Analyze an entity's digital footprint across official sites, GitHub, package registries, documentation, and third-party sources to evaluate its web presence.
Analyze an entity digital footprint across official, GitHub, package registry, documentation, and 3rd-party sources.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Optional domain hint (e.g. aibuildinfra.com) | |
| entity_id | Yes | Canonical entity ID or name |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It lists the data source categories but does not clarify key behaviors such as whether the tool performs external network calls, how results are aggregated, whether it is read-only, or what the output format looks like. This is a significant transparency gap for an analysis 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 sentence, front-loaded with the action and resource, and lists sources compactly without unnecessary words. It is appropriately sized for what it communicates, though it omits deeper context that would improve usefulness.
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 absence of annotations and output schema, plus the existence of several related siblings, the description is under-specified. It does not explain what 'analyze' produces, how the tool relates to other analysis tools, or any operational caveats. An agent cannot confidently predict the tool's behavior or output from this description alone.
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 both parameters are already documented in the schema. The description adds no additional parameter-level context beyond what 'domain' and 'entity_id' already state. A baseline of 3 is appropriate because the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Analyze') and the resource ('an entity digital footprint'), and enumerates the sources covered (official, GitHub, package registry, documentation, 3rd-party). This distinguishes it from generic search/get siblings, though it doesn't explicitly differentiate from audit_entity_consistency or find_evidence, which could overlap.
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 invoke this tool versus sibling tools such as find_evidence, get_entity, or audit_entity_consistency. The description implies a general analysis use case but provides no context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.