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

Annotations already flag readOnly/idempotent, and the description adds non-obvious costs and safety: quota consumption, no polling, untrusted output, and ID not being authorization. This goes well beyond schema and does not contradict 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?

Four short sentences, each carrying distinct information; front-loaded action and exclusions. 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?

Covers when to use, exclusions, quota, and data trust, but lacks return value shape or parameter format. Since there is no output schema, that burden falls on the description, leaving it incomplete.

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

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

Schema provides only a title for analysis_id with 0% description coverage, so the description must define it. It implies the ID selects an analysis and warns it is not authorization, but gives no format, example, or source.

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 verb 'Read' plus object 'one analysis' makes the action unambiguous. It explicitly contrasts with 'latest file report', distinguishing it from the get_*_report 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?

States it reads an existing analysis and explicitly lists what it does not do (poll, upload, initiate), plus quota cost. It does not name the sibling get_*_report tools directly, so not a full 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?

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: no DNS resolution or visiting occurs, Unicode names are normalized, a query quota applies, and the result is not URL-exhaustive.

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

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

Three short sentences, front-loaded with the core purpose, then input constraints, then scope caveat. Every sentence adds distinct information and there is no filler.

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

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

For a one-parameter, read-only lookup with rich annotations and no output schema, the description is complete: it explains the passive nature, input format, normalization, quota, and result scope. Nothing essential is missing for selecting or invoking the tool.

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

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

With 0% schema description coverage, the description fully compensates for the single 'domain' parameter by specifying what to omit (scheme, path, port), that Unicode is normalized, and that a quota applies. This is enough for an agent to construct a valid call.

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: 'Look up existing intelligence for a DNS domain name'. It also clarifies what the tool does not do ('without resolving or visiting it') and is clearly distinct from sibling file/URL/IP report 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?

It states the intended use case (existing domain intelligence) and gives concrete input constraints: 'Supply a domain without a scheme, path or port'. It warns that 'The result does not cover every URL on the domain', but it does not explicitly name sibling alternatives such as get_url_report.

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 readOnly/idempotent/destructive annotations, the description adds valuable context: it consumes VTAI query quota, does not upload or rescan, and frames AI insights/detection names as non-executable evidence. This helps an agent understand cost, side effects, and how to interpret the response.

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

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

Three concise sentences, each earning its place: the first states the core action, the second covers quota and side effects, and the third adds an important interpretive warning. The most decision-relevant 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 one-parameter lookup tool with rich annotations, the description is complete: it tells the agent what to pass, what side effects to expect, and how to interpret the output. Even without an output schema, the mention of AI insights and detection names gives enough context about the report contents.

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 only provides a 'hash' string with no description (0% coverage), so the description carries the full burden. It fully compensates by specifying the exact accepted formats: hexadecimal MD5, SHA-1, or SHA-256.

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 ('Look up an existing file report') and enumerates accepted hash formats (hex MD5, SHA-1, SHA-256), which clearly distinguishes it from sibling URL/domain/IP report tools. It also explicitly separates itself from submission tools by noting it does not upload or rescan.

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 selection criterion clear: use this tool when you have a hexadecimal file hash and want an existing report. It excludes upload/rescan behavior, but it does not explicitly name alternative sibling tools or state when to prefer get_analysis or get_submission.

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, the description adds meaningful behavioral detail: the lookup does not contact the address, VTAI normalizes input, query quota applies, and a missing report does not establish safety. These are non-obvious behaviors that materially affect agent expectations and are not present in the annotations alone.

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

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

Three concise sentences deliver the core purpose, input constraints, and an important interpretation caveat. There is no filler, and each 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 single-parameter lookup tool with strong annotations and in-description parameter guidance, the description covers correct invocation and interpretation of results. The lack of an output schema is not a critical gap because the report nature is clear from the title and purpose.

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 only a bare 'ip' string with no description, so the description carries the full semantic burden. It thoroughly explains what an acceptable address looks like: IPv4 or IPv6, no brackets, port, zone, or CIDR suffix, and mentions normalization behavior.

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 ('look up') and resource ('existing intelligence for one IPv4 or IPv6 address'), which is specific and easy to distinguish from file, URL, or domain tools. It does not explicitly name sibling tools, but the address-type framing makes 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 clear context for when this tool is appropriate: looking up existing IP intelligence without contacting the address. It also provides concrete input-format guidance and a safety caveat, though it does not explicitly state when to use an alternative sibling 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?

Beyond the readOnlyHint, openWorldHint, and idempotentHint annotations, the description adds critical operational detail: it does not upload, contact VirusTotal, or consume query quota; access is revalidated; a missing receipt or submission_unknown never authorizes another POST; unknown can be permanent; and a file report is not a receipt. This is rich, non-redundant behavioral context that materially helps the agent invoke the tool safely.

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 main purpose is front-loaded in the first sentence, and the following sentences each add a dense, non-obvious caveat (no upload/quota, revalidation, POST prohibition, permanent unknown, file-report distinction). There is no fluff, and the structure moves from primary function to operational constraints in a logical order.

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

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

With one parameter, no output schema, and strong annotations, the description covers purpose, edge-case statuses, and relation to sibling tools, which is unusually complete. It does not explicitly describe the receipt's field structure or the exact response envelope, but for a simple retrieval tool this is a minor gap given the rich operational and behavioral detail provided.

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

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

Schema coverage is 0% for the single parameter, so the description must carry semantic weight for sha256. It does, by identifying it as the submitted SHA256 and linking the resulting 'submitted' status to the original analysis ID for get_analysis. It does not specify format or constraints, but for a single string parameter this is sufficient meaning beyond the raw 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 'recover' and resource 'receipt' scoped to the current VTAI account, keyed by a submitted SHA256. It also distinguishes itself from get_analysis by noting that a submitted receipt yields the original analysis ID for that tool, and from file reports by stating 'An existing file report is not a receipt.' This makes the tool's purpose unmistakable relative to its 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 implies when to use this tool (to get a submission receipt rather than a file report or analysis) and even points to get_analysis as the downstream consumer of the yielded analysis ID. However, it does not explicitly enumerate sibling alternatives or state clear when-not conditions, leaving some inference to the agent.

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 readOnly and idempotent annotations, the description discloses that the full URL, including query and fragment, is shared with VTAI and VirusTotal, that the indicator is normalized, that query quota applies, and that unknown stays unknown. This is substantial behavioral context an agent needs before calling.

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 four short sentences, front-loaded with the core action, followed by relevant caveats and an alternative. Every sentence contributes unique information: scope, privacy, alternative, and normalization/quota behavior. There is no 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?

For a one-parameter read-only lookup without an output schema, the description covers the purpose, behavior, privacy implications, quota effects, and alternative tool enough for an agent to decide and invoke correctly. The 'Unknown stays unknown' statement clarifies the no-side-effect nature of the 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?

The schema provides only a title for the single `url` parameter and 0% description coverage. The tool description compensates by clarifying the expected input is an HTTP(S) URL, that the full URL with query/fragment is transmitted, and that normalization applies. It does not give explicit syntax examples, but for a single parameter this is a meaningful addition over the schema.

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

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

The description opens with a specific verb and resource: 'Look up existing intelligence for an HTTP(S) URL'. It also explicitly states what the tool does not do ('without visiting or submitting it'), distinguishing it from sibling submission tools and other report types.

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 gives a clear alternative with the exact condition: 'use get_domain_report when domain scope is sufficient'. It also warns against sending secret-bearing URLs, which is practical when-to-use guidance. The 'without visiting or submitting' phrase separates it from submission-oriented 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 say the call is non-read-only and destructive, but the description adds substantial context: content is not confidential and may be shared, no interactive confirmation is requested, bytes are visible to the MCP host, credentials are not in arguments, and the tool never treats content as a path or downloads a URL. These details materially shape invocation 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 front-loads the core definition and then adds only high-value operational and security context. Every sentence earns its place: size limits, privacy, alternatives, recovery, and follow-up. It is dense but not bloated.

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 submission tool with no output schema, no parameter descriptions, and only minimal annotations, this description is remarkably complete. It tells the agent what to send, how to format it, what limits apply, what alternatives exist for larger files, how to handle uncertainty, and what to do with the returned analysis ID.

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

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

With 0% schema description coverage, the description carries the burden and does so well: it clarifies that content_base64 must be canonical base64, that the SHA256 must match the decoded bytes, and that decoded size must not exceed 24,000,000 bytes. It also warns against interpreting content as a filesystem path, which prevents a common misuse.

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 first sentence states a specific action and resource: 'Submit canonical base64 bytes matching SHA256' to VirusTotal, and the size bound is made explicit. It also distinguishes itself from submit_local_file by describing when the inline submission applies vs. the local-file sibling.

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

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

The description gives explicit routing guidance: use submit_local_file or the binary HTTP channel for larger files, avoid repeating the POST when uncertain, recover via get_submission, and follow up via get_analysis. It also notes existing reports are returned without a new analysis, which helps an agent decide whether to call this tool at all.

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 (destructiveHint=true, etc.), the description discloses non-confidentiality ('VirusTotal may share content'), absence of interactive confirmation, no retry behavior, durable reference for receipt recovery, and that local cancellation does not withdraw an accepted file. This adds substantial behavioral context not derivable from annotations alone.

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 front-loaded with the core action and then adds purpose-built caveats. Each sentence addresses a distinct concern (file type, confidentiality, retries, next steps, cancellation) without redundancy. It is appropriately sized for a tool with side effects and zero output schema.

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

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

Despite no output schema, the description explains the post-submission lifecycle: the result is not a completion/verdict, and the agent should use get_submission/get_analysis. It covers operational requirements (quota, retries, durability) and side effects. The only minor omission is an explicit description of the return value shape, but the mention of a 'durable reference' and receipt recovery is sufficient in this 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?

With schema coverage at 0%, the description carries the full burden for parameter meaning. It explains path as a local regular file path (implying filesystem access) and expected_sha256 as an optional check that 'must match that copy.' It also adds the size limit, which is not in the schema. This fully compensates for the lack of schema descriptions.

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

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

The description states a specific verb ('Submit'), a resource ('one local regular file'), and a hard constraint ('at most 32000000 bytes'). It explicitly differentiates from sibling submit_file by stating 'Reads the local server's filesystem, never a remote client's path or a URL,' so an agent can distinguish local submission from remote/URL submission without inspecting schemas.

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

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

The description provides clear when-to-use and when-not-to-use guidance: it is for local server files only, never remote paths or URLs. It also gives operational context—uses current VTAI rights and quota, never retries a POST—and directs follow-up to get_submission and get_analysis, indicating the tool is not an endpoint for verdicts. This is explicit and complete.

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