Batchloom Evidence

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

Annotations already signal read-only and idempotent behavior, and the description adds meaningful traits beyond that: deterministic, free, no remote fetching, no signing/payment, and no semantic verification. It also discloses exactly what categories of issues it reports, which is valuable behavioral context for an agent.

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 tight sentences with no filler. The core purpose and scope are front-loaded, followed by a compact list of checks and then the limitations. Every clause adds useful information.

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

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

For a tool with two parameters and no output schema, the description is complete enough to guide invocation: it states the inputs, the kinds of issues detected, the fact that it produces validated evidence request batches, and the boundaries of its behavior. Combined with the schema constraints and annotations, an agent has what it needs to call this tool appropriately.

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 schema description coverage at 0%, the tool description carries the burden of clarifying the two parameters. It explains that 'report' is text and 'references' are structured refs using [cite:id] markers, and it mentions URL/quote checks. It does not spell out the exact object shape, but the schema supplies types and constraints, so the description adds sufficient semantic grounding.

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 ('audit') with a precise resource ('caller-supplied report text and structured references using [cite:id] markers'), then enumerates the exact checks performed. It also distinguishes itself from evidence-preparation and validation siblings by stating what it does not do, so an agent can select it confidently.

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

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

The description gives clear context: it is a preflight audit that is free, deterministic, and limited to citation/reference checks. The explicit exclusions ('No fetch, signing, payment, semantic verification or claim-coverage score') help an agent avoid using it for those needs, though it does not name a specific alternative tool to use instead.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context beyond that: it specifies that no fetch, payment, or content storage occurs, which goes beyond the read-only hint. It also discloses the size limit (196608 bytes) and states that no authenticity or truth inference is made, which are behavioral traits not in annotations. It doesn't contradict annotations, so a high score is justified.

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

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

The description is concise (two sentences) and front-loaded with core purpose and constraints. Every sentence adds value: it specifies the action, the resource, key behavioral exclusions, and important caveats. No wasted words, and the information is structured logically.

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 comparison tool with a rich input schema and detailed constraints (matching input hashes, size limits), the description is largely complete. It covers the main context: it's offline, no side effects, handling of unreadable sources, and what is not inferred. The schema already documents the nested structure and limits (e.g., max items, byte limits) in the input schema, so the description doesn't need to repeat those. The absence of an output schema is a minor gap, but the description's key behavioral notes are sufficient for an agent to call it correctly.

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

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

Schema description coverage is 67%, with most parameters having descriptions in the schema (e.g., 'inputHash' and 'evidence' have descriptions). The description adds minimal additional parameter meaning beyond what the schema provides, mainly reinforcing that both inputHashes must match the canonical input hash. The baseline for high coverage is 3, and since the description does not significantly enhance parameter understanding beyond the schema, a 3 is appropriate.

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

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

The description states a specific action ('compare'), a clear resource ('two supplied evidence snapshots'), and a key constraint ('bound to the same input'). It clearly differentiates from siblings by emphasizing 'no fetch, payment or content storage', which distinguishes it from tools like prepare_evidence_request or validate_evidence_request that likely involve fetching or validation. The title is also informative.

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

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

The description explicitly says 'No fetch, payment or content storage', which tells the agent when not to use it (for actions that require fetching or storing). It also clarifies that 'Unreadable sources and changed/unknown processing profiles are not classified as quote removal', which prevents misinterpretation of results. It doesn't name an alternative tool directly, but the exclusion of fetch/payment/storage is clear enough to guide selection among siblings.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful behavioral context beyond those annotations: it reads specific contract details, mentions 'safe purchase recovery,' and explicitly rules out network crawling and payment actions. No contradiction with annotations.

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

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

The description is extremely concise: one sentence covering what is read, followed by a short exclusion note. Every phrase earns its place, and the core information is front-loaded.

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

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

For a zero-parameter, read-only inspection tool, the description covers the key return areas and non-behaviors. The lack of a return format is a minor gap, but the low complexity and rich annotations make the definition adequate for an agent to invoke correctly.

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

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

The input schema has zero parameters and schema description coverage is 100% (vacuously). The baseline for a zero-parameter tool is 4, and the description does not need to explain parameter semantics that do not 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 uses a specific verb 'Read' and names concrete resources: price, exact supported hosts, limitations, and safe purchase recovery. It also explicitly states what the tool does not do ('No network crawl or payment'), which helps distinguish it from sibling tools like preview_assets and get_evidence_sample.

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 'No network crawl or payment' clause gives helpful context about what the tool avoids, but it does not explicitly name alternatives or state when to choose this tool over siblings such as get_evidence_sample or prepare_evidence_request. Usage is implied rather than fully stated.

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

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds the meaningful facts that the result is fixed, synthetic, and carries no live-fetch or truth guarantee, which is context beyond the annotation flags. There is no contradiction with annotations.

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

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

Two short sentences, each earning its place: the first states the operation, the second states the limitations. The most important scope information is front-loaded.

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

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

For a no-argument, read-only fixture tool, the description is sufficient: it names the resource, states the synthetic or fixed nature, and flags non-guarantees. It does not describe the returned fixture's shape, but the absence of an output schema and the intentionally simple scope make that omission minor.

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, there is no parameter semantics for the description to add. The empty schema fully documents the input contract, so the baseline score 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 opens with 'Read a fixed synthetic evidence example,' providing a concrete verb and resource. This clearly frames the tool as a read-only fixture accessor, distinct from live-data or validation tools. The title 'citation evidence fixture' reinforces the specific resource.

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 second sentence gives a clear negative usage signal: this is not for live data, payment-dependent content, or assertions of truth. That tells an agent when not to use it, but it does not name a specific sibling alternative such as get_manifest or get_evidence_contract for live or validated evidence.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds the content scope (what is read) and explicitly states it does not buy or sign, which are behavioral details beyond the annotations. It does not contradict the annotations; it reinforces them with additional context.

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

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

The description is a single sentence that front-loads the action ('Read') and lists the specific content in a compact, comma-separated list. It includes a clarifying exclusion at the end. There is no filler or redundancy; 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?

For a no-parameter, read-only tool with annotations already covering safety, the description is complete. It lists exactly what the tool retrieves and clarifies it does not take purchase/sign actions. Since there is no output schema, the description does not need to explain return format; the content scope is sufficient for an agent to decide when to call it.

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

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

The tool has zero parameters, so the schema is fully covered by definition (100% coverage). The description does not need to explain parameters, and it adds no parameter-specific information because there are none. According to the baseline for 0 parameters, a score of 4 is appropriate.

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

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

The description uses a specific verb ('Read') and names the exact resource contents ('free product manifest, source-license price, endpoint limits and purchase/recovery instructions'). It also explicitly states what it does NOT do ('Does not buy or sign anything'), which distinguishes it from purchase or signing tools among the siblings. This is not a tautology; it is clear and specific.

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

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

The description implies when to use this tool (to read the manifest info) and implicitly excludes it from buy/sign operations, but it does not name alternative tools or give explicit when-to-use/when-not-to-use guidance. The statement 'Does not buy or sign anything' is a negative constraint rather than positive routing. So usage guidance is implied, not explicit.

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

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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds useful scope details (three fixed SVG examples, no source toolkit), but it does not describe response shape or any further behavioral nuances.

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 short sentences with no filler. The key facts are front-loaded, and every phrase contributes meaning.

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

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

For a zero-parameter, read-only tool with no output schema, this description is sufficient. It tells the agent what the tool returns and an important limitation (no source toolkit), leaving no critical gap for invocation.

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

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

The tool has zero parameters, so the schema fully covers parameter semantics. The description correctly includes no parameter-specific content, 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 ('Read') and resource ('three free fixed SVG examples'), clearly stating what the tool returns. The phrase 'No source toolkit is included' also helps distinguish it from sibling evidence/sample 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?

There is no explicit guidance on when to use this tool over the sibling tools, nor any mention of alternatives like get_evidence_sample or trial_evidence. The purpose is clear, but the usage context is left entirely to inference.

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

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

The annotations already convey readOnly, idempotent, and non-destructive behavior, but the description adds meaningful non-obvious details: it computes a canonical hash, does not fetch the source, does not generate secrets, does not sign or pay, and leaves source/facilitator capacity unchecked. These details go well beyond the annotation flags and reduce the chance of an agent misusing the 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?

Three tight sentences front-load the core action, then list critical non-actions and a residual limitation. Every sentence earns its place, with no redundant phrasing or marketing language.

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 side-effect-free preparation tool with strong annotations, the description covers purpose, safety, and limitations well. It lacks an explicit statement of return values or next steps, which is notable because there is no output schema, but the intended outputs — hash, payment/client requirements, and storage readiness — are reasonably inferable from the verbs.

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

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

The description does not explain the sources or requireAllSources parameters or how they affect the preparation result. Schema description coverage is only 50%, and the main 'sources' parameter lacks a top-level description; the tool description does not compensate. An agent must rely almost entirely on the schema and x-allowed-hosts for parameter meaning.

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 explicit actions: validate input, compute a canonical hash, and read payment/client requirements and receipt storage readiness. It also distinguishes itself from siblings by listing what it does not do — fetches no source, generates no secret, signs and pays nothing. This gives an agent a precise, resource-specific purpose beyond the generic title.

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 this is a read-only preparation step before a citation evidence purchase retry, and it lists exclusions such as no source fetching, no signing/paying, and unchecked capacity. However, it never explicitly says when to use this tool versus validate_evidence_request or another sibling, nor does it name alternatives. Selection logic is largely left to inference.

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

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

Beyond the annotations (read-only, idempotent, non-destructive), the description discloses meaningful behavioral details: the input is passed directly without a wrapper, there is a 8192-byte serialization limit, and it returns assets and warnings without toolkit source. These add practical context for the agent.

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 compact two-sentence structure that front-loads the core purpose and immediately follows with key constraints. Every sentence contributes essential information without redundancy, achieving high information density in minimal space.

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

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

The description covers the essential operational constraints (input format, size limit, output contents) and correctly notes the single-product limitation, but it omits any usage context or when to choose this tool over siblings. Given the tool's moderate complexity and lack of output schema, it is adequate but not fully 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?

The description does not mention any parameters or their semantics, and schema description coverage is 0%, so it fails to compensate for the lack of inline parameter information. Although the schema itself is richly documented, the tool description adds no parameter-level guidance, leaving the agent to rely solely on 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 a specific verb ('render') and resource ('one product') with an explicit output ('up to three SVG assets') and a distinctive qualifier ('for free'). This distinguishes it from sibling tools focused on evidence and validation, leaving no ambiguity about its function.

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

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

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. While 'for free' hints at a trial purpose, it does not explicitly compare with other tools or state when to prefer it.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful side-effect context: no payment, no durable receipt, and specific per-client/service quota. These details go beyond the annotations and do not contradict them.

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

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

Two short sentences front-load the core action and then list constraints. Every clause carries information—scope, payment, receipt, quota—with no filler 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 2-parameter trial tool, the description plus rich schema and annotations cover the essential call constraints and quota behavior. The main omission is explicit guidance on when to prefer this over the sibling validation/preparation tools, but this is not fatal.

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

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

The description reinforces the schema's maxItems by stating 'one supported source and one quote,' and 'supported source' points to the allowed-host constraint. However, it does not explain requireAllSources or the URL/host matching details, and with schema coverage at 50% it only partially compensates for the gap.

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

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

The description opens with a concrete action ('Try') and precisely scopes the resource: one supported source and one quote using the production extractor. The 'free' and 'one' qualifiers separate it from paid or full validation flows, though it does not explicitly name a sibling alternative.

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 clearly situates the tool as a limited free trial with explicit quota ('2 attempts/client/UTC day'), which implies when this lightweight path is appropriate. However, it gives no explicit when-not-to-use guidance or comparison to sibling tools such as validate_evidence_request or prepare_evidence_request.

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

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

Annotations already indicate readOnly/idempotent/non-destructive behavior, and the description adds meaningful extra context: it returns only summary data, not rendered assets or toolkit source. Nothing here contradicts the annotations or hides side effects.

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 only two sentences, with the most decision-relevant facts presented first: scope and cost, input relationship, and return behavior. There is no fluff or redundant wording.

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

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

For a tool with no output schema, the description supplies the key returned fields and explicitly states what it will not return. Combined with the detailed input schema and read-only annotations, this is enough for an agent to call it correctly, though it could say slightly more about the validation-warning format or detailed failure modes.

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 statement 'Arguments are the render input directly' is genuinely useful because it tells the agent to reuse the same render payload rather than wrap it. However, it does not explain the meaning of brand, products, style, theme, or formats, so most parameter semantics are left to schema constraints despite the reported 0% schema description 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 specific verb and resource: 'Validate ... product batch', with clear bounds ('up to 100 products and 3 formats') and expected outputs ('validity, product count, expected asset count and validation warnings'). This clearly separates it from the evidence-related and preview sibling 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 'free' constraint and 'no rendered assets or toolkit source' clause make the intended use case—validation as a preflight check—broadly clear. However, it does not explicitly compare against sibling tools like preview_assets or validate_evidence_request, nor state when one should be preferred over this one.

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

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

The description adds behavioral context beyond the annotations: it states the tool does not fetch pages, does not establish source availability, and involves no payment. These are important behavioral traits not captured by readOnlyHint or idempotentHint alone. It does not contradict any annotation. This extra context is valuable for an agent deciding whether to invoke this 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 two sentences with zero redundancy. The primary action and scope are front-loaded in the first sentence, and the exclusions are efficiently stated in the second. Every word earns its place, 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?

For a tool with only two parameters (one nested) and a rich input schema, the description covers the essential purpose and exclusions. It does not mention return values or error behavior, but since there is no output schema and the tool is read-only, that is not critical. The description adequately complements the schema and annotations to give an agent the necessary context to invoke the tool correctly.

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

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

Schema description coverage is 50% (only requireAllSources has a direct description; sources lacks one). The description partially compensates by describing the operation on 'bounded URLs and literal quotes', which gives meaning to the sources parameter. However, it does not explain requireAllSources beyond what the schema already provides. The item-level descriptions for url and quotes are detailed, so the overall parameter semantics are reasonably covered, but the description itself adds limited unique value beyond the schema.

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

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

The description states a specific action (check bounded URLs and literal quotes against a fixed host list) with clear scope and context (before purchase). It also explicitly disclaims what it does not do (fetch pages, establish availability, payment), which distinguishes it from other tools that might perform those actions. This clearly differentiates it from siblings like audit_report_citations or compare_evidence_snapshots.

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

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

The description provides clear usage context by stating 'before purchase' and clarifies what it does not do, which implicitly tells an agent not to use this tool for fetching or payment. However, it does not explicitly name alternative tools or provide when-not-to-use conditions relative to siblings like validate_batch or prepare_evidence_request. The context is clear but lacks explicit exclusions or alternative routing.

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