search_writingSemantic search across the published posts, case studies and résumé. Each result is a passage, the URL it is published at, and an "exact" flag saying whether the excerpt is the passage that matched.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many passages to return. Defaults to 5. | |
| query | Yes | What to look for, in natural language. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses the result structure (passage, URL, 'exact' flag) and clarifies that matching is semantic rather than exact, which explains the flag's meaning. Minor omission: no mention of result ordering or relevance guarantees, but the core behavior is transparent.
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 sentences with no filler. The purpose is front-loaded, and the result format explanation is concise and directly useful.
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 simple search tool with no output schema and no annotations, the description covers the search scope and result contents. It lacks explicit ordering details or edge-case guidance, but it is complete enough for correct invocation.
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 100%, so the baseline is 3. The description adds no parameter details beyond what the schema already provides for query and limit; it does not enhance understanding of argument semantics.
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 'Semantic search' with specific resources (published posts, case studies, résumé). Clearly distinguishes from siblings that retrieve or list items (e.g., get_post, list_writing) rather than search across them.
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?
Usage is implied: use when you need to find relevant passages across the blog, case studies, or résumé. However, no explicit when-not or alternative routing is given; the agent must infer from sibling names that this is the search tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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