Search an ingested local document corpus using BM25 keyword matching with metadata filters to retrieve relevant passages and sources for market research evidence.
Perform lexical BM25/keyword search across the ingested local document corpus with metadata filtering.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| run_id | Yes | ||
| sources | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It does convey genuinely useful behavior — that ranking is BM25 lexical scoring rather than embedding similarity, and that results can be narrowed by metadata — but it says nothing about permissions, rate limits, empty-result behavior, or how the required run_id scopes the corpus.
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?
A single well-formed sentence with the search action and its distinguishing trait front-loaded, and no filler. It is efficient, though the density means a second short sentence about run_id scoping would have been worth the space.
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?
An output schema exists, so return values need not be explained. However, with 0% schema coverage and a required run_id parameter that is never mentioned, an agent lacks enough context to know why the run must be supplied or how sources filtering is expressed. Adequate but with a clear gap.
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 0%, so the description must compensate for all four parameters. It only loosely gestures at 'query' (keyword search) and 'sources' (metadata filtering), and says nothing at all about the required run_id or the limit/default-10 paging parameter — a significant gap for a 4-param tool.
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 gives a specific verb (search) and resource (ingested local document corpus) plus the retrieval method (lexical BM25/keyword). Naming the algorithm implicitly separates it from search_semantic and search_source, but it never names those siblings explicitly, so the differentiation is inferential 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?
Usage is implied rather than stated: 'lexical BM25/keyword search' suggests it fits exact-term matching better than a semantic sibling, and 'with metadata filtering' hints at scoped queries. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g., search_semantic), which the sibling list makes an obvious omission.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.