Payram

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

With no annotations, the description carries the burden. It discloses what the tool inspects (dependency files, frameworks, .env status) and that it suggests actions, which implies a read-only assessment. However, it does not detail potential side effects, required environment state, or how suggestions are generated.

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 states the tool's actions and outcome. No wasted words.

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

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

Given the tool has no parameters and an output schema exists, the description provides a clear overview. It covers what is inspected and the purpose, though it could elaborate on what 'next integration actions' might entail or if any prerequisites exist.

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

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

The tool has zero parameters, so the baseline is 4. The description doesn't need to explain parameters since there are none. It adds no param-specific info, but that is not a gap under the rubric.

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

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

The description clearly states the tool's function: 'Inspects dependency files, frameworks, and .env status to suggest the next integration actions.' This is a specific verb + resource combo that distinguishes it from sibling tools like generate_setup_checklist or check_payment_readiness, which have different focuses.

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 assessing Payram readiness in an existing codebase, but does not explicitly mention when to use this tool versus alternatives or any exclusions. It provides context ('existing codebase') but no direct guidance on 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 are provided, so the description carries the full burden. It discloses read-only behavior, exact lagging thresholds (10 min for non-BTC, 90 min for BTC), the listener check, and that it names exact remediation steps. No contradictions.

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

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

The description is compact: three sentences that front-load the key verdict and then detail thresholds and workflow. Every sentence provides actionable context 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?

With an output schema present for return values, the description covers the remaining context: what triggers lagging, what else is checked (listener), and the recommended operational sequence. This is complete for a read-only diagnostic 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 tool has zero parameters, so the baseline is 4. The description adds context about what is checked but not parameter-specific semantics, since there are none to describe.

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 produces a per-chain node health verdict with specific categories (healthy/lagging/unreachable/listener-down), which is a specific verb+resource and distinguishes it from sibling tools like payram_doctor and restart_payram_worker.

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

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

Explicit guidance is given: 'Read-only — run this first; restart second; re-run this ~60s after a restart to confirm recovery.' This precisely defines when to use the tool and the workflow around it, including naming the remediation tool (restart_payram_worker).

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 responsibility for behavioral disclosure. It explicitly states the tool is read-only, reports gaps, and does not create wallets—critical side-effect information that lets an agent invoke it safely without expecting mutations.

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 concise sentences, front-loaded with the main purpose and specific checks. Every word earns its place, covering what it does, what it reports, and what it does not do, with zero 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?

Given the tool's simple parameter schema and presence of an output schema, the description sufficiently covers the tool's scope and safety profile. It lacks explicit guidance on when to use this tool over closely related siblings like payram_doctor or assess_payram_project, which slightly 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 input schema already provides 100% coverage for the single optional parameter externalPlatformId, including a clear description and auto-resolve behavior. The tool description adds no additional parameter semantics, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's function: it diagnoses payment readiness gaps per blockchain, listing specific checks (missing deposit wallet, disabled chain/currency, stopped listener worker). It differentiates from siblings by focusing narrowly on readiness and explicitly saying it does not create wallets, which distinguishes it from setup 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 provides clear context: use as a read-only diagnostic, and it points to the CLI for wallet setup, effectively giving an alternative for actual setup. It does not explicitly compare to sibling diagnostic tools like payram_doctor, but the 'read-only' and 'does not create wallets' exclusions give practical guidance.

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

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

With no annotations, the description fully discloses the write behavior ('This WRITES — it creates a real payment request'), authentication requirement (PayRAM API-Key), the hosted checkout flow where customer selects chain/currency, and how to track the payment via reference_id. This exceeds the minimal disclosure expectations.

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

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

The description is three sentences, front-loaded with the primary action and result. Every sentence adds value: action/return, auth note, mutation warning, hosted checkout behavior, and status polling pointer. No redundancy or wordiness.

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

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

The tool has an output schema (referenced) and the description mentions the key return values (hosted URL, reference_id). Given the write semantics, auth requirements, and follow-up status mechanism, the description is complete for an agent to invoke and understand the outcome. Siblings cover status lookup.

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 for all three parameters, so the baseline is 3. The description adds context about the hosted checkout (customer chooses chain/currency), which implies why currency/chain are not parameters, but it doesn't add syntax or format details 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?

The description clearly states the verb ('Creates') and resource ('PayRam checkout/payment link'), and specifies the return payload (hosted URL + reference_id). It distinguishes itself from siblings like lookup_payment by focusing on creation and explicitly noting it WRITES.

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

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

The description provides clear context for when to use the tool (creating a payment link) and gives an explicit alternative for later status checks ('Poll status later with lookup_payment'). It doesn't explicitly state when not to use it, but the context is sufficient.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It conveys an informational, explanatory nature through 'Describe,' implying a read-only operation. However, it does not explicitly state that no side effects occur, nor does it mention the output format or whether it accesses external systems. The output schema exists but is not referenced in the description.

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

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

The description is a single, focused sentence that immediately states the core purpose. There is no redundant language, and the phrasing is front-loaded with the action verb 'Describe' and the subject 'payments.'

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 explain tool, the description is largely complete: it specifies the exact scope of the explanation (initiation to settlement). It does not explicitly mention Payram, but the sibling tool names and overall context imply this. The output schema covers return-value details, so the description does not need to elaborate further.

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

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

The tool has zero parameters, so the input schema trivially covers all inputs. The description adds no parameter information, but none is needed. Per the guidelines, 0 params results in a baseline score of 4.

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

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

The description uses the specific verb 'Describe' and clearly identifies the resource as 'payment flow' with an explicit scope 'from customer initiation through settlement.' This distinguishes it from sibling explanation tools like explain_referral_flow or explain_payram_concepts, making the purpose unmistakable.

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 conditions, prerequisites, or situations where another tool (e.g., explain_payram_basics) would be more appropriate. This leaves the agent without decision-support for tool selection.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not mention the output format, whether it accesses live data, or any limitations. For an explainer tool, this is a minimal but non-misleading description; however, it adds no behavioral context beyond the obvious 'explain' action.

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

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

The description is a single, concise sentence that directly lists the covered topics. Every word adds value, with no redundant information or fluff. It is perfectly front-loaded and appropriate for a simple informational 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 the low complexity (no parameters, no side effects), the description is sufficient to convey the tool's purpose. The output schema exists (though not shown), so return value details are not required. It covers the essential topics but could benefit from a note about the target audience (e.g., 'for newcomers') to fully complete the 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 tool has 0 parameters, and the schema coverage is effectively complete since there are no properties. Per the rubric, the baseline for 0 params is 4. The description does not mention parameters, which is appropriate, and the empty schema already communicates this clearly.

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 with a specific verb ('explain') and resource (Payram's product pillars, architecture, payments, and payouts). It covers a well-defined scope and is distinguishable from sibling tools like explain_payram_concepts by its 'basics' focus, though it could have explicitly differentiated itself.

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 alternative explain tools such as explain_payram_concepts or explain_payment_flow. The description only states what the tool does, leaving the agent to infer the appropriate 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Glossary-backed explanation,' giving no indication of whether the tool is read-only, what output format to expect, or any limitations. This is minimal and vague.

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 with no wasted words, making it very concise. However, it might be too terse to be fully informative, and a more structured description could add value without sacrificing brevity.

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 abundance of similar explanation tools among siblings (explain_payram_basics, explain_payment_flow, explain_referral_flow), the description is insufficient to guide correct tool selection. It does not mention what specific terms or constraints are covered, nor does it clarify the scope relative to other explain tools.

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

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

The tool has zero parameters, so the baseline is 4. There are no parameter details to explain, and the description does not need to compensate for schema gaps since the schema is empty and coverage is 100%.

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 explains Payram terminology and constraints, backed by a glossary. This is a specific verb+resource combination, but it does not explicitly distinguish it from sibling tools like explain_payram_basics or explain_payment_flow.

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 about when to use this tool versus alternatives. There is no mention of appropriate use cases, exclusions, or comparisons to other explanation tools, leaving the agent to guess which tool fits a given query.

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

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It only states what the tool details, without mentioning whether it is read-only, what output to expect (despite an output schema existing), or any side effects. The informational nature is implied by 'Detail' 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 a single sentence that is direct and front-loaded. Every word adds meaning, with no wasted text.

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

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

Given the tool has no parameters and an output schema exists, the description adequately covers the subject matter: the referral lifecycle and APIs. It does not include usage guidance (scored elsewhere), but for a simple explain tool, the description is reasonably complete.

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

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

The tool has zero parameters, so there is nothing to explain beyond what the empty schema already shows. The baseline of 4 applies because no parameter description is needed.

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

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

The description uses the specific verb 'Detail' and names the exact resource: 'the referrer/referee lifecycle and required APIs.' This clearly distinguishes it from sibling tools like explain_referrals_basics (which covers general concepts) and generate_referral_* (which generate code snippets).

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. The description implies it is for explaining the referral flow, but it does not contrast it with siblings like explain_referrals_basics or get_referral_dashboard_guide, leaving the agent to guess the appropriate 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?

With no annotations, the description carries the full burden. It states it will 'Summarize', which implies a read-only informational output with no side effects. However, it does not disclose the return format, level of detail, or any potential limitations. For a simple explain tool this is acceptable but not thoroughly transparent.

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

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

The description is a single, front-loaded sentence that states the verb and resource immediately. Every word is necessary; there is no redundancy or filler.

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

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

The tool is intentionally simple: zero parameters, an output schema exists, and the description covers the core purpose. It could potentially list subtopics (e.g., referral links, rewards, tracking), but the description is complete enough for a basics overview tool given its 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 tool has zero parameters, and the input schema confirms this with no properties. The baseline for 0 params is 4, and the description correctly adds no parameter-specific semantics because none are needed.

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

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

The description uses a specific verb ('Summarize') and clearly identifies the resource ('Payram referral campaigns') and the scope ('configured and managed'). It distinguishes from sibling tools like explain_referral_flow (which likely covers the process flow) and explain_payram_basics (which covers Payram generally).

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 a high-level overview of referral campaign setup and management, but it does not explicitly state when to use this tool versus alternatives such as explain_referral_flow or get_referral_dashboard_guide. No exclusions or alternative references are provided.

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

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

No annotations are provided, so the description carries full responsibility. It only states that it 'creates' a template without disclosing whether it writes a file, returns content, or what variables are included, leaving significant behavioral 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?

A single, front-loaded sentence communicates the core function with no extraneous 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?

The tool is simple (0 params) and has an output schema, so the description doesn't need to explain return values. However, it could benefit from noting what the template includes or typical usage, but given low complexity, it is adequate.

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

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

With zero parameters and 100% schema coverage, the description adds context by specifying the template's purpose, but there are no parameter details to elaborate on. Meets the baseline for a no-parameter 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 uses a specific verb ('Creates') and identifies the resource ('.env template') and its purpose ('configuring a merchant backend to talk to a self-hosted Payram server'), clearly distinguishing it from sibling snippet generators.

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

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

It provides clear usage context (for self-hosted Payram setups) but doesn't explicitly contrast with alternatives like generate_setup_checklist or scaffold_payram_app, nor state when not to use.

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

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

No annotations are provided, so the description carries full behavioral disclosure burden. It discloses that it generates a snippet, implying no actual sending occurs, but it does not explain this distinction clearly, nor does it mention any limitations, side effects, or prerequisites. The description adds little beyond the tool's name.

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 of 13 words, front-loaded with the key action and purpose. Every word earns its place, with no wasted 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?

The tool is simple with 2 fully described parameters and an output schema available, so the description does not need to explain return values. The lack of explicit sibling differentiation is a minor gap, but the core usage context is clear enough for an agent to invoke correctly.

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

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

Schema description coverage is 100%; both parameters have clear descriptions (status enum, language enum). The tool description adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate.

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

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

The description uses a specific verb ('Generates') and resource ('snippet to send mock Payram webhook events'), and clearly states the purpose (testing local endpoint). This distinguishes it from sibling tools like generate_webhook_handler, which generates a handler rather than a sending snippet.

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 testing local endpoints ('to your local endpoint for testing'), but it does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions. With many sibling snippet generators, more explicit guidance would be beneficial.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does, not the nature of the output (e.g., placeholder values, authentication headers, whether it uses real credentials), nor any side effects or limitations. This is a significant gap for a snippet generator that might include code with assumptions about the environment.

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 direct and free of filler. It front-loads the core action and resource, making it easy to scan and understand. There is no wasted 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?

The tool is simple with only one parameter and has an output schema, so the description does not need to explain return values. However, it lacks contextual details about the snippet's content, such as authentication handling or whether it is production-ready. Given the low complexity, the description 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?

The schema description coverage is 100%, with the 'language' parameter having an enum and a clear description. The tool description adds no additional meaning beyond echoing 'in the requested language,' so it does not improve upon the schema. The baseline of 3 applies because the schema already fully documents 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 that it generates a raw HTTP sample for creating a Payram payment, with a specific verb ('generates'), resource ('HTTP sample'), and purpose ('creating a Payram payment'). The phrase 'raw HTTP' distinguishes it from sibling tools like generate_payment_sdk_snippet or generate_payment_route_snippet, making its purpose unambiguous.

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

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

The description implies usage for raw HTTP snippet generation, but does not explicitly state when to prefer this over alternatives (e.g., SDK or route snippets). It provides no exclusions or alternative tool references, so the guidance is only implicit through the tool name and the words 'raw HTTP'.

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

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the tool 'generates a ready-to-use backend endpoint' without clarifying whether it returns code, writes files, or requires existing setup. No mention of side effects, output format, or limitations.

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

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

The description is a single, focused sentence with no filler. It front-loads the action and includes a concrete example, making it highly concise and easy to parse.

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, output schema present), the description is minimally adequate. However, it lacks usage guidance and explicit behavioral detail, which would be needed for fully confident tool selection alongside many similar 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 schema provides 100% coverage for the sole parameter 'framework', including a description and enum values. The tool description adds no extra parameter context, 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?

The description clearly states the tool generates a backend endpoint for Payram payments with a concrete example path. It uses a specific verb ('generates') and distinct resource ('backend endpoint'), effectively distinguishing it from sibling snippet tools like HTTP or SDK snippets.

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. There are several similar sibling tools (e.g., snippet_express_payment_route, generate_payment_http_snippet) but the description doesn't indicate selection criteria or when to prefer this over those.

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 carry the behavioral disclosure burden. It only restates the core purpose and gives no detail about the generated code's structure, framework-specific variations, or any side effects, making it minimally transparent.

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

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

The description is a single, front-loaded sentence that efficiently states the tool's action and scope. There is zero wasted wording.

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

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

The tool is simple (one parameter, output schema exists), and the description conveys the essential purpose. However, it lacks any context about when this SDK snippet should be preferred over the many related snippet tools, leaving a completeness gap for an agent navigating the toolset.

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 provides 100% coverage of the single 'framework' parameter with enum descriptions, so the description does not need to add parameter details. It adds no extra value beyond the schema, aligning with the baseline score.

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

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

The description uses a specific verb ('Generates') with a clear resource ('backend code using the official Payram JS/TS SDK to create a payment'). It distinguishes itself from sibling tools like generate_payment_http_snippet and generate_payment_route_snippet by explicitly targeting the SDK approach.

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, nor does it mention any prerequisites or context. Sibling tools exist for HTTP, route, and status snippets, but the description does not differentiate usage scenarios.

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

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

No annotations are provided, so the description must disclose behavior. It accurately states the tool generates code rather than executing it, implying a safe, read-only action. However, it does not describe the output format or any contextual behavior (e.g., whether the generated code requires authentication). The description is minimal but not misleading.

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 contains no filler. Every word contributes to the tool's purpose. It is appropriately concise for a simple code-generation 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 the tool's simplicity (one parameter, output schema present) and clear purpose, the description is largely complete. It could mention when to use this over related status snippet tools, but the core functionality is adequately communicated. The output schema likely covers return-value details.

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

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

The schema fully describes the only parameter 'style' with a detailed description: 'sdk uses the Payram SDK, http uses raw HTTP requests'. Since schema coverage is 100%, the description adds no additional parameter information. 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?

The description is highly specific: 'Generates backend code to query the status of a Payram payment.' It clearly states the verb ('generates'), the resource ('backend code'), and the scope ('query the status of a Payram payment'). This distinguishes it from sibling snippet tools like generate_payment_http_snippet or generate_payment_sdk_snippet, which are not focused on status queries.

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 doesn't mention prerequisites, when this snippet type is appropriate, or explicitly exclude other tools. With many sibling snippet generators, this lack of usage context is a notable gap.

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 present, so the description carries the burden. It discloses the tool's non-mutating nature (generates a snippet) and details the recommended flow with OTP validation. It does not describe output format or potential caveats, but the presence of an output schema mitigates this. The behavior is clearly communicated.

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

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

Two sentences, front-loaded with the core action and flow, then usage guidance. Every word earns its place, with no redundant filler.

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

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

The description fully captures the tool's purpose, the exact steps in the generated flow, and when to use it versus an alternative. With zero parameters and an output schema available, nothing essential is missing for a code-snippet generator of this scope.

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

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

The tool has zero parameters, so the baseline is 4. The description adds meaning by explaining what the generated snippet contains, even though there is no parameter schema to annotate. It effectively communicates the tool's purpose without needing parameter details.

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 generates a specific 3-step OTP-verified payout flow, naming the exact sequence (create recipient → validate OTP → create payout). It also explicitly differentiates from a sibling tool by mentioning use for repeat beneficiaries vs one-off payouts, making the purpose unambiguous.

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

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

Explicit guidance is provided: 'Use this for repeat beneficiaries; use generate_payout_sdk_snippet for one-off direct payouts.' This clearly states when to use this tool and when to use an alternative, leaving no ambiguity.

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

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

No annotations are provided, so the description carries the burden. It states the action ('Generates') and the output type implicitly, but does not disclose potential side effects, limitations, or whether any external calls are made. The simple nature of the tool and the explicit purpose give some transparency, but additional context (e.g., 'read-only', 'no execution') would improve 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 a single concise sentence that is front-loaded and directly states the tool's purpose. There is 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?

The tool has a simple 1-parameter input schema with full coverage, an output schema (so return values are documented), and a clear purpose statement. The description is adequate for a straightforward code generator, though it lacks usage guidance that would make it fully complete.

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

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

The schema description covers the single parameter 'framework' with 100% coverage, including an enum. The description does not add any extra meaning 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?

The description clearly states the tool generates a backend code snippet for creating a payout using the Payram JS/TS SDK. It uses a specific verb ('Generates') and resource ('backend code snippet for creating a payout'), and distinguishes from sibling tools by specifying 'payout' and 'SDK'.

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 exclusions or name sibling tools that should be used for other scenarios (e.g., HTTP snippets, status snippets).

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 communicates the core action (generates backend code) but does not disclose any details about the code's structure, language, or return behavior beyond what the output schema already provides. It is not misleading, but it offers limited behavioral insight.

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 immediately informative, front-loaded with the core verb and object. It contains no unnecessary words or repetition.

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 code generator with no parameters and an output schema, the description is adequate. It could add context about what 'payout status' means or how the snippet integrates, but the current text is sufficient for an agent to select and invoke the tool correctly.

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

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

The tool has zero parameters, so the baseline per the rubric is 4. The description correctly does not need to explain parameter semantics because there are none to explain.

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

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

The description clearly states the tool's function: generating backend code to query payout status via the Payram SDK. It names both the resource (payout status) and the SDK, and the phrase 'payout status' distinguishes it from sibling tools like generate_payment_status_snippet and generate_referral_status_snippet.

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 use case (generating payout status snippets) but provides no explicit guidance on when to choose this over alternatives such as generate_payout_sdk_snippet or generate_payment_status_snippet. There is no mention of exclusions or alternative scenarios.

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

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

With no annotations provided, the description must fully disclose behavior. It ambiguously says 'Generates a backend route' without clarifying that it returns a code snippet rather than actually modifying a live system. This could mislead the agent into thinking the tool has side effects. No details about output format, permissions, or limitations are given, leaving a significant transparency 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?

The description is a single, front-loaded sentence with zero fluff. It immediately states the action and resource, and every word contributes to the purpose. This is appropriately sized for a simple one-parameter 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 the tool's simplicity, the description combined with the schema and output schema covers the basic invocation. However, the ambiguity about whether it generates a live route or a code snippet is not resolved, and without output schema details visible, the description alone feels incomplete. It adequately covers functionality but lacks the clarity needed for a fully self-contained description.

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 100% coverage for the sole parameter 'framework' with a description and enum values, so the baseline is 3. The tool description adds no extra meaning about the parameter, but the schema fully explains it, so no additional compensation is needed.

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

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

The description clearly states the tool's function: 'Generates a backend route such as /api/referrals/create for logging referral events.' It names a specific verb (Generates), resource (backend route), and scope (for logging referral events), and the example path distinguishes it from sibling snippet generators like payment route or referral SDK snippets.

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 generating backend route code for referral event logging, but it provides no explicit guidance on when to use this tool versus alternatives like generate_referral_sdk_snippet or generate_payment_route_snippet. No exclusions or alternative tools are mentioned, so usage context is only implied by the example path.

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 responsibility for behavioral disclosure. It does not state whether the snippet is returned inline, written to a file, or how it integrates with the framework. It also omits the fact that only 'generic-http' is currently supported, which is important behavioral context 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 sentence with no unnecessary filler. It is efficient, though the phrase 'backend route or service snippet' could be more precise. Overall, it earns a strong conciseness score.

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?

This is a simple tool with one documented parameter and an output schema present, so the description need not detail return values. However, it lacks guidance on when to use it and does not mention the supported framework constraint beyond what the schema already shows. Adequate for a minimal generator but not comprehensive.

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% because the only parameter 'framework' has a description and enum. The tool description adds nothing beyond the schema, but per the rubric baseline 3 applies when schema already thoroughly documents parameters.

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

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

The description uses a specific verb 'Generates' and names the resource: 'a backend route or service snippet to create a referral event using the Payram SDK.' It distinguishes from pure route snippets by emphasizing the SDK, though the 'route or service' phrasing is slightly ambiguous.

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 about when to use this tool versus alternatives like generate_referral_route_snippet. There is no mention of prerequisites, when SDK-based snippets are preferred, or any exclusions, leaving the user without 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?

With no annotations, the description must convey behavior. It states that it generates code, but does not explicitly mention that it doesn't execute the fetch or that the output is only a sample snippet. This leaves some ambiguity about side effects, though the operation is inherently non-destructive.

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 one sentence, front-loaded with the main verb, and contains no filler. It is appropriately concise for a tool with minimal complexity.

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

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

The tool is simple (one parameter, output schema present), and the description adequately states the core purpose. However, it lacks guidance on selecting this snippet variant over other referral snippet tools, which would make it fully complete.

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

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

The schema covers the single parameter 'style' fully with an enum and description, so the description adds no new parameter information. Baseline per the rubric is 3 due to 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 uses a clear verb 'Generates' with a specific resource ('referral progress, rewards, or status'). It distinguishes the tool from general referral snippet tools by focusing on status, though it doesn't explicitly name sibling tools or contrast with them.

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 such as generate_referral_sdk_snippet or generate_referral_route_snippet. The style parameter in the schema hints at usage options, but the description itself gives no exclusions or contextual triggers.

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 only mentions that it 'generates' a snippet, but does not disclose any details about side effects, output format, or safety profile. This is insufficient for a tool with no other behavioral hints.

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, concise sentence with no fluff. It is appropriately sized for a 0-parameter tool, though it could be more detailed 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 presence of many sibling snippet generators, the description is too terse to allow reliable selection. It does not mention what kind of snippet (language, framework), output characteristics, or use cases. The output schema exists but the description still lacks essential 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 0 parameters, so baseline is 4. The description does not need to explain parameters, and it adds contextual meaning by specifying the domain (referral IDs, statuses, eligibility), which helps understand the tool's purpose.

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 'Generates a snippet to validate referral IDs, statuses, and eligibility,' which clearly identifies the action (generating a snippet) and the resource (referral validation). It distinguishes from sibling tools like generate_referral_status_snippet by focusing on the validation aspect, though it does not explicitly name alternatives.

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

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

There is no guidance on when to use this tool versus alternatives. The description simply states what it does without providing context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name.

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. The verb 'Returns' indicates a read-only operation, which is accurate. However, it does not disclose whether the checklist is static or dynamic, nor does it explicitly state that no configuration is modified. It lacks details about prerequisites or limitations.

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

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

The description is a single, well-structured sentence that front-loads the action ('Returns') and directly states the outcome. It contains no fluff or redundant information, making it highly scannable.

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—zero parameters, no annotations, and an output schema—the description is adequately complete. It clearly communicates what the tool does and for whom. There is no need for additional return-value details since an output schema exists.

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 is empty with 0 parameters, and schema description coverage is 100% (vacuously). The 0-param baseline is 4, and the description correctly avoids parameter documentation. It provides the only relevant context: that the checklist is for merchants.

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

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

The description uses the specific verb 'Returns' and clearly identifies the resource: a step-by-step checklist. It adds scope with 'everything a merchant must configure to start using Payram', which distinguishes it from other generate_* tools like generate_env_template or scaffold_payram_app. This is a precise, non-generic 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 the usage context: when a merchant needs to know what to configure to start using Payram. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or alternative tools. More explicit guidance (e.g., 'Use this during merchant onboarding') would improve clarity.

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 takes on the burden. It explains the core behavioral logic (credits first, then debits) and the design outcome (balance states instead of payment exceptions). This goes beyond just saying 'generates code' and helps the agent predict what the tool produces. It doesn't mention output format, but that's covered by the output 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 about 50 words, front-loaded with the target audience, and every sentence adds value: use case, components, behavioral promise, and alternative path. No fluff or repetition.

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 2 parameters, a rich output schema, and an explicit use-case split (existing vs new store), the description covers the key decision points. It names the pieces, explains the integration approach, and points to the alternative for new stores, making it complete for selection and invocation.

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

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

Schema coverage is 100% with clear enum descriptions for both parameters, so the schema does the heavy lifting. The description doesn't add much parameter-specific detail beyond what's already in the schema, but it does contextualize the components ('ledger schema + cumulative-credit webhook handler + atomic invoice-settle function') which maps to the 'part' enum.

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 emits a top-up wallet integration with specific components (ledger schema, webhook handler, atomic invoice-settle function). It distinguishes itself from sibling snippet tools by scoping to 'EXISTING apps' and contrasting with the checkout/plugin path.

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 'For EXISTING apps' and gives an alternative for new stores: 'Use the checkout/plugin path instead'. Also recommends pairing with a skill, giving clear when-to-use and when-not-to-use guidance.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention side effects (e.g., file creation, overwriting), dependencies, authentication requirements, or any limitations. 'Generates' implies a side effect but lacks specifics.

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, concise sentence that front-loads the action verb 'Generates' and contains no redundant information. It is efficiently structured and easy to parse.

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 an output schema, the description is minimal and does not explain what the generated router entails, what framework or structure it assumes, or what 'domain handlers' means in this context. This tool performs a complex code-generation operation but is under-specified for an agent to understand its full scope and dependencies.

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

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

The tool has zero parameters, so the input schema is empty. The baseline for zero parameters is 4, and the description does not need to add parameter context. No additional parameter information is necessary.

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 action ('Generates'), the resource ('a backend event router'), and its function ('dispatches Payram webhook events to domain handlers'). This distinguishes it from the sibling tool 'generate_webhook_handler' by focusing on routing rather than handling.

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, no context for when it should be invoked, and no mention of prerequisites or exclusions. It simply states what it does without any usage direction.

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 for behavioral disclosure, but it only states that code is generated. It does not explain whether files are written, output format, side effects, or any prerequisites beyond the framework parameter. This is a significant gap for a generator 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 a single, front-loaded sentence with no redundancy. It is brief but could be slightly expanded to include usage context without becoming verbose, so it loses one point for being too minimal.

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, output schema present), the description covers the core purpose. However, it lacks differentiation from siblings and omits behavioral context, leaving the overall completeness at a minimum viable level.

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

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

The schema already provides a description for the parameter (framework) with an enum, achieving 100% coverage. The tool description adds no additional meaning about how the framework affects the generated code, so the baseline of 3 is appropriate.

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

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

The description clearly states the tool generates backend code for Payram webhook HTTP requests, using a specific verb and resource. It distinguishes itself from siblings like generate_webhook_event_router by focusing on the HTTP handler, but it does not explicitly name alternatives.

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 the many similar code-generation siblings. The description does not mention when this is appropriate or what alternatives exist, leaving the agent to infer usage from the name and schema.

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 the content scope, including chain recommendations, faucet URLs, prerequisites, and recovery commands for interrupted sessions. It does not explicitly state whether the tool has side effects, but 'Returns' strongly implies a safe, read-only operation, adding useful context beyond a simple generic statement.

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 well-structured sentences. The first sentence front-loads the primary purpose, and the second efficiently lists the key contents. Every phrase earns its place, with no redundancy or filler.

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

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

The description is fairly complete for a no-parameter guide-returning tool. It covers the flow, recommendations, prerequisites, and recovery commands. Since an output schema exists, return value details are presumably defined there. However, it could slightly improve by explicitly mentioning it is a read-only reference or comparing to similar sibling tools.

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

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

The tool has zero parameters, and schema coverage is 100% vacuously. The description does not need to explain parameters. Baseline 4 is appropriate since there is nothing to compensate for.

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 step-by-step setup flow for deploying PayRam as an agent, listing specific components (install, wallet creation, faucet funding, contract deployment, first payment). This specific verb+resource+scope distinguishes it from siblings like generate_setup_checklist or onboard_agent_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?

The description implies the tool is used when one needs the full setup flow, and the detailed content makes the use case clear. However, it does not explicitly state when to use this tool versus alternatives like onboard_agent_setup or generate_setup_checklist, nor does it provide 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 carries the full burden of behavioral disclosure. It discloses the key filter of only counting FILLED payments and the date default behavior. It does not mention rate limits, auth requirements, or error handling, but for a read-only aggregate query, this is a reasonable amount of disclosure. A score of 3 reflects that it adds meaningful behavioral context but not exhaustive details.

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

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

The description is two sentences with no redundancy. The main action and the critical qualifier (FILLED only) are front-loaded, making it clear and scannable. 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 that an output schema exists, the description need not explain return formats. It covers the core behavior (aggregated volume, date default, filtering) and the parameters are fully documented in the schema. It could add a note on timezone handling or what 'volume' sums, but these are minor gaps, so it is sufficiently complete for a straightforward read 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 already documents both parameters with 100% coverage, including the default for 'date' and the auto-discovery of 'externalPlatformId'. The description adds no additional semantic detail beyond what the schema already provides, 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?

The description clearly states the tool returns total payment volume for a specified date, with breakdowns by network and currency, and explicitly notes it only counts FILLED payments. This is specific and distinguishes it from sibling tools like lookup_payment or search_payments, which likely return individual transaction details rather than aggregated volume.

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 querying daily volume with an optional date, and mentions that it defaults to today. However, it does not explicitly state when to prefer this tool over alternatives such as get_payment_summary or get_unswept_balances, nor does it provide exclusions or prerequisites. Thus, the usage context is clear but not fully articulated.

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 clearly states the output (counts by status) but does not disclose any potential limitations, such as time range, data freshness, or whether it aggregates across platforms. This is adequate but not rich.

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

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

Two sentences that directly convey the key information without any waste. The structure efficiently communicates the purpose and intended use.

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, the presence of an output schema, and a single optional parameter, the description is sufficient to understand its role. It could mention scope (e.g., date range) but the overview of statuses is clear 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 fully documents the only parameter with a helpful description stating it is optional and auto-discovered. The tool description adds no additional parameter meaning, 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?

The description clearly states it returns payment counts (total, open, closed, cancelled), which is a specific verb+resource combination. This distinguishes it from sibling tools like search_payments or lookup_payment, which focus on detailed retrieval rather than a summary.

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

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

The phrase 'useful for a quick overview of payment activity' provides clear context on when to use this tool. However, it does not explicitly mention alternatives or when not to use it, so it stops short of the top score.

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

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

With no annotations, the description carries the full burden. It states the return type (markdown) and gives an example id format, which is transparent about the output. However, it does not mention error behavior, permissions, or any side effects, though for a likely read-only getter this is acceptable.

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

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

The description is a single sentence with a clear subject, verb, and object, plus an example. Every word earns its place; there is no fluff or redundancy.

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

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

Given the tool's simplicity (one param, no nested objects) and the presence of an output schema, the description is sufficient. It explains the purpose and input, though it could briefly mention how to discover ids (e.g., list_payram_docs) for full 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 provides no description for the 'id' parameter (0% coverage), so the description must compensate. It does so by explaining that the id is used to fetch a doc and giving an example ('features/payouts'), which adds meaningful format context 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 action (returns markdown) and the resource (Payram doc) with an input identifier. It gives a concrete example, but it does not explicitly distinguish from siblings like list_payram_docs or explain_payram_concepts, so it is 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?

Usage is implied: use this when you have a doc id and want markdown. However, there is no explicit guidance on when to use this rather than list_payram_docs or other sibling tools, and no exclusionary 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, the description carries full responsibility for behavioral disclosure. It only states what links are surfaced, omitting details like whether network access is required, how results are structured, or any limitations. This is 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?

A single, front-loaded sentence that is concise and waste-free. It mentions the exact categories of links (documentation, website, community) in under ten words.

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

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

For a parameterless, simple retrieval tool with an output schema present, the description is essentially complete. It communicates the core purpose without needing to detail return values, as the output schema covers that.

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

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

The tool has zero parameters, so the schema coverage is complete by default. Per guidelines, the baseline is 4, and the description correctly avoids inventing parameter details that don't exist.

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's purpose: surfacing official documentation, website, and community links. It uses a specific verb ('Surface') and specifies the resource (links), distinguishing it from sibling tools like get_payram_doc_by_id or list_payram_docs, which deal with document content rather than link collections.

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 usage guidance is provided. The description does not indicate when to use this tool versus alternatives such as list_payram_docs or get_payram_doc_by_id, nor does it give context on expected 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?

No annotations are present, so the description carries the full burden. It indicates the tool is informational ('Explain'), implying no mutations, but does not disclose what the explanation includes (e.g., step-by-step guide, code examples) or any limitations. This is minimally transparent but lacks behavioral depth.

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

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

The description is a single, front-loaded sentence that directly and efficiently states the tool's purpose with no redundant words or unnecessary 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 low complexity (zero parameters, informational tool) and the presence of an output schema, the description sufficiently covers the tool's scope. It does not detail what 'embed and manage' entails, but the output schema likely provides the response structure, and the description is adequate for a guide 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 tool has zero parameters, so the baseline is 4. The description adds contextual meaning by specifying the tool covers 'embed and manage' of the referral dashboard, which is useful despite no parameter details being needed.

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

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

The description uses the specific verb 'Explain' with a clear resource ('the referral dashboard experience') and scope ('embed and manage'), which distinguishes it from sibling tools like explain_referral_flow or generate_referral_* snippets. It clearly states what the tool does.

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

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

No guidance is provided on when to use this tool versus alternatives. The description only states the tool's function without mentioning related tools or exclusions, leaving the agent to infer 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a generic 'returns balances' by detailing output structure (breakdown by blockchain/currency), statuses (sweep, sweep_in_progress, sweep_not_allowed, no_balance), and specific reasons for stuck funds (e.g., HOT_WALLET_LOW_GAS with hot-wallet address). This transparency enables accurate expectation-setting.

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

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

The description is compact, front-loading the core purpose and then adding necessary detail about statuses and error reasons. Every sentence earns its place, and the formatting (with 'AND why stuck funds are stuck') guides attention to actionable insight without bloat.

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

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

For a no-parameter read-only tool, the description covers the essential aspects: scope (all wallets), grouping (blockchain/currency), statuses, error examples, and common reasons for stuck funds. An output schema exists (as per context signals), and the description already explains return values enough for an agent to select and interpret results correctly.

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

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

There are zero parameters, and the schema confirms an empty properties object (100% coverage). Baseline for 0 parameters is 4; the description appropriately omits parameter details since none exist.

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

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

The description opens with a specific verb and resource: 'Returns unswept (unsettled) balances across all wallets, broken down by blockchain and currency.' This clearly distinguishes the tool from siblings like get_daily_volume or get_payment_summary by focusing on sweep/settlement status.

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 when to use it: 'Use this to answer "where is my money / why has it not swept".' It also explains what insights are provided (sweep readiness, lastSweepError with actionable info, pending SCW deployment, missing cold wallet), giving clear context for selection over 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states this is a public endpoint requiring no API key or JWT, and that it operates per node. It also implicitly signals a read-only operation by saying 'Lists,' which is appropriate for the description.

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

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

The description is two sentences with no fluff. The first sentence states the core functionality, the second covers auth and usage. Every word contributes value, and it is perfectly front-loaded.

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

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

For a simple 0-parameter list endpoint with an output schema, the description covers all essentials: purpose, auth requirements, usage, and output contents. It is self-contained and leaves no obvious gaps for an agent to invoke it correctly.

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

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

The tool has zero parameters, so the baseline is 4. The description adds useful context about what the response will contain (chain code, network, currency code), which is helpful even though not strictly about input parameters. No further param explanation is needed.

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

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

The description starts with a specific verb and resource: 'Lists every blockchain currency PayRam supports on this node,' and explicitly names the output fields (chain code, network, currency code). This clearly distinguishes it from sibling tools like list_platforms or list_recipients.

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 usage guidance: 'Use this to discover valid blockchainCode/currencyCode values before creating payments or payouts.' It also states the access requirement (only PAYRAM_BASE_URL needed), which helps the agent decide when to call this 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?

With no annotations provided, the description carries the full burden for behavioral disclosure. It clearly states the tool returns doc IDs (not file contents) and specifies the directory, implying a read-only listing operation. It does not cover edge cases like authentication or ordering, but for a simple list this is adequate.

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

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

Two concise sentences, directly stated with no filler. The first sentence defines the purpose, the second explains the optional parameter. 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?

For a simple listing tool with one optional parameter and an output schema, the description is sufficiently complete. It specifies the directory, the result type (doc IDs), and the scoping mechanism. The output schema covers return details, so no further explanation 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 schema has one optional parameter, 'prefix', with no description. The description adds meaning by explaining it scopes the listing and gives an example ('features'). This goes beyond the bare schema and compensates for the 0% 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 tool lists available Payram doc IDs from a specific directory (docs/payram-docs-live). This distinguishes it from sibling tools like get_payram_doc_by_id, which fetch a specific document's 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?

The description provides context on when to use this tool (to list doc IDs) and mentions optional prefix scoping, but does not explicitly contrast it with alternatives or state when not to use it. The use case is implied rather than explicitly guided.

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 convey behavioral context. It does so by specifying 'for the authenticated user' (auth context) and 'Lists all' (scope). It also reveals that the output includes a platform ID. However, it does not explicitly state that the operation is read-only or describe the response structure, though the output schema likely covers that.

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 action. The second sentence provides a practical use case without redundancy. Every word earns its place, making it highly concise and well-structured.

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

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

Given the tool's simplicity, the description covers the essential aspects: what it does, for whom, and a key use case. The presence of an output schema means return value details are not strictly needed. It lacks explicit mention of edge cases (e.g., empty list) but is complete enough for a basic list 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 tool has zero parameters and the schema is vacuous, so the baseline is 4. The description adds no parameter-specific information because none is needed. It does add value by explaining the purpose of the output (platform ID), which indirectly informs why there are no parameters.

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

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

The description clearly states the tool's function: 'Lists all external platforms (projects) for the authenticated user.' The verb 'Lists' and the resource 'external platforms' are specific, and the parenthetical '(projects)' clarifies terminology. It also distinguishes itself from other list tools by highlighting the platform ID discovery use case, which is unique among siblings.

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

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

The description provides explicit guidance on when to use the tool: 'Use this to discover your platform ID.' It also implies when it is not needed by noting that 'other tools auto-resolve if omitted.' While it does not name specific alternative tools, this is clear enough for selection in most contexts.

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

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

No annotations are available, but the description reveals that this is a read-only listing operation ('Lists') and gives insight into the output by referencing the status field ('active'). It doesn't discuss potential errors or authentication, but the simplicity of the tool and presence of an output schema mitigate this 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?

The description is exactly two sentences: the first states the core function, the second provides two concrete use cases. No filler, front-loaded, and every sentence earns its place.

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

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

For a zero-parameter read-only listing tool with an output schema, the description fully covers the essentials: what it lists, why you'd use it, and what status information is available. The reference to the payout flow and OTP verification completes the contextual picture.

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 there is nothing to explain. The baseline for 0-param tools is 4, and the description adds contextual value by explaining the purpose and usage without needing to elaborate on parameter syntax.

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 function: 'Lists saved withdrawal recipients (payout beneficiaries).' It names a specific verb and resource, and the mention of 'recipient ID' and 'OTP-verified' distinguishes it from sibling listing tools like list_currencies or list_platforms.

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

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

Explicit usage guidance is provided: 'Use this to find a recipient ID for the 3-step payout flow, or to check whether a beneficiary is already OTP-verified.' This tells the user exactly when to invoke the tool, and the context makes clear it's the primary (and only) recipient-list 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 are provided, so the description carries the full burden. It discloses the result limit ('Returns up to 5 matching payments') and that it returns 'full details'. However, it does not explicitly state that the operation is read-only (though 'look up' implies it), nor does it describe error cases, empty results, or rate limits. This is moderate transparency, but not exceptional.

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

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

The description consists of two concise sentences. The first sentence states the purpose with a clear verb and resource, and the second adds the key behavioral detail (result limit). There is no redundancy, fluff, or repetition of schema information. It is perfectly sized 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?

The description provides the essential information: the tool's purpose, accepted identifier types, and return limit. Since an output schema exists, the return structure is already defined. The input schema covers parameter details. The only gap is lack of explicit guidance on choosing between this and similar tools (e.g., search_payments), but given the well-specified schema and description, it is largely complete for a simple lookup 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 covers both parameters with descriptions (100% coverage), so the baseline is 3. The tool description restates the query types but adds no new parameter-specific meaning beyond what the schema already provides. The description does mention the return limit, but that's about output, not parameters. Thus, it meets but does not exceed the baseline.

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

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

The description clearly states the tool's function: 'Look up payments by transaction hash, email, reference ID, customer ID, or invoice ID.' It uses a specific verb ('look up') and resource ('payments') and enumerates the query types. However, it does not explicitly differentiate itself from sibling tools like search_payments, so it doesn't fully earn 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 provides clear context on when to use this tool: whenever you have one of the listed identifiers (transaction hash, email, reference ID, customer ID, or invoice ID). It implies the tool is for targeted lookups, but it does not explicitly mention alternatives or when not to use it, such as for broader searches that might require search_payments. This aligns with 'clear context, no 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It states that the tool 'Returns' a guide, implying a read-only, non-mutating operation. It adds context about the autonomous nature and lack of web UI, which clarifies expectations. However, it does not go into further depth about potential side effects or required auth, but for a simple retrieval tool this is sufficient.

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

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

The description is a single, well-structured sentence. It front-loads the core action ('Returns the complete autonomous agent setup guide') and adds a crucial qualifier ('without any web UI or human interaction') without any wasted words.

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

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

The description is complete for a tool with zero parameters and an output schema. It fully explains the tool's purpose and the specific context. Since the output schema handles return value details, the description doesn't need to over-specify. No gaps are apparent.

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 is empty with no parameters, and the description correctly doesn't attempt to explain parameters. The schema description coverage is 100%, and with 0 parameters the baseline is 4, which fits perfectly.

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

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

The description uses a specific verb 'Returns' and clearly identifies the resource: 'the complete autonomous agent setup guide for deploying Payram without any web UI or human interaction.' It distinguishes itself from siblings like get_agent_setup_flow by emphasizing 'complete autonomous' and the specific deployment 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?

The description gives clear context on when to use the tool: when deploying Payram without a web UI or human interaction. However, it does not explicitly mention alternatives or exclusions, leaving room for confusion with similar sibling tools like get_agent_setup_flow.

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 behavioral burden. It explicitly states 'read-only' and explains the staged execution and the returns of fix commands for the first failing stage, giving clear stop conditions. It omits details about potential network calls or runtime, but the read-only marker is a key safety disclosure.

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

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

The description is three concise sentences with no waste. Each sentence provides distinct value: the staged pipeline, the output behavior, and the usage instruction.

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

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

For a complex diagnostic tool, the description captures the staged flow, the output type, the stopping condition, and the read-only nature. With an output schema present, the description adequately covers all necessary context for correct invocation.

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

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

Schema coverage is 100%, with detailed parameter descriptions that include defaults and operational nuances (e.g., port 80 vs 8080). The description itself adds no extra parameter context, so the baseline 3 is appropriate.

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

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

The description clearly states the tool diagnoses a PayRam setup via a specific staged pipeline (server reachability, merchant API key, admin JWT, payment readiness). It also distinguishes itself from sibling tools by positioning as the first-line check for any PayRam failure.

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?

Provides an explicit when-to-use instruction: 'Run this FIRST when anything PayRam-related fails.' This is strong guidance, but it does not explicitly name alternative tools or when not to use it, so it falls short of full coverage.

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 only states that the tool confirms certain elements, but does not disclose whether it makes any changes, what it returns (beyond output schema), or any side effects. The behavior is under-specified.

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

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

A single sentence that is front-loaded with the main action and resources. No wasted words, and the structure is efficient.

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

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

Given the tool's simplicity (0 parameters) and the presence of an output schema, the short description is mostly adequate. It provides the essential purpose and timing, though it could add a hint about the output format or what 'confirm' entails beyond the 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?

The tool has zero parameters, so the input schema is trivially complete (100% coverage by default). No parameter descriptions are needed, and the 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?

The description uses a specific verb ('Confirm') with clear resources ('hosting, credentials, environment variables') and a contextual trigger ('before generating demo apps'). It distinguishes this readiness-check tool from other sibling tools like test_payram_connection or generate_setup_checklist, though it does not explicitly name alternatives.

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?

Provides a clear situational context ('before generating demo apps') indicating when this tool should be used. It does not mention exclusions or alternatives, but the context is sufficiently clear to guide invocation.

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

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

With no annotations provided, the description carries full transparency burden. It openly declares it as a write operation ('write'), specifies the mechanism (supervisor), requires 'admin JWT with write_system_settings', and clearly states what it does NOT fix. This goes beyond the minimal and gives an accurate behavioral model.

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

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

The description is dense but every clause serves a purpose: action type, trigger condition, workflow, limitation, alternative, and permission. It is front-loaded with 'REMEDIATION ACTION (write)' and uses efficient formatting, with no wasted words.

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

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

The description is complete for decision and invocation: it explains when to use, the expected workflow, the failure mode with a clear alternative, and required permissions. The presence of an output schema means return value details are unnecessary, and the parameter schema handles parameter specifics.

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

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

Schema description coverage is 100%, so baseline is 3. The input schema already explains both parameters with examples and usage ('Omit when using all=true'). The description adds no additional parameter-level semantics beyond what the schema provides.

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

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

The description clearly states the tool restarts a blockchain listener worker via supervisor as a remediation action. It distinguishes itself from diagnostic siblings like check_node_sync by explicitly labeling it as the minimal fix when chains lag or listeners are down.

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?

Provides explicit when-to-use guidance (when check_node_sync reports lagging/listener-down), a step-by-step workflow (check → restart → wait → re-check), and when-not-to-use with an alternative (unreachable RPC → fix dashboard config instead). Also notes required admin JWT permission.

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 only says 'generates' without disclosing side effects like file creation, directory changes, dependency installation, or whether it is safe/non-destructive. This lack of behavioral detail is a significant 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?

The description is a single sentence, front-loaded with the verb 'Generates', and contains no fluff or redundant phrasing. 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?

An output schema exists, and the param schema is complete. The description clarifies the output includes payments/payouts routes and a simple UI. It lacks detail on prerequisites but is adequate for a scaffold tool's complexity.

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

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

Schema coverage is 100%, with each parameter described. The description mentions 'language and framework' but adds no extra meaning beyond the schema. Baseline of 3 is appropriate given the 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 tool 'Generates a minimal full-stack app skeleton with Payram payments and payouts routes (and a simple UI) for a chosen language and framework.' This specifies the verb, resource, and scope, distinguishing it from sibling snippet generators like generate_payment_route_snippet.

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 a use case for bootstrapping a full project, but it does not explicitly contrast with alternatives or state when not to use. The context is clear enough without explicit exclusions, so it earns a 4 rather than a 5.

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 burden of disclosing behavior. It states that it returns a paginated list and implies a non-destructive search operation. However, it omits details such as default behavior with no filters, rate limits, authentication requirements, or potential side effects, making it adequate but not rich.

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

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

The description is two sentences, front-loaded with the primary action, and every word earns its place. It avoids redundancy with the schema and provides a clear, efficient summary.

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 (13 optional parameters) and presence of an output schema, the description is functionally complete. It communicates the core capability and return type. A minor improvement would be explicitly noting that all filters are optional, but the schema already indicates no required parameters, so the current description suffices.

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 covers all 13 parameters with descriptions (100% coverage), so the description does not need to add parameter details. The mention of 'status, network, currency, dates, webhook status, and pagination' broadly aligns with schema properties but adds no new semantic meaning. Baseline 3 applies per rubric.

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

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

The description uses a specific verb+resource combination ('Search and filter payments') and clearly enumerates the filter dimensions (status, network, currency, dates, webhook status) and pagination. It distinguishes itself from sibling lookup_payment by emphasizing filtering and paginated list 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 implies usage context: when you need to search/filter a list of payments with full control over filters and pagination. However, it does not explicitly state when not to use it (e.g., for single-payment lookup) or mention sibling alternatives like lookup_payment, so it stops short of full guidance.

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

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

No annotations are provided, so the description carries the full burden. It does disclose that the tool returns a router that posts to the payment endpoint, which is transparent about the core behavior. However, it doesn't clarify that this is code generation (a snippet string) or mention any potential side effects, authentication, or constraints that might be relevant.

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 conveys the essential information: what it returns and the endpoint. No wasted words, perfectly concise for a snippet-generation 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 the low complexity (0 parameters, output schema exists, simple direct return), the description is complete enough. It states the return type and the endpoint. While it doesn't detail the request body or integration steps, the output schema likely covers return structure, and the description is sufficient for this 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?

The tool has zero parameters, so the schema is trivially 100% covered. According to the baseline for 0-param tools, a score of 4 is appropriate. The description doesn't need to add parameter semantics because none exist.

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 Express router that posts to a specific Payram endpoint. The verb 'Returns' and resource 'Express router' are specific, and the mention of 'Express' differentiates it from sibling snippet tools for other frameworks (FastAPI, Go, Laravel, etc.).

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

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

No explicit guidance is given on when to use this tool versus alternatives. The description merely states what it does without mentioning alternative snippet generators or framework-specific selection criteria. The usage is only implied by the tool name.

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

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

With no annotations, the description must carry behavioral transparency. It says 'Returns a FastAPI handler', which implies it generates code, but it doesn't explicitly confirm that no payment is executed at generation time, or mention authentication or side-effect expectations. This is a moderate gap for an unannotated 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 a single, front-loaded sentence that conveys all essential information without filler. Every word earns its place.

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

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

The tool has no parameters and an output schema exists, so the description doesn't need to explain return values. It covers framework (FastAPI), target API (Payram create-payment), and the nature of the output (handler). It could more explicitly say 'code snippet' to avoid any ambiguity, but this is largely mitigated by the title and the word 'Returns'.

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 properties, so there are no parameters to describe. The baseline for 0-parameter tools is 4, and the description correctly avoids introducing any unnecessary parameter 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 exactly what the tool does: it returns a FastAPI handler that calls Payram's create-payment HTTP API. This is a specific verb ('Returns'), resource ('FastAPI handler'), and target API, clearly distinguishing it from sibling snippets for other frameworks or HTTP/SDK variants.

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 makes the intended context clear: you need a FastAPI handler for Payram's create-payment API. It doesn't explicitly mention alternatives or when not to use it, but the FastAPI scoping is enough to guide selection among the many framework-specific 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 carries the transparency burden. It states the tool returns a handler and names the proxied endpoint, which is informative, but it does not disclose any potential side effects, dependencies, or the exact content of the generated handler. It is adequate but not rich for a code-snippet 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 a single, well-structured sentence that immediately conveys the tool's output and behavior. There is no filler or repetition, making it highly concise and easily scannable.

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

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

For a simple, zero-parameter snippet generator with an output schema, the description is sufficient. It covers the core function and the proxying behavior, though it could optionally hint at the handler's request/response details. Overall, it is complete enough for an AI agent to know what to expect.

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

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

The tool has zero parameters and an empty input schema. With no parameters to document, the baseline score of 4 applies, and the description does not need to add parameter-level 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 'Returns a Gin handler that proxies /api/pay/create to Payram's create-payment API.' This uses a specific verb (returns) and resource (Gin handler), and explicitly identifies the route and target API. It distinguishes from sibling framework-specific snippet tools by naming Go/Gin and the payment-route 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 the tool is for generating a Go/Gin payment-route handler, but it does not explicitly state when to use it over alternate framework snippets like Express or FastAPI. There is no comparison or exclusion guidance, leaving usage to be inferred from the title and tool name.

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 responsibility for disclosing behavior. It reveals that the returned controller posts to a specific endpoint, but it omits details such as HTTP method nuances, authentication requirements, request/response shape, or any side effects. For a no-annotation tool, this is 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?

The description is a single, concise sentence that front-loads the key information: what is returned and what it does. Every word earns its place, and there is no redundancy with the title or 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?

For a zero-parameter snippet generator, the description is largely sufficient: it identifies the framework, target endpoint, and overall purpose. Since an output schema exists, the description need not detail return values. However, it could slightly improve by mentioning that the returned value is runnable code or a snippet, though the title already implies this.

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

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

The tool has zero parameters and the schema coverage is vacuously 100%, so the baseline for parameter semantics is 4. The description correctly adds no parameter details, which is appropriate since there are none to explain.

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

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

The description uses a specific verb ('Returns') and resource ('Laravel controller') with a clear action ('posts to Payram's /api/v1/payment endpoint'). It clearly distinguishes itself from sibling snippet tools by naming both the framework (Laravel) and the target endpoint.

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 Laravel projects by stating it returns a Laravel controller, but it does not explicitly state when to use this over alternatives or mention any exclusions. The sibling names like snippet_express_payment_route imply alternatives, but the description itself offers no direct comparison or selection guidance.

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

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

With no annotations provided, the description carries the full transparency burden. It only says the tool returns a route snippet that calls an API; it does not disclose whether the snippet is complete, includes error handling, requires additional setup, or any other behavioral details. This is 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?

The description is a single, focused sentence with no filler words. It immediately conveys the tool's purpose and scope.

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 (0 parameters) and the presence of an output schema, the description is sufficient to understand what is returned. It could mention the snippet content in more detail, but for a code-snippet generator with no inputs, the description 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 tool has zero parameters, so the schema already fully describes the input. The description does not need to add parameter semantics, and the baseline for 0 params is 4.

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 a specific action and resource: it returns a Next.js App Router API route that calls Payram's create-payment HTTP API. This distinguishes it from sibling snippet tools for other frameworks and from more general HTTP/SDK snippet generators.

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 Next.js App Router projects, but it does not explicitly state when to use this over alternative framework-specific snippets or provide exclusions. Usage context is clear but not directly contrasted with 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 are provided, so the description carries the full burden. It discloses that the tool returns a controller code snippet and identifies the endpoint it calls, which is basic but sufficient for a simple snippet generator. However, it omits any detail about the snippet's contents (e.g., HTTP method, request/response shape, dependencies), so richer behavioral context is lacking.

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: 'Returns a Spring Boot controller that calls Payram's /api/v1/payment endpoint.' Every word contributes value, with no filler or repetition of the tool name.

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

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

Given the tool has no parameters and an output schema is present, the description is largely sufficient: it states the output (controller), the framework (Spring Boot), and the endpoint. The title mentions 'create-payment' and the description implies it via the payment endpoint, but explicitly stating the create-payment purpose would eliminate a minor 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 input schema has zero properties, so the parameter baseline is 4. The description adds meaning by specifying the framework (Spring Boot) and the target endpoint, which is the only 'input' context the agent needs. There are no parameters to explain, so the description adequately 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 uses a specific verb ('Returns') and identifies a distinct resource ('Spring Boot controller') plus the exact endpoint ('/api/v1/payment'), clearly differentiating this from sibling language-specific snippets like snippet_express_payment_route or snippet_fastapi_payment_route.

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

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

The description provides clear context: a Spring Boot controller calling a specific payment endpoint, making the intended use case obvious. It does not explicitly exclude alternatives or name which sibling to use instead, but the Spring Boot mention in both the title and description effectively communicates when to select this 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?

With no annotations provided, the description carries the full burden. The word 'suggests' implies a non-destructive, advisory behavior, but it does not explicitly state whether the tool creates files, returns a plan, or requires any project context. The behavior is partially transparent but lacks detail.

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 conveys the tool's purpose without wasted words. It is appropriately concise for a tool with no parameters and a straightforward function.

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 params, output schema present), the description covers the essential purpose. It could be slightly more complete by noting when to use it relative to scaffolding tools, but overall it is adequate for a suggestion-only 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 tool has zero parameters and an empty input schema, so there is nothing to explain. Per the rubric, 0 parameters warrants a baseline of 4; the description appropriately adds no parameter-specific details.

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 verb ('Suggests') and resource ('backend folder/file structure') for integrating Payram. The word 'suggests' distinguishes it from sibling tools like scaffold_payram_app, which implies actual creation, making the purpose unambiguous.

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

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

The description gives only a broad context ('for integrating Payram') but provides no explicit guidance on when to use this tool versus alternatives such as scaffold_payram_app or generate_setup_checklist. There are no exclusions or alternative recommendations.

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 transparency burden. It discloses the fallback behavior (returning an .env template when params are missing) and implies a read-only network check, but it doesn't explicitly state side effects, success/failure behavior, or auth requirements beyond using the API key.

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 the primary action stated first and the conditional fallback second. Every word contributes meaning, and it is appropriately sized for the tool's simplicity.

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

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

The tool has an output schema and only two optional parameters, and the description covers the main purpose and fallback. It is complete for a connectivity check, though it doesn't explicitly relate to sibling tools or describe the output format—both are covered by external schema/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?

Schema description coverage is 100%, so baseline is 3. The description adds context about what happens when parameters are not provided, which complements the schema's explanatory text and clarifies the optionality of both parameters.

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

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

The description clearly states the tool's function: it checks a specific endpoint (/api/v1/payment) on a Payram server using baseUrl and apiKey. The verb 'Checks' and the resource are specific, and it distinguishes from sibling tools that check project readiness or node sync.

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