agentready

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

No annotations are provided, so the description carries the full burden. It describes the search mechanism (full-text, ranked, blended with scores) and output (best matches with report links). However, it does not mention rate limits, data freshness, or whether the tool is read-only. It is adequate but lacks deeper behavioral context.

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

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

Two sentences, 25 words total. The first sentence states the core purpose and example, the second adds detail on search approach and output. No redundant or filler words; 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 the simplicity (2 params, no output schema, no annotations), the description covers the main points: purpose, input, search method, and output. It lacks details about product attributes or score interpretation, but for a search tool this level is sufficient. Output schema absence is mitigated by describing returns as 'best-scoring matches with report links'.

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

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

Schema coverage is 100%, baseline 3. The description adds value by providing an example for 'intent' ('send transactional email') and defining it as 'what you're trying to accomplish, in plain words', which clarifies usage. The 'limit' parameter is not expanded but is clearly described in the schema.

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

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

The description clearly states the tool's purpose: 'Find agent-ready products for a task intent'. It specifies the input (intent) and output (best-scoring matches with report links). 'Discover_products' is distinct from sibling 'search_capabilities' as it focuses on products with agent-readiness scores.

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 explains when to use the tool: 'for a task intent (e.g. 'send transactional email')'. It implies usage context (finding agent-ready products) but does not explicitly state when not to use it or compare to siblings like 'search_capabilities'.

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 explicitly notes that check IDs are stable and suggests gating CI on explicit ID lists, which is a valuable behavioral insight. However, it does not disclose other traits like idempotency, caching, or auth needs.

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 wasted words. The first sentence front-loads the purpose, and the second adds an essential behavioral insight. 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 the tool has no parameters and no output schema, the description provides a thorough list of what the catalog contains (ids, layers, weights, tiers, fix guidance). It also adds a practical note about stability. This is sufficient for an agent to understand the tool's 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 zero parameters, and schema description coverage is 100%. The description adds no parameter info, but with zero parameters the baseline is 4. The description does not need to explain parameters.

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

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

The description clearly states that the tool returns 'the complete catalog of scanner checks' with specific attributes (stable ids, layers, weights, tiers, fix guidance). It uses a specific verb-resource pair and inherently distinguishes from sibling tools like get_feedback or get_skill.

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 the full list of scanner checks, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention cases where it should not be used.

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 behavior. It mentions read operation ('Read') and the data types returned, but does not state whether changes are made (though implied not), any side effects, rate limits, or access requirements. The 'Read' verb implies idempotence but is not explicit.

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

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

The description is two sentences, front-loaded with the core purpose and key outputs, followed by a usage note. No redundancy or unnecessary words. It earns its space.

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 compensates by naming returned fields (success rate, etc.). However, it is vague about 'recent agent-submitted reviews' – no time range or pagination info for 50 max reviews. Without annotations, it leaves gaps about idempotence and result structure. Adequate for a simple read tool 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 description coverage is 100%, so the baseline is 3. The description does not add extra meaning for parameters beyond what the schema provides. It lists the fields returned (success rate, etc.) but does not clarify how 'limit' affects reviews or what 'recent' means. Schema already explains domain and limit adequately.

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 reads community feedback for a domain and lists specific data returned (success rate, recommend rate, recent reviews). It also mentions utility (useful before choosing a site). However, it does not differentiate from sibling tools like 'submit_check_feedback' or 'submit_feedback' which are write operations, but that distinction is obvious enough.

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 includes a usage hint ('Useful before choosing a site for a task'), giving context for when to use the tool. However, it does not explicitly exclude alternative tools or mention when not to use it, such as for submitting feedback instead of reading 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?

With no annotations provided, the description carries the full burden. It implies a read-only operation ('browse') but does not disclose any behavioral traits such as pagination behavior, data freshness, rate limits, or what happens when no filter is applied. The description adds minimal transparency beyond the schema.

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

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

The description is a single, front-loaded sentence that efficiently conveys the main purpose. It is concise with no wasted words, though it could include a bit more detail without becoming verbose.

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

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

Given the tool has 3 parameters, no output schema, and no annotations, the description is too brief. It does not explain what the rankings contain, how to interpret the results, or how pagination works. The agent would need additional context to use the tool correctly, especially for constructing queries with limit/offset.

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

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

Schema description coverage is 100%, so the baseline is 3. The description mentions the optional category filter, which adds value beyond the schema by confirming it's a filter. However, it does not explain the meaning of limit and offset or their interaction, so the description adds only marginal value over the schema.

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

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

The description clearly states the tool's purpose: 'Browse the agent-readiness rankings.' It uses a specific verb ('browse') and resource ('rankings'), and distinguishes itself from sibling tools like get_score or get_checks, which serve different functions.

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 description does not mention any prerequisites, exclusions, or scenarios where another tool would be more appropriate. It lacks explicit usage guidelines.

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 that the tool reads a cached score and does not trigger a new scan, which is important behavioral information. However, it doesn't mention what happens if the domain is not cached, or whether it might return stale 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 two sentences with zero waste. It front-loads the purpose and ends with actionable 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?

The tool is simple with one parameter and no output schema. The description covers the purpose and usage context. Some might expect details on return value, but given the simplicity, it is adequate, though a note on caching behavior could be added.

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

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

Schema coverage is 100% and the domain parameter is clearly described with an example. The description adds minimal parameter info beyond the schema, so a baseline of 3 is appropriate.

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

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

The description clearly states the tool looks up a cached score and does not trigger a new scan, using specific verbs and a clear resource. It distinguishes from scan_domain explicitly.

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

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

It explicitly instructs to try this before scan_domain, providing clear precedence and implied alternative usage. This is sufficient guidance for when 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 the full burden. It clearly discloses that the data is refetched each run (live, not cached) and describes the content as a step-by-step playbook with verification steps. This gives the agent useful behavioral context about freshness and structure. No contradictions with missing annotations.

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

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

The description is two sentences, each pulling weight. The first sentence defines the resource and its nature, the second adds a key behavioral note (freshness). No fluff or redundancy. Excellent 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 there are no parameters, no annotations, no output schema, and the tool is simple (parameterless retrieval), the description covers the essential: what it returns, its liveness, and its structure (playbook). It could possibly mention the format or size of the returned playbook, but for a tool of this simplicity, it is complete enough.

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 and 100% schema description coverage, so the baseline is high. The description adds value by explaining what the tool returns (the fix playbook), which goes beyond the empty schema. For a parameterless tool, this is adequate.

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

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

The description clearly states it retrieves a specific 'agent-ready-website skill' which is a step-by-step fix playbook. The verb 'Get' is clear, and the resource is named. It distinguishes itself by noting it is refetched each run, which hints at liveness. However, it could be more explicit about how it differs from sibling tools like 'get_checks' or 'get_score'.

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

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

The description implies the tool is used to retrieve a fix playbook for checks, which gives some context for when to use it. However, it does not explicitly state when to use this tool over alternatives like 'get_checks' or 'scan_domain', and provides no 'when not to use' guidance. The context is implied but could be clearer.

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. It discloses that the challenge is single-use, expires in 5 minutes, and is trivially solvable by an LLM. This covers the key behavioral traits for a challenge token.

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 concise sentences: the first defines the purpose and nature, the second states prerequisite context, the third states lifetime and usage constraint. Every sentence adds value without redundancy.

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

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

Given the tool's simplicity (no parameters, no output schema), the description covers purpose, prerequisite relationship, and expiration. It is fully sufficient for an agent to understand when and how to use this 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 input schema has zero parameters, so schema coverage is 100%. The description adds no parameter-specific information because none exist. Per guidelines, baseline 3 is appropriate.

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

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

The description clearly states it gets a verification challenge, defines the acronym HATCHA, and explains it is a reverse CAPTCHA for LLMs. It distinguishes itself from siblings by explicitly linking it to prerequisites for submit_feedback and submit_check_feedback.

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

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

The description explicitly states the tool is 'Required before submit_feedback or submit_check_feedback,' giving clear context for when to use it and no ambiguity about alternatives. This sets expectations for a prerequisite step.

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 caching behavior ('Cached results within the freshness window are returned instantly; pass force to always scan live') and mentions the return structure. However, it does not address potential side effects (e.g., network requests, timeouts), error handling, or whether the scan is destructive. The transparency is adequate 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 two sentences long, with the first sentence front-loading the action and output, and the second explaining caching behavior. Every word adds value; there is no repetition or filler. It is appropriately sized for a tool with 3 parameters and no output 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?

The description explains the core purpose and return values (score, grade, layer breakdown, fix recommendation) but lacks details about the layer breakdown, the freshness window duration, error scenarios, and rate limits. Since there is no output schema, more context about the expected return structure would improve completeness. The description is adequate for a simple scan tool but has 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 already provides descriptions for all three parameters (100% coverage). The description adds minimal value beyond the schema: it reinforces the force parameter's effect ('pass force to always scan live') and mentions the return type, but does not clarify the meaning of 'freshness window' or 'mcpUrl' beyond what the schema already states. Baseline 3 is appropriate given high schema coverage.

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

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

The description clearly states the action: 'Run a full agent-readiness scan on a website or MCP server URL.' It specifies the output (score, grade, layer breakdown, fix recommendation) and distinguishes the tool from sibling tools like get_checks or get_score by focusing on scanning a domain rather than retrieving existing data. The verb+resource+scope is specific and unambiguous.

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

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

The description provides no guidance on when to use this tool versus sibling tools (e.g., get_checks, get_score). It does not mention when not to use it, prerequisites, or alternatives. The only hint is the caching behavior, but that is not usage guidance. Without explicit context, an agent cannot determine if this tool is the best choice for a given task.

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 mentions that results are based on the latest scan and that filtering is by free-text query. Since no annotations are provided, the description carries the full burden. It doesn't disclose whether results are real-time or cached, whether query is case-sensitive, or what happens if no matches are found. The behavioral disclosure is adequate 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?

The description is a single, front-loaded sentence that efficiently conveys the core purpose and filtering mechanism. Every part adds value: 'scanned domains', 'machine-payable capability', 'latest scan verified x402 pay-per-call support', and 'free-text query'. No superfluous 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?

The tool has 2 parameters (both simple), no output schema, and no annotations, so the description must cover purpose, behavior, and parameter semantics. It does this well: purpose is clear, filtering explained, and parameter semantics partially covered. It doesn't describe the return format or edge cases, but for a search tool this is acceptable given the context signals.

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

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

Schema description coverage is 100%, so the parameters 'query' and 'limit' are already documented in the schema. The description adds the detail that query is a free-text filter over 'domain, name, and capability details', which provides some semantic enrichment. However, it doesn't elaborate on the format of query or the default value for limit beyond what the schema says.

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

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

The description clearly specifies the verb 'search', the resource 'scanned domains', and the filtering criterion 'machine-payable capability' with x402 pay-per-call support. It distinguishes itself from sibling tools like scan_domain (which performs scans) and discover_products (which likely lists products) by focusing on capability-based search of existing scan results.

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 states when to use the tool: when you need to find domains that have confirmed pay-per-call support. However, it does not explicitly say when NOT to use it or mention alternative tools for other use cases (e.g., use scan_domain first if a domain hasn't been scanned). It provides minimal usage context.

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

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

No annotations are provided, so the description carries the full burden. It reveals the tool is a write operation (dispute) and requires authentication-like challenge solving. However, it does not disclose side effects, rate limits, or what happens upon success/failure. With no output schema, the agent is left guessing the response.

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: first sentence states the purpose and accepted dispute types, second sentence lists prerequisites. Every word serves a purpose, with no redundancy or filler.

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

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

For a tool with 7 required parameters, no output schema, and no annotations, the description covers the main purpose, acceptable reasons, and prerequisite flows. It is missing the return value or success indication, but given the complexity, it is reasonably complete.

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

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

All 7 parameters have schema descriptions (100% coverage). The description adds value by linking check_id and challenge_id/challenge_answer to their source tools (get_checks, get_verification_challenge), which aids the agent in correctly populating them. This goes beyond the schema's static descriptions.

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

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

The description clearly states the action ('Dispute a specific check result') and the resource ('a domain's scan'), with explicit types of disputes (false pass, false fail, wrong details, outdated). This distinguishes it from sibling tools like get_checks (retrieval) and submit_feedback (general feedback).

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

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

The description provides explicit prerequisites: 'requires a solved challenge from get_verification_challenge' and 'Check ids come from get_checks.' It also marks itself as 'Agent-only,' giving clear context for when to invoke. It does not explicitly state when not to use, but the guidance is strong.

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

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

With no annotations provided, the description carries the full burden. It discloses that the tool is agent-only (auth hint), requires a solved challenge, and has a side effect (powers community stats). However, it does not mention whether the operation idempotent, what happens on failure, or any rate limiting or confirmation response.

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 with only three short sentences, front-loading the core verb and resource. Every sentence adds value: purpose, prerequisite, and effect. There is no redundancy or unnecessary detail.

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 having 10 parameters and no output schema, the description omits any indication of what the tool returns (e.g., success confirmation, review ID). It also does not explain if submission is idempotent, if multiple submissions are allowed, or any other behavioral details that would help an agent fully understand the tool's behavior.

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

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

Schema description coverage is 100%, so the parameter documentation is already comprehensive in the schema. The tool description does not add any additional parameter context beyond what is in the schema, which is acceptable at the baseline score of 3.

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

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

The description clearly states the verb 'submit' and the resource 'review of a domain', specifies the context 'after completing (or failing) a real task', and includes a prerequisite. It is specific and distinguishes from siblings like get_feedback by indicating it creates new data rather than retrieving it.

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

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

The description gives explicit context for when to use the tool ('after completing or failing a real task') and a required precondition ('solved challenge from get_verification_challenge'). However, it does not state when NOT to use it or compare it to alternative tools like submit_check_feedback.

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