Search Hf Spaces

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

With no annotations, the description carries the full burden, and it says nothing about how the search behaves: what fields are matched, whether results are ranked, or whether the call is a safe read. It only characterizes what Spaces are, not how the search operates. The output schema covers return shape, but the search mechanics remain undisclosed.

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 short, front-loaded blocks with no filler; the core action comes first and the usage scenario second. Slightly sparse rather than bloated, but nothing is wasted.

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?

The output schema removes any need to explain return values, and the purpose is legible. However, for a 2-parameter search with zero schema coverage and no annotations, the missing query/limit semantics leave a real gap an agent would need to fill by trial.

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 0%, so neither parameter is documented anywhere. The description never explains what "query" is matched against (Space name, model, tags, README) or what "limit" controls and whether it caps results or paging. Both parameters remain a guessing exercise.

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 ("Search Hugging Face Spaces") and adds a concrete scope (running web demos, reference architectures, prototypes) that distinguishes it from search_hf_models and search_github_repos by content type. It never names those siblings explicitly, so differentiation is implied rather than stated.

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?

An explicit "When to use" section with a concrete triggering scenario ("user wants to see an interactive working demonstration") gives a clear selection signal. It stops short of exclusions or naming the alternative tool (search_hf_models) for the adjacent case.

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