ask_local

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

With no annotations, the description carries the full behavioral burden but does so well: it discloses the no-echo system hint, that the *answer* (not the prompt) is redacted before returning over MCP (output-only DLP), and by implication that the inbound prompt is not scrubbed. It omits error behavior, timeouts, or model context limits, preventing a 5.

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?

Three tight sentences with the core action and the key security trait front-loaded, and no redundant restatement of the name. Dense and mostly waste-free, though the parenthetical and asterisk emphasis are slightly informal.

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 5-parameter tool with no annotations and no output schema, this covers the operationally critical facts: locality, default no-echo behavior, and output-only redaction. It stops short of describing the return shape or failure modes, but the essential invocation context is present.

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 100%, so all five parameters including the redact/allow_echo defaults are already documented in the schema. The description reinforces the DLP/default behavior but adds no syntax or format detail beyond what the schema provides, so baseline 3 is correct.

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 ("Ask the local Ollama model"), clearly positioning it as the query/inference tool distinct from sibling list_local_models (enumeration) and redact_text (scrubbing). It never names those siblings to differentiate explicitly, so it lands at 4 rather than 5.

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?

It implies usage context by noting secrets/PII are allowed because processing stays local, which is a meaningful hint about when this tool is appropriate. However, it gives no explicit when-not guidance and does not route the agent to redact_text for standalone redaction, so usage is only implied.

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