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

No annotations are provided, so the description carries the full behavioral burden and does so well: it discloses the trial quota per installation, that exhaustion returns 402 and is reported rather than faked, and that results come with a hub-signed receipt nonce verifiable against the published key. It does not disclose possible side effects of the invoked capability, which is the remaining gap.

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

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

Four sentences, front-loaded with the core action, and every sentence earns its place: trial tier, verifiability, quota/402 behavior, paid-access exclusion. No filler or repetition of the schema.

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 an output schema present, return values need not be spelled out, and the description covers the operational essentials an agent needs (quota limits, error semantics, verifiability, paid-path exclusion) alongside fully documented parameters.

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

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

Schema description coverage is 100%, so parameters (including the non-obvious product_id and source_hub federation caveats) are already documented. The description adds no parameter-level guidance beyond the schema, so the baseline of 3 applies.

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

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

States a specific verb+resource with scope: 'Run one capability from market_search on the hub's free trial tier.' It explicitly grounds the tool against the sibling market_search_tool (this invokes what that one discovers), so an agent can distinguish them without opening schemas.

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

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

Clear context: use after market_search, on the free trial tier, and a when-not (paid access requires on-chain escrow, deliberately unavailable here). It does not name an alternative tool to use for paid access, but the trial/no-trial boundary is well stated.

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

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

With no annotations the description carries the full burden, and it does well: it discloses zero cost/auth requirements, the shape of returned metadata, the search-is-exhaustive semantics behind an empty result, and the AIMARKET_HUB_URL override for pointing at another hub. It leaves out ranking/ordering behaviour and what the trust score means, so it is strong but not exhaustive.

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

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

Front-loaded with the core purpose, then caveats in descending order of importance (free, return shape, empty-result semantics, config override). Every sentence carries information and nothing is padded.

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?

An output schema exists, yet the description still gives the agent enough to act: what a call costs, what comes back, what an empty result means, and where the next call goes. Nothing needed to call or interpret it correctly is missing.

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

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

Schema description coverage is 100% (limit, intent, category, max_price_usd are all documented with defaults and examples), so the schema already does the work. The description adds no parameter-level detail such as how intent is matched or how max_price_usd interacts with the returned prices, making this baseline territory.

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?

Specific verb and resource ('Discover paid AI capabilities listed on an AIMarket hub, with prices') with the scope made explicit. It also names the downstream sibling ('pass both ids to market_invoke to run one'), which separates it cleanly from market_invoke_tool and the generic web_search_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?

Clear context for use: it is free, needs no wallet/key/payment channel, and the next step is stated. The empty-result rule ('the hub lists only capabilities it can actually execute, so an empty result means it genuinely does not sell that') is genuinely useful guidance. However, it never states when to prefer this over web_search_tool or metis_verify_tool, so no explicit alternatives 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, so description carries burden. It explains the response includes machine-readable metadata and fail-closed behavior. Could add more on 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?

Three short sentences, front-loaded with purpose, efficient.

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

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

Given schema and output schema, description adds configuration and behavioral notes. No major 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?

Schema coverage is 100% so baseline is 3. Description adds little beyond schema: mentions route enum options but schema already enumerates them.

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 runs Metis cognition and verification, returns answer plus verify_score/verified, and names the API endpoint. Siblings are web tools, so no 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?

Describes configuration and that it calls a specific API, but does not explicitly state when to use or not use versus alternatives. However, context is clear enough.

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?

Despite no annotations, the description provides substantial behavioral details: SSRF hardening (scheme allow-list, private-IP block, per-redirect re-validation), size cap, output sanitization, role-marker stripping, and untrusted wrapping. This goes beyond the basic fetch 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?

Two sentences, no redundant words. The purpose is stated first, then detailed safety and output handling. Every sentence provides 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 the tool's moderate complexity, the description covers core functionality, safety constraints, and output format. With an output schema present, return value explanation is unnecessary. Could mention caching or rate limits but not critical.

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

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

Schema coverage is 100% with clear descriptions. The tool description reinforces safety context (SSRF, size cap) that adds value beyond the schema, especially for the url parameter which warns about private IPs.

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 'Fetch a web page by URL and return its main text content', with a specific verb and resource. It distinguishes itself from sibling tools (web_search_tool for searching, metis_verify_tool for verification) by focusing on direct URL fetching.

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?

While the description implies usage for fetching known web pages, it does not explicitly contrast with sibling tools or provide when-to-use vs when-not-to-use guidance. The agent must infer from 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 backend (DuckDuckGo HTML) and output sanitization/wrapping (<untrusted>). No annotations provided, so description carries burden; it gives useful context but omits potential rate limits or result count limits.

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

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

Three sentences, no wasted words. Front-loaded with purpose. Every sentence adds value.

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

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

Tool is simple with one param. Description covers backend, output format, and usage context. Output schema exists but description doesn't detail full return structure; however, 'top result snippets' and wrapping info suffice.

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 'query' has schema description (100% coverage). Description adds an example and context ('natural-language', 'live web facts'), enhancing meaning 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?

Description clearly states verb ('search'), resource ('web'), and output ('top result snippets'). Differentiates from siblings by recommending use over guessing for recent 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?

Explicitly states when to prefer this tool ('when the answer depends on recent events or documentation'). Lacks explicit exclusions or when not to use, but the positive guidance is clear.

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