gf_cite
GET cite catalog, or POST one cite packet {kind,id,claim?}.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| kind | No | Optional; if set, POST packet | |
| claim | No |
GET cite catalog, or POST one cite packet {kind,id,claim?}.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| kind | No | Optional; if set, POST packet | |
| claim | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the burden of behavioral disclosure. It reveals the HTTP methods (GET/POST), which imply read vs. write, but omits side effects, permissions, error behavior, or return characteristics. This is a significant gap for a tool involving both query and mutation.
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, front-loaded sentence with no filler or repetition. It conveys the two modes and the packet shape efficiently, making every word meaningful.
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, the description is too terse to be complete. It leaves unanswered how the GET response is structured, how id interacts with GET vs POST, what 'cite packet' contains beyond the listed fields, and what errors or prerequisites exist. The tool has moderate complexity (3 params, nested object) that warrants richer 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?
The description adds the packet structure '{kind,id,claim?}', giving purpose to the parameters beyond the sparse schema. However, it does not clarify the role of 'id' in the GET context or the exact conditions for each parameter, and schema coverage is only 33%, so the description only partially compensates.
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 identifies two distinct operations: GET the cite catalog or POST a cite packet, with the packet shape explicitly specified. This verb+resource structure is specific and differentiates the tool from siblings like gf_dossier or gf_verify.
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 GET vs POST distinction implies when to use each operation, and the schema hints that setting 'kind' triggers POST. However, there is no explicit guidance about alternatives or conditions for choosing between fetch and create beyond this, and no mention of related tools.
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.
Tools are mostly distinct but there is some potential confusion: gf_darshan and gf_package both involve admit/refuse operations, and gf_cite and gf_verify both deal with claims. Descriptions help clarify, but boundaries are not perfectly crisp.
All tools follow a consistent 'gf_' prefix with snake_case resource names. The pattern is uniform across the entire set, making it predictable for agents.
With 9 tools, the server is well-scoped for a federation service. Each tool covers a distinct aspect without excessive bloat or redundancy.
The tool surface covers core operations like citation, darshan sampling, dossier access, packaging, reporting, and verification. Minor gaps exist (e.g., no explicit update/delete for claims), but the existing tools cover the main workflows without causing dead ends.