost, but does not mention whether the tool is read-only, any authentication needs, rate limits, or error behavior. This is insufficient for safe agent usage.

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

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

The description is brief (two sentences, one incomplete) and includes cost information which is useful. However, the cut-off phrase 'For geopolitical' and lack of structure (no bullet points or paragraphs) reduce its effectiveness.

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 is undocumented and no output schema exists, the description should provide more context on the arg and return format. It only vaguely describes outputs, leaving the agent with incomplete information to use 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 input schema has a single required parameter 'arg' with no description and 0% schema coverage. The description does not explain what 'arg' represents (e.g., country name, ISO code). An agent cannot determine how to populate this 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 clearly states the tool returns 'country profile + World Bank projects + live USD exchange rate', which are specific resources. This distinguishes it from sibling tools like finance_forex or finance_sec_filings. However, the phrase 'For geopolitical' is cut off, slightly reducing clarity.

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 (e.g., finance_forex for exchange rates only). It does not mention prerequisites, exclusions, or context. An agent would have to infer usage from the output description.

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

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

With no annotations, the description carries the burden. It mentions monetary cost per call, which is a behavioral trait, but omits authentication requirements, rate limits, or whether the tool is read-only (implied). This leaves significant gaps.

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

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

The description is very concise with two sentences and a cost line. It front-loads the core purpose. No wasted words, but could expand slightly on parameter usage without losing concision.

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?

Lacks explanation of the return format beyond a few fields, no output schema, and no clarity on the parameter. For a simple query tool, the missing parameter semantics makes it incomplete.

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

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

The single parameter 'arg' has no description in the schema (0% coverage) and the tool description does not explain what 'arg' should be (e.g., ticker, company name). The description fails to compensate for the missing schema 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 the tool returns recent 8-K material events with specific fields (date, item codes, document URL) and examples of event types. It differentiates from sibling finance_sec_* tools by focusing on 8-K events, though it doesn't specify the recency timeframe.

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 siblings like finance_sec_filings or finance_sec_recent. The agent must infer from the description alone, which lacks explicit context for 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?

No annotations are given. The description mentions cost and returns data but does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. The truncation further reduces clarity.

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 short but truncated, missing a complete sentence. It includes a cost note, which is useful, but could be more concise and 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?

Given the tool's complexity (multiple profile fields and filings), and no output schema, the description provides limited context. It does not explain the parameter, nor does it differentiate from similar SEC filing tools among siblings.

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 required parameter 'arg' with no description. The tool description does not explain what 'arg' represents (e.g., ticker or CIK). With 0% schema description coverage, the description fails 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 it returns a company profile and 20 recent filings with specific fields, distinguishing it from sibling tools like finance_sec_financials or finance_sec_insider. However, the description is truncated (ends with 'Offic') and lacks explicit differentiation from finance_sec_recent.

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

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

No guidance is provided on when to use this tool versus alternatives like finance_sec_search or finance_sec_recent. There is no mention of prerequisites, exclusions, or typical use cases.

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, description provides only cost range. Missing details on behavior such as handling of missing tickers, rate limits, or whether data is read-only.

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

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

Two sentences, reasonably concise. First sentence front-loads purpose. However, it sacrifices necessary detail on parameters, making it under-specified.

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 parameter and no output schema, description should clarify input and output format. It mentions only output items, not how to specify which company, nor return structure.

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 one undocumented parameter 'arg' with 0% coverage. Description does not explain what 'arg' represents (presumably ticker/company identifier), leaving the agent without necessary input 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?

Description clearly states it returns headline financials (revenue, net income, etc.) from latest annual SEC XBRL. Verb 'returns' and specific resource distinguish it from sibling finance_sec_* 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?

No explicit guidance on when to use this tool vs alternatives like finance_sec_filings or finance_sec_search. Only implicit from its specific output.

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; the description only says it returns data, implying read-only, but does not disclose limitations, authentication needs, or potential issues like data freshness or required permissions.

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?

Short but has a typo ('SEC s' cut off) and includes cost info awkwardly. Could be more polished and 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?

For a simple tool with one parameter, the description fails to explain the required input, leaving a major gap. No output schema provided.

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

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

The only parameter 'arg' is completely undocumented in both schema and description. With 0% schema coverage and no param explanation, the agent cannot determine what to pass (e.g., ticker, CIK, name).

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 returns insider trades with specific SEC forms (4/3/5), actors (directors/officers), transaction details (dates, shares, prices, URLs), distinguishing it from siblings like finance_sec_filings or finance_sec_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?

No guidance on when to use this tool versus alternatives. No context about when it is appropriate or when to avoid 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?

No annotations are provided, so the description carries full burden. It mentions cost ($0.005-$0.05) which is helpful, but does not disclose whether the operation is read-only, requires authentication, or any side effects. The description is also truncated.

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 (two sentences plus cost), but it is truncated ('Offi') and does not front-load the most important information (what the parameter is). The cost line is useful but could be integrated.

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 parameter with no explanation and no output schema, the description should clarify the argument's purpose and return format. It only lists filing types, leaving the parameter and output ambiguous.

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

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

The schema has one required parameter 'arg' with no description and schema coverage is 0%. The description does not explain what 'arg' should contain (e.g., a CIK, ticker, or date). This is a critical 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 that the tool returns latest marketwide SEC filings, listing specific types (S-1 IPOs, 8-K events, etc.), which gives a clear verb-resource purpose. However, it does not explicitly differentiate from sibling tools like finance_sec_filings or finance_sec_events, so it's not a 5.

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

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

The description implies the tool is for getting recent SEC filings broadly, but provides no guidance on when to use it versus alternatives (e.g., finance_sec_search, finance_sec_events). There are no explicit conditions or exclusions.

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

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

The description adds the cost range ($0.005–$0.05) and data time range (2001-present), providing useful behavioral context beyond what annotations would convey. However, it does not disclose pagination, rate limits, or result limits, leaving gaps.

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 short but includes cost info, which is helpful. However, it appears truncated ('For co'), reducing clarity. It is front-loaded with purpose but loses points for the incomplete sentence.

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

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

While the description lists returned fields, it lacks output schema, parameter info, and enough context for a search tool with many siblings. The tool's behavior and expected input are insufficiently specified for reliable 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 single parameter 'arg' is completely undocumented in both the schema and description. Schema description coverage is 0%, and the description adds no meaning about what 'arg' expects (e.g., search query, CIK, etc.), failing to help the agent.

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 SEC filings with specific fields and notes it's full-text search, which gives a good sense of purpose. However, it does not differentiate from sibling tools like finance_sec_filings, which may have overlapping functionality.

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 its siblings. The mention of 'Full-text search' hints at a use case but lacks explicit when-to-use or when-not-to-use instructions.

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 adds cost information ($0.005–$0.05 USDC per call), which is beyond a simple read operation. However, it does not disclose any behavioral traits like rate limits, authentication requirements, or error handling.

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 concise but is cut off ('portfoli...'), which harms clarity. It front-loads the main return fields and adds cost separately.

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 with no description and no output schema, the description is incomplete. It fails to specify the required input format (e.g., stock ticker) or return structure, making it difficult for an agent to invoke correctly.

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

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

The input schema has 0% coverage for parameter descriptions, and the tool description does not explain what the required 'arg' parameter represents. It likely expects a stock symbol, but this is not stated.

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 returns a live quote with specific fields (price, 24h change, etc.) and mentions Yahoo Finance. It indicates it's for equity trading, distinguishing it from sibling tools like finance_forex or crypto_price.

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 vs alternatives. The description only says 'For equity trading' but does not provide context on when not to use it or mention alternative 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 description should disclose behavioral traits. It mentions cost and source but lacks information on read-only nature, authentication requirements, rate limits, or side effects beyond returning data.

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

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

The description is very short and front-loaded with the main purpose, but it omits essential details about the parameter, making it incomplete despite being 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?

Given the tool has one opaque required parameter and no annotations or output schema, the description is insufficient. It provides data categories and cost but does not explain how to invoke the tool correctly.

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

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

The sole parameter 'arg' is required but completely undocumented in both schema and description. With 0% schema coverage, the description should explain what 'arg' expects, but it does not, leaving the agent guessing.

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 returns live US Treasury data including specific categories like interest rates and federal debt, with a specific verb 'Returns' and resource 'US Treasury data'. It distinguishes from siblings like finance_forex and crypto_treasury, though the mention of ECB source might cause slight confusion.

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. The phrase 'For macro trading' is vague and doesn't provide comparative context against siblings like finance_macro or finance_forex.

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 fully carries the behavioral burden. It declares the action (return snippets), the scope (multiple platforms), and an important trait (free). No contradictions or hidden behaviors are present.

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

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

The description is a single sentence that is concise and front-loaded. Every word adds value: verb, object, target platforms, and the 'free' attribute. No unnecessary information.

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

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

For a zero-parameter, no-output-schema tool, the description is complete. It fully specifies what the tool returns and for which environments. No additional context is needed.

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%. The description does not need to add parameter meaning, as there are none. Baseline 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 explicitly states the tool returns ready-to-paste configuration snippets for installing this MCP server in six named platforms, using a specific verb ('Return') and resource ('configuration snippets'). It clearly distinguishes from siblings like 'list_endpoints' or 'pricing_info'.

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 when one needs installation snippets for the listed platforms. It does not explicitly mention when not to use or provide alternatives, but given the zero-parameter nature and clear purpose, the usage context is well implied.

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 provided, so description carries full burden. It discloses that listing is free and requires no wallet, indicating no destructive behavior. However, lacks details on response format or 'live status' meaning.

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 with no fluff, front-loading purpose and immediate usage guidance.

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

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

Given zero parameters and no output schema, description covers purpose, usage, and behavioral expectations. Could briefly define 'live status' 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?

Zero parameters, schema coverage 100%, so no need for param details. Baseline of 4 applies.

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

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

Description clearly states it lists paid endpoints with prices and live status. It explicitly says to use first to discover tools, distinguishing it from sibling tools that are specific endpoints.

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 says 'Free — no wallet required' and 'Use this first to discover what tools are available,' providing clear context and sequential guidance. No exclusions needed for a discovery tool.

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 provided, so description carries burden. It discloses that the tool is read-only and mentions cost ($0.005–$0.05 USDC per call), but does not discuss rate limits, authentication, or data source. Adequate but incomplete for 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?

Description is concise and front-loaded with the core purpose. However, it appears cut off (ends with 'Re') and could be slightly more structured. Cost information is included inline.

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; description lists four metrics but does not explain the 'verdict' or format of the return value. Given the tool's moderate complexity and lack of annotations or output schema, more details on what the agent should expect 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 coverage is 0%, and the only parameter 'arg' lacks description. The description adds meaning by stating the tool works for 'any US state or ZIP', implying arg accepts state names or ZIP codes. However, it does not clarify format (e.g., 'CA' vs 'California') or whether multiple inputs are valid.

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 clearly states the tool returns specific metrics: home-price-to-income ratio, rent-to-income %, live 30-yr mortgage estimate, and verdict for any US state or ZIP. It distinguishes from sibling tools like market_compare or market_profile by focusing on affordability.

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 such as finance_macro or market_profile. The description does not provide context for appropriate use cases or exclusions.

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

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

No annotations are provided, so the description must disclose behavior. It mentions the return of a comparison but does not cover data freshness, error handling, or prerequisites. The cost note ($0.005–$0.05 USDC) adds some transparency, but overall insufficient.

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

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

The description is very short but incomplete (cut off) and includes a cost note that interrupts the flow. It lacks a proper sentence structure and does not fully convey the required 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 the tool's complexity (multiple metrics for comparison) and the lack of output schema, the description is severely lacking. It does not specify input format, output structure, or any constraints. The sibling tools are not differentiated.

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

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

The schema has one parameter 'arg' (string) with 0% description coverage. The description does not explain what to pass as 'arg' (e.g., market names, ZIP codes, IDs). This is a critical gap, as the tool cannot be used correctly without this information.

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 it returns side-by-side market comparison with specific metrics (population, density, wage, etc.), which gives a clear purpose. However, it is cut off after 'for two US', leaving ambiguity about the entities (likely cities or markets) being compared. Mildly incomplete but still conveys the main action.

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 sibling tools like market_profile or market_rank. There are no exclusions or context for appropriate use. The description only describes what it does, not when it's 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?

No annotations are provided, so the description carries the full burden. It mentions the output (count, share %, diversity verdict) and cost range, but lacks details on idempotency, authentication, rate limits, or data freshness. 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?

The description is short but includes an incomplete sentence. The cost info is relevant but could be placed elsewhere. Overall, it is not overly verbose, but the truncation harms structure.

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 parameter and no output schema/annotations, the description should fully explain input and output. It describes output well but completely omits input semantics. This makes it insufficient 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?

The input schema has a single required parameter 'arg' with 0% description coverage. The tool description does not clarify what 'arg' should be (e.g., a state/county name or code). This is a critical gap, as the agent cannot infer the correct input format.

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 returns top industry sectors by count, share %, and diversity verdict for US states or counties. This is specific and distinguishes it from sibling tools like market_affordability or market_saturation. However, the description is cut off ('Economic-development & in'), slightly reducing clarity.

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 US states or counties, but provides no guidance on when to use this tool versus alternatives, nor any conditions or exclusions. Usage context is implied 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 provided, but the description includes cost information ($0.005–$0.05 USDC per call). It does not disclose auth requirements, rate limits, or any destructive behavior. The cost is a useful transparency addition, but other behavioral aspects are missing.

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 short and includes a cost note, but it is cut off and mixes a usage hint with pricing. It could be more structured and complete without unnecessary 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 and minimal parameter info, the description should explain the output format or return structure. It lists metrics but does not specify how they are returned (e.g., object with keys). The tool is simple but the description is insufficient for complete 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 single parameter 'arg' is a required string with no description in the schema (0% coverage). The description does not explain what to input (e.g., state name, abbreviation, or FIPS code), leaving the agent uncertain how to invoke the tool correctly.

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 clearly states it returns a market-vitality profile with specific metrics (businesses-per-capita, jobs-per-capita, etc.) for US states. The purpose is specific and distinct from siblings like market_saturation or market_affordability, but it is cut off and could be more explicit about the geographic scope.

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 like market_saturation or market_affordability. The description does not mention contexts where this aggregate profile is preferred over more focused 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. The description adds cost information ($0.005–$0.05 USDC) but does not disclose read-only behavior, rate limits, data freshness, or side effects. For an unannotated tool, this is insufficient.

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 fluff. The first sentence delivers the core purpose; the second provides cost. Structure is clean and front-loaded, though the cost line could be separated or formatted.

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

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

Given a single parameter, no output schema, and no annotations, the description should cover parameter format, output structure, and industry specification. It omits these, leaving significant gaps for an agent.

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

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

The input schema has only one parameter 'arg' with no description and 0% coverage. The description implies 'arg' is an industry NAICS code but does not specify format, examples, or allowed values. It adds no meaningful semantics beyond the bare 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 verb 'returns', the resource 'US states ranked by per-capita business density', and the scope 'for any industry (NAICS)'. It distinguishes the tool from siblings like market_saturation by specifying a ranking and per-capita metric.

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 like market_saturation or market_profile. The description mentions 'any industry (NAICS)' but does not clarify prerequisites, exclusions, or context for 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?

No annotations are provided, so the description carries the full burden. It mentions 'live' odds and the cost range, but lacks details on rate limits, data freshness, or whether results are aggregated. Some transparency is present but incomplete.

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

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

The description is concise with two sentences, front-loading the main purpose. A minor typographical issue ('Tr') is present, but 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?

Despite the tool's complexity in returning prediction odds, there is no output schema or description of the return format. The parameter lacks detailed explanation. Cost information is helpful, but overall completeness is low.

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

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

With 0% schema coverage, the description indicates the 'arg' parameter is a keyword search term, adding some meaning. However, it fails to specify format, case sensitivity, or provide examples, leaving ambiguity.

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 returns live prediction-market odds from Polymarket, specifically implied probabilities and 24h volume for keyword searches. This is a specific verb and resource, distinguishing it from sibling tools like predict_events.

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 guidance on when to use this tool versus alternatives such as predict_orderbook or predict_trades. There is no mention of when not to use it or context about its scope.

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 mentions the return type (index and verdict) and cost, but does not indicate if it is a read operation, whether it requires authentication, or any side effects. The cost information is helpful but insufficient for full transparency.

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 concise with two sentences plus a cost note. However, the presence of 'Fran' appears to be a typo or truncation, which detracts from structure. The purpose is front-loaded, which is good.

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 there is no output schema, the description partially explains the return value (index and verdict). However, the single parameter is not properly defined, and the tool context (industry, place) is not mapped to the parameter. The description is incomplete for a tool with only one undocumented parameter.

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%, but the description fails to explain what the single parameter 'arg' represents. It mentions 'by NAICS code' but does not explicitly state that 'arg' is the NAICS code or the format expected. This leaves the parameter meaning ambiguous.

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 a saturation index and verdict for an industry in a US place by NAICS code. This distinguishes it from sibling tools like market_affordability or market_industry_mix. However, the sentence appears cut off after 'Fran', which slightly reduces clarity.

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

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

No guidance is provided on when to use this tool versus alternatives. While the description implies it is for saturation analysis of industries, it does not explicitly state when to choose it over siblings such as market_compare or market_profile.

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 monetary cost ($0.005-$0.05 per call), which is valuable, but does not mention read-only/destructive nature, authorization, rate limits, or whether the tool is idempotent. This is insufficient for a tool with no annotation support.

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 short and front-loaded with purpose, but it contains a typo (cut-off 'ag' after 'forecasting') which detracts from clarity. Every sentence provides information (bundle content and cost), but the typo and lack of param info reduce effectiveness.

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 as a composite data retrieval tool with 1 parameter and no output schema, the description should fully enable correct invocation. It states the data returned and cost, but omits the parameter's purpose, making the description incomplete for successful use.

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

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

The input schema has one required 'arg' parameter with 0% description coverage, and the description does not explain what 'arg' should contain (e.g., market ID or slug). The description fails to compensate for the lack of schema documentation, leaving the agent to guess the parameter semantics.

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 is a premium bundle of Polymarket data including top market, live odds, order-book depth, and recent trades. It distinguishes itself from sibling tools (e.g., predict_events, predict_orderbook, predict_trades) by explicitly being a composite of these into one call.

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 when a comprehensive view of a prediction market is needed, and mentions it's a 'bundle' as opposed to individual endpoints. However, it lacks explicit when-not guidance or direct comparison to siblings (e.g., when to use predict_360 vs. calling individual 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?

With no annotations, the description carries full burden but only mentions return type and cost. It does not disclose data freshness, pagination, rate limits, or any other behavioral traits. The cost mention is helpful but insufficient for full transparency.

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 but appears truncated ('Forecasting & trading agents d'). While concise, the truncation harms clarity. Every part is used, but structure is not optimized.

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 enumerates return components (event groups, live markets, outcomes, implied odds), which helps. However, it lacks detail on return format, examples, or handling of no results. For a tool with one parameter, it is adequate but not 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 single parameter 'arg' has no description in the schema (0% coverage). The description implies it is a keyword for search, adding some meaning. However, it does not specify format, allowed values, or constraints.

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 returns Polymarket event groups, live markets, outcomes, and implied odds for any keyword. The verb 'Returns' and specific resource list make the purpose clear, but it does not explicitly differentiate from sibling tools like predict_orderbook or predict_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?

No guidance is provided on when to use this tool versus alternatives, nor are there any exclusions or prerequisites mentioned. The description lacks context for usage decisions.

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 description must disclose behavior. It mentions cost ($0.005–$0.05 USDC) and that it's live data, but omits whether it's read-only, side effects, or rate limits. Cost disclosure is helpful but safety traits are missing.

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 somewhat concise but appears truncated (ends with 'fo'), suggesting missing text. This reduces clarity and professionalism.

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 1 parameter and no output schema, the description covers purpose and cost but lacks return value details, error handling, or format. It is minimally adequate but not 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 0% with parameter 'arg' having no description. The description adds that it expects a valid Polymarket token ID as a string, which provides meaning beyond the schema's bare 'Arg' title, but lacks format or example.

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 returns live bid/ask depth from Polymarket CLOB, specifying the resource and verb. It distinguishes itself from sibling tools like predict_trades and crypto_price by focusing on order book depth.

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 tells agents they must input a valid Polymarket token ID, providing a clear prerequisite. However, it doesn't explicitly state when to use this tool over alternatives, though the niche (depth) is implied.

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, leaving the description to carry full behavioral disclosure. It adds cost transparency ($0.005–$0.05 USDC) but fails to specify number of fills returned, ordering, real-time nature, rate limits, or error handling for the 'arg' parameter.

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

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

The description is two sentences plus a cost line, front-loading key information without wasted words. It is appropriately sized for a simple tool.

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

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

Given no output schema or annotations, the description covers the input (keyword) and output (fills with fields). However, it lacks details on output quantity, ordering, update frequency, and error conditions, leaving moderate gaps.

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 provides only a string 'arg' with 0% description coverage. The description adds meaning by stating the arg is a keyword for matching the top market, which tells the agent how to use the parameter, though format details are missing.

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

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

The description clearly states the tool returns Polymarket fills (side, price, size, time) for the top market matching a keyword. This specific verb+resource combination distinguishes it from siblings like predict_events (events) and predict_orderbook (orderbook).

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 fill data related to a keyword, but does not explicitly provide when to use or avoid this tool compared to alternatives. No exclusionary guidance is given.

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 does not explicitly mention safety (read-only) or lack of side effects. However, the term 'Return' suggests a read operation, and it briefly notes it is free, which adds some 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, efficient sentence that conveys all necessary information without any fluff. It is 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 zero parameters, no annotations, and low complexity, the description is complete. It lists the key return items despite lacking an 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?

There are zero parameters, so the baseline is 4. The description adds value by explaining what the tool returns, which is not evident from the schema 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?

The description clearly states it returns pricing details for the GoCreative Agent API, listing specific items (base price, premium endpoints, cache TTLs, payment networks). It distinguishes itself from sibling tools, which are focused on other functionalities like AI, crypto, or endpoints.

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 obtaining pricing info and notes it is free, but does not explicitly state when not to use it or mention alternatives. However, the context of sibling tools makes it clear this is the go-to for pricing queries.

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 a cost range ($0.005–$0.05 USDC) but omits other behavioral traits such as result aggregation format, rate limits, authentication needs, or caching behavior. This is insufficient for a multi-source 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 short and front-loaded with the core purpose, but it is truncated ('in ONE ca'), which undermines readability. The cost note adds value but could be integrated more cleanly.

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?

Despite the tool's complexity (meta-search across many platforms), the description lacks details on return format, pagination, error handling, or result limits. No output schema is provided, and the single parameter is not documented. The cost information is useful but does not compensate for the missing context.

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 required parameter 'arg' with 0% description coverage. The description does not explain what 'arg' represents or its constraints; its role as a search query is only implied by the tool name and description. The description fails to compensate for the missing schema documentation.

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 is a 'multi-platform meta-search' covering multiple sources (web, GitHub, Hacker News, etc.), which effectively communicates the tool's purpose and distinguishes it from sibling tools like 'search_web' or 'search_github'. However, the sentence is truncated ('in ONE ca'), slightly reducing clarity.

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 for broad cross-platform searches, and the sibling list includes platform-specific search tools, suggesting when to use this vs. alternatives. However, it does not explicitly state when not to use it or provide direct comparison.

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 are absent, so the description carries full burden. It discloses cost and data source but not other behavioral traits like rate limits, error handling, or that results are limited to 'recent' papers. The description is minimal.

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-loads purpose, and includes cost information. Every sentence is necessary; 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 the simplicity (one parameter, no output schema), the description is adequate but incomplete. It fails to specify input format or output structure, and does not mention pagination or result count.

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

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

The schema has one required parameter 'arg' with 0% description coverage. The description says 'for a query' but does not clarify what 'arg' should contain (e.g., search term, title, author). No format or examples 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 'Recent academic papers for a query' and lists fields (title, authors, journal, year, DOI, citations) and the data source (Crossref). This provides a specific verb+resource, but it could be more differentiated from the sibling 'research' 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?

The description mentions cost, which is helpful for budgeting, but gives no guidance on when to use this tool vs alternatives, prerequisites, or 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?

No annotations are provided. The description mentions cost but lacks disclosure of rate limits, authentication requirements, error behavior, or side effects. The single parameter 'arg' is unexplained, leaving behavioral traits ambiguous.

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

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

The description is brief (two sentences) but front-loads functionality and cost. However, the second sentence appears truncated ('Arbitr...'), and the lack of parameter documentation makes it less 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?

No output schema, one undocumented parameter, and no annotations. For a tool making network calls across 48 chains, the description omits essential usage details like response format, parameter format, or error handling.

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 0%: the sole required parameter 'arg' has no description in the schema, and the tool description does not clarify what 'arg' should contain (e.g., JSON-RPC method, chain ID, or address). This is a critical 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 that the tool returns native balance, tx count, contract check, block & gas price via JSON-RPC across 48 EVM chains. The verb 'Returns' and resource enumeration provide good clarity, though it doesn't explicitly distinguish from siblings like crypto_price or crypto_chains.

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. Sibling tools exist (e.g., crypto_price, crypto_gas) but no differentiation or context 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?

With no annotations provided, the description carries full burden but only mentions cost (behavioral trait) and data fields. It omits whether the tool requires authentication, its read-only nature, rate limits, or any side effects. The cost note is helpful but incomplete.

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

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

The description is short and front-loaded with purpose, but appears truncated ('For dev a') which is a structural flaw. The cost note adds extra but non-essential 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 no output schema and low schema coverage, the description fails to specify the return structure, pagination, error handling, or input formatting (e.g., exact keyword syntax). The truncation further reduces 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 schema has 0% description coverage, but the description implies that the single required parameter 'arg' is a keyword for searching repos. This adds some meaning beyond the bare schema, though no format or constraints are stated.

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 'GitHub repository discovery' with specific fields (name, language, description, forks, topics) and identifies the action as searching by keyword. This distinguishes it from sibling search tools like search_web or search_youtube, though the truncation slightly undermines clarity.

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 (e.g., search_web for general web or other GitHub-specific tools). No prerequisites, context, or exclusion criteria are mentioned, leaving the agent without decision support.

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 mentions cost and returns top posts, but does not cover rate limits, authentication requirements, or whether the tool is read-only. For a tool with no annotation, this is insufficient.

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 short and front-loaded with purpose, but appears truncated (ends with 'trend-discov') which makes it incomplete. If complete, it would be efficient, but as provided, it suffers from missing content.

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 parameter (0% schema coverage) and no output schema, the description must cover both input and output adequately. It mentions output fields and cost, but lacks clarity on the input parameter (e.g., data type, required format) and behavioral aspects like pagination or rate limits. This leaves significant gaps for an agent.

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

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

The single parameter 'arg' has no schema description (0% coverage). The description implies the parameter is a hashtag ('for any hashtag'), adding some meaning beyond the generic name. However, it does not specify format, required format (e.g., with or without #), or case sensitivity.

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 top Instagram posts for a hashtag and lists specific output fields (post URL, caption, engagement, timestamp). It distinguishes from siblings like search_tiktok_hashtag by focusing on Instagram. However, the description is cut off and lacks an explicit verb like 'retrieves' or 'searches'.

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 vs alternatives such as search_tiktok_hashtag or search_youtube. Only cost information is provided, which is useful but does not help an agent decide based on 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?

Discloses main behavior (geocoding, outputs) and cost per call, but lacks details on rate limits, authentication, error handling, or scope limitations. No annotations to supplement.

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 plus cost line, immediately front-loading purpose and output. No 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?

Covers purpose and return values, but fails to document the single input parameter or describe output structure. Without output schema or annotations, this is a noticeable gap for a simple 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?

Only one parameter 'arg' with 0% schema coverage. Description does not explain what to input (e.g., place name, address) or expected format, leaving the agent to guess.

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 clearly states geocoding (verb) for places/addresses (resource) using OpenStreetMap, and lists outputs (full address, category, lat/lng). It distinguishes from sibling search tools which focus on other domains.

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?

Mentions 'For maps, logistics' as use cases, but does not explicitly exclude when not to use or mention alternatives. However, no sibling tool performs geocoding, so implicit distinction is 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 bears full responsibility. It mentions return fields and cost but lacks behavioral details such as read-only nature, rate limits, or authentication requirements. Minimal 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?

Description is relatively short but appears incomplete (ends mid-word 'soc'). It conveys core information but lacks completeness and proper structure due to truncation.

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 minimal schema, no output schema, and no annotations, the description is insufficient. It provides a high-level purpose but omits crucial details like parameter format, usage context, and behavioral constraints.

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?

Single parameter 'arg' has zero description in the input schema. The description mentions 'any hashtag' but does not clarify expected format (e.g., with/without #) or constraints. Schema coverage is 0%, and description fails 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?

Description clearly states tool retrieves top TikTok videos for any hashtag, listing specific fields returned. Distinguishes from sibling tools like search_instagram_hashtag by focusing on TikTok. However, the description appears truncated, slightly reducing clarity.

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 or alternatives. The description implies use for TikTok hashtag search, but does not specify when not to use or provide instructions relative to 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 burden. It discloses that results are ranked with title, URL, and snippet, and also mentions cost. However, it does not address rate limits, authentication, or other behavioral aspects beyond the output format.

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 but contains a cut-off word ('prospe') that suggests an incomplete thought. It is structured with a dash separating the main purpose from the cost note. Could be slightly more polished.

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 (one parameter, no output schema, no annotations), the description adequately covers its basic purpose and cost. However, it lacks details on return format pagination, error handling, or scope of search results.

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 'arg' is documented in schema but with 0% coverage in description. The description says 'for any query', which provides minimal guidance. It does not specify required format, length, or 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 tool performs web search returning ranked results (title, URL, snippet). It also mentions its role as a core discovery primitive for lead generation and prospecting. However, it does not explicitly differentiate from the sibling tool 'web', which may serve a similar purpose.

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 lead generation and prospecting but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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 provides no behavioral information such as auth requirements, rate limits, pagination, or what the tool returns. As there are no annotations, the description carries full burden for transparency but fails entirely.

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 short, but this is due to omission rather than conciseness. It is under-specified and does not provide value. There is no structure beyond a cost note.

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 required parameter and no output schema, the description is woefully incomplete. It does not explain how to use the parameter, what results to expect, or any behavioral traits. The tool is effectively undocumented.

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 'arg' has no description in the schema (0% coverage). The description does not explain what the parameter represents, its expected format, or any constraints. This leaves the agent guessing.

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 'YouTube Search Results' is a noun phrase that essentially restates the tool name. It does not specify a clear action or resource, and fails to differentiate from siblings like search_web which may also return YouTube content.

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

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

No guidance is provided on when to use this tool versus alternatives. The only additional information is cost, which is not a usage guideline. Sibling tools are numerous and include other search tools, making this omission critical.

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 provided, so description bears full burden. It states it returns stats and is free, but does not disclose any behavioral traits like rate limits, data freshness, or side effects. Since it's a read-only stats call, it is acceptable but not thorough.

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 wasted words. Front-loaded with action and content. 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?

Given zero parameters and no output schema, the description covers the purpose, content, and use case. Lacks return format or examples, but the low complexity makes it mostly 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?

No parameters exist, so baseline is 4. Description adds no parameter info, but none 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?

Description clearly states the verb 'Return' and resource 'summary stats of how this MCP server has been used', listing specific content (top tools, success rate, recent activity). It distinguishes from sibling tools which are functional tools, while this is a meta-usage 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?

Explicitly says 'Use to verify your own integration is hitting the right tools', providing a clear use case. Lacks explicit 'when not to use' or alternatives, but the context is sufficient for a simple tool.

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 provided, but the description fully explains the tool's behavior: it returns instructions. No side effects or complex behavior to disclose.

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 fluff. Purpose and usage are immediately clear. Efficient 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 no input/output schema and no annotations, the description adequately covers all needed context. Sufficient for agent to select and 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?

No parameters exist, so schema coverage is 100% trivial. Description adds no param info, but none needed. Baseline of 4 for zero-parameter tools.

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 step-by-step instructions for setting up x402 USDC autopay. It distinguishes from sibling tools (e.g., AI, defi) by focusing on payment setup.

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 tells when to use: after a 402 error or when onboarding a new agent needing payment. Also mentions it is free, aiding decision.

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. The description only discloses cost ($0.005–$0.05 per call) but omits behavioral traits like rate limits, data source freshness, or response format. The description carries the full burden and is insufficient.

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

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

The description is concise and front-loaded with the tool's purpose. Cost information is provided separately. Every sentence adds value, though it could be slightly more 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?

For a simple web lookup tool with one parameter and no output schema, the description covers basic purpose and cost but lacks details on return format, pagination, or error handling. Adequate but with gaps.

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% description coverage for the 'arg' parameter. The description implies it is a query for DuckDuckGo, but does not clarify format, length limits, or special characters, leaving ambiguity.

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 performs web lookup via DuckDuckGo, offering instant answers, definitions, and related topics. However, it does not explicitly distinguish from sibling tools like 'search_web', limiting differentiation.

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 'For research, fact-check, and defini...' implying use cases, but provides no explicit guidance on when to use this tool versus alternatives or 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?

No annotations are provided, so the description carries full burden. It describes output fields but omits behavioral traits such as authentication requirements, rate limits, side effects, or error handling. The cost mention is useful but insufficient for full transparency.

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 short and front-loads key information, but the second sentence appears truncated ('For social-intel, le'), reducing clarity. The cost line adds value but could be integrated.

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

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

With no output schema, the description should detail the return structure. It lists some fields but incompletely. The missing parameter explanation and incomplete sentence leave gaps for a simple tool.

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

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

Schema coverage is 0%, and the description does not explain the single required parameter 'arg'. The hint 'for any handle' suggests it expects a Twitter handle, but no explicit mapping is provided, leaving the agent to infer.

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

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

The description clearly identifies the tool as a 'X/Twitter profile snapshot' and lists specific data fields (followers, bio, verified status, post count, following). It distinguishes itself from sibling tools, none of which focus on Twitter profiles.

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

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

The description states it is 'for social-intel' and mentions cost, implying use for social intelligence gathering. While it does not explicitly exclude alternatives, the uniqueness among siblings makes usage context clear.

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