Send an LLM request through the caching proxy. Returns cached response if available, otherwise proxies to upstream LLM.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | JSON request body as string | |
| path | Yes | API path (e.g. /v1/chat/completions) | |
| api_key | Yes | API key for the upstream provider | |
| provider | Yes | LLM provider to proxy to | |
| cache_ttl | No | Cache TTL in seconds (default 86400) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It does explain the core caching logic (cached response if available, else proxy), which is good. However, it omits details like handling of proxy failures, cache key derivation, or side effects (e.g., writing to cache). These gaps leave behavior partially 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?
The description is two sentences, front-loaded with the main purpose, and contains no redundant information. Every word earns its place, making it highly concise and well-structured.
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 description is adequate but incomplete given the absence of annotations and output schema. It specifies the core behavior (cached vs upstream response) but lacks details on error handling, response format, and cache TTL specifics. For a tool with 5 parameters and no output schema, a bit more context would be needed for full completeness.
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 input schema has 100% description coverage for all parameters, so the baseline is 3. The description does not add any additional meaning to the parameters beyond the schema, but since the schema already documents each parameter, no deduction is warranted.
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 tool's function: 'Send an LLM request through the caching proxy.' It uses a specific verb ('send') and resource ('LLM request'), and differentiates from the sibling tool 'health' by focusing on proxying and caching. The caching behavior further clarifies the purpose.
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 provides clear context: it is used when needing to send an LLM request via the caching proxy, returning cached or upstream responses. No explicit alternatives are mentioned, but the only sibling is 'health,' which is not a substitute. There are no exclusions, and the intended use is obvious, though no explicit when-not-to-use guidance is provided.
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.
The two tools have completely distinct purposes: cache_query handles LLM requests through the proxy, while health is a simple status check. No ambiguity exists between them.
cache_query follows a verb_noun pattern, but health is a single noun without an action prefix. Minor deviation, but names are clear and readable.
With only 2 tools, the set feels slightly thin but appropriate for a focused proxy service. The core operation and a health check are the essentials.
The main lifecycle of a caching proxy is covered by cache_query. Missing cache-specific operations like invalidation could be useful but are not essential for basic proxy functionality.