get_beingFetch one entity profile with its full cited references ledger. Every claim in the profile is backed by a citation into the document or sighting archive.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile with readOnlyHint=true and destructiveHint=false. The description adds useful context about the cited-references ledger and citation backing, but it does not address errors, auth, pagination, or exact return format.
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 filler, front-loading the action and resource while immediately stating the ledger feature that differentiates the tool. 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 simple one-parameter read tool, the description conveys the main returned content (profile plus cited references) and relies on annotations for safety. However, it omits slug semantics, error behavior, and any mention of how the cited ledger is structured, so it is not fully self-sufficient.
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 required slug parameter with 0% description coverage, and the description does not explain what slug means, where to obtain it, or what format it should take. It only weakly implies that the slug selects which entity profile to fetch.
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 names a specific verb and resource ('Fetch one entity profile') and highlights the distinguishing feature ('full cited references ledger'). The word 'one' clearly separates it from list-style siblings such as list_beings.
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 tool is for fetching a single entity profile, but it never explicitly states when to use it over alternatives like list_beings or get_document. Usage context is inferable from the wording but not directly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool pairs a single action (get, list, search, related) with a distinct resource type, so there is no real overlap. Cross-references in descriptions also actively clarify the intended separation between search_documents, search_videos, search_semantic, and the get_video full-detail endpoint.
All tools follow a consistent lowercase snake_case verb_noun pattern: get_*, list_*, search_*, and related_*. There are no mixed conventions, vague generic verbs, or unpredictable naming styles.
Fourteen tools is well within the ideal range and each one earns its place: five getters, four search methods, three listers, and two related-content navigators. The count is broad enough to cover the research archive without becoming bloated.
The archive is retrieval-focused, and the tool surface covers all major entities: documents, news, sightings, videos, and beings, plus bidirectional related-content browsing. Search, semantic search, and source-key listing provide the discovery paths a research archive needs; no obvious dead ends or missing core operations are apparent.