cone_searchCone search around (RA, Dec).
| Name | Required | Description | Default |
|---|---|---|---|
| ra | Yes | RA in decimal degrees. | |
| dec | Yes | Dec in decimal degrees. | |
| max | No | ||
| catalog | Yes | ||
| radius_deg | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the behavioral profile is clear. The description adds no additional behavioral context, which is acceptable but not enhanced.
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 very concise (6 words), but it lacks structure and fails to provide essential details. While concise, it sacrifices clarity for brevity.
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 tool's complexity (5 parameters, domain-specific), the description is insufficient. It does not explain what a cone search entails, the meaning of parameters, or how it relates to sibling tools.
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 40% (only 'ra' and 'dec' have descriptions). The tool description does not add meaning to the undocumented parameters 'catalog', 'max', and 'radius_deg', which are crucial for usage.
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 'Cone search around (RA, Dec)' clearly indicates the tool performs a cone search given coordinates. It is specific and not a tautology, but it lacks differentiation from sibling tools like 'query_catalog'.
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?
No usage guidelines are provided. The description does not state when to use this tool versus alternatives, nor does it specify any prerequisites or restrictions.
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.
Several tools occupy adjacent roles: ask_pipeworx and ask_pipeworx_beta are currently identical in behavior, discover_tools and suggest_questions both serve discovery, and the astronomy plus Polymarket scanners have overlapping boundaries. The descriptions are unusually detailed and do differentiate most tools, but the number of near-neighbor tools still creates real selection risk.
Names are uniformly snake_case and mostly descriptive, which helps, but the grammatical pattern is inconsistent: verb_noun names (compare_entities, resolve_entity) sit alongside bare nouns (catalogs, object) and bare verbs (remember, recall, forget). It is readable but not a predictable verb_noun convention.
At 35 tools, the surface is well beyond what an agent can comfortably hold in mind. The set mixes a data-research core with one-off utilities like generate_llms_txt, scan_dependency, and AI-visibility auditing, making it feel like a grab-bag rather than a scoped server.
The core data-research workflow is strongly covered: plain and grounded Q&A, deep research, entity resolution, profiles, comparisons, claim validation, recent changes, tool discovery, memory, and subscription lifecycle all exist. Minor gaps remain, such as no subscription-update operation and no generic citation-fetch tool, but there are no serious dead ends.