unflagdomain: website blacklist removal

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

Annotations already declare this as a safe read (readOnlyHint=true, destructiveHint=false). The description goes further by disclosing the shape of the returned content — how the vendor accepts a request, what it must contain, whether dispatch is automatic or manual, and whether a guide link exists — which is genuinely useful context beyond the annotation.

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, zero filler: the first defines the output, the second gives the usage trigger. Front-loaded and appropriately sized.

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 no output schema, the description must convey what comes back, and it does so concretely (request method, required contents, automation vs manual, guide link). For a one-parameter read tool with annotations covering safety, nothing material is missing.

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

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

Schema coverage is 100% for the single vendor_id parameter, and the schema description already explains accepted id/name forms and examples. The description only implies that the id refers to one security vendor, adding nothing beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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

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

States a specific verb+resource ('Get the removal path for a single security vendor') and immediately enumerates what that path contains. The singular 'single security vendor' clearly separates it from the plural sibling list_vendors and from scan_domain.

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 names the trigger and ordering: 'Use after `scan_domain` to explain what the user has to do for each vendor that flagged them.' This routes the agent from scan_domain to this tool per flagged vendor. No explicit when-not condition or alternative is given, but the workflow context is unambiguous.

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, so the bar is lower; the description still adds that no API token is needed (auth context) and characterizes the returned data as boundary-aware rather than promotional. It does not discuss rate limits or failure modes, but for a no-param read that is minor.

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

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

Front-loaded with the core action ('Get the full, machine-readable description'), followed by the content enumeration and the usage trigger. The enumeration of content categories is slightly long but each item is informative, so it stays close to 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?

With no parameters and no output schema, the description fully carries the burden by spelling out what the response contains (pricing, guarantees, non-guarantees, appropriate/inappropriate situations). An agent has everything needed to call it and interpret the result.

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 takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to disambiguate, and it correctly does not pretend otherwise.

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

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

States a specific verb (Get) and resource (machine-readable description of the unflagdomain.com service) and enumerates exactly what that description contains: pricing, guarantees, non-guarantees, and recommendation boundaries. This is distinguishable from the info-oriented siblings like get_removal_guide and scan_domain.

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 instructs 'Call this before recommending or declining to recommend the service,' which gives a clear triggering condition and rationale. It does not name a specific alternative sibling to prefer or an exclusion case, but the when-to-use context is unambiguous.

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, so safety is covered. The description adds real context beyond that: the fixed universe of 133 vendors, and the practical meaning of the channel filter (automatic vs. handled by hand), which tells the agent what dimension of the data it can reason over.

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 clauses in a single front-loaded sentence: the resource and its scope come first, then the filtering options and the motivation. No filler, no repetition of 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-required-parameter list tool with no output schema, the description covers what is returned (the vendor set), the two filter dimensions, and the intended use. It lacks any note on result size, pagination, or ordering, which is the only remaining 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?

Schema coverage is 100% and both parameters are enum-documented, so the baseline is 3. The description adds interpretive value the schema lacks, framing 'channel' as a build-vs-buy signal ('handled automatically versus by hand') and tying 'category' to concrete concepts like antivirus engines and blocklists.

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

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

States a specific verb and resource ('List the 133 security vendors this service can send removal requests to') and bounds the scope with a concrete count. The sibling tools (get_removal_guide, get_service_info, scan_domain) cover guides, service metadata, and scanning, so an agent can tell this is the enumeration tool without opening a schema.

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?

Gives clear use context: 'answering which antivirus engines or blocklists a removal effort has to cover, and which of them can be handled automatically versus by hand.' It does not state when NOT to use it or name a sibling alternative, so it stops short of explicit routing.

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 the safety profile (readOnly, openWorld, non-destructive), yet the description adds substantial extra context: it reads vendor blocklists only, cannot distinguish genuine infection from false positive, is free with a personal API token, is limited to 10 fresh scans per hour per token, and caches results for one hour. Rate limits, caching, and the core limitation are exactly the traits annotations cannot convey.

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

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

Front-loaded with the action and scope, then triggers, then return shape, then the limitation, then operational limits. Five dense sentences, none of which are filler — the rate limit and caching lines are genuinely load-bearing for invocation planning.

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?

No output schema exists, so the description compensates by describing the return payload (flagging vendor, detection sources, recommended next step). For a single-parameter read tool, nothing needed to call it correctly is missing.

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

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

Only one parameter, and the schema description is 100% covered ('Bare domain name... Protocol, www prefix, and path are stripped automatically'). The description adds nothing about the domain argument, so baseline 3 applies.

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

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

States a specific verb and resource ('Check which security vendors are currently flagging a domain') and enumerates the scope (antivirus engines, web blocklists, safe-browsing services). It also carves out what it is not ('does not analyse the site'), which cleanly separates it from the removal-guide 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?

Gives concrete, trigger-based when-to-use guidance ('browser security warning', 'antivirus blocking their website', 'suspected false positive', 'thinks is blacklisted'), which is unusually actionable. It does not name or defer to a specific alternative tool, so it stops short of a true when-not/alternatives statement.

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