mcp_engram_scout

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

No annotations present, but description fully details the pipeline: DuckDuckGo search (no API key), synthesis via Gemma 4B, storage as ZEDOS_DECLARATIVE block (CRS=0.9). Config are given. No surprises.

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?

Concise yet comprehensive: Phase identifier, pipeline summary, usage instruction, example, and config. Front-loaded with purpose. No unnecessary text.

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 tool with 2 parameters and no output schema, the description covers the full flow, return value, configuration, and use case. No missing critical information.

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 covers both parameters fully. Description adds no new semantics beyond what the schema already provides (e.g., default and max for max_results are already in schema). Baseline 3.

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?

Description clearly states the tool searches the web, synthesizes results, and stores them. It is distinct from sibling tools which are about memory/engram operations, not web search.

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?

Provides explicit use case: 'ground a hypothesis in real-world web data before storing it.' Example further clarifies. Does not specify when not to use, but context is clear.

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