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gzmagyari

RepoChatMCP

by gzmagyari

chat.search_knowledge

Search persisted knowledge artifacts built from chat history and return snippet matches. Refine results using filters for kind, limit, and batch ID.

Instructions

Search persisted knowledge artifacts directly and return snippet matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNocombined, knowledge, or content_summary
limitNoMax matches to return (default 20)
queryYesSearch query text
batchIdNoOptional batch ID filter
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It only says 'search' and 'return snippet matches,' which implies a read-only operation but does not explicitly confirm safety, state prerequisites (e.g., whether knowledge must be indexed first), or explain what 'directly' means. This leaves significant behavioral ambiguity for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with no redundant words. It states the action and expected output in a clear, front-loaded structure, earning every word.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is too sparse given the lack of annotations, the presence of 4 parameters, and a complex sibling set. It omits practical context like whether prior indexing is required, how results are scoped, or when to prefer this over chat.search or chat.grep. The phrase 'persisted knowledge artifacts' hints at scope but does not elaborate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides 100% parameter descriptions, so the baseline is 3. The description does not add additional meaning about parameter usage beyond the schema, such as how 'kind', 'limit', or 'batchId' influence the search. It simply states the overall purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Search') and resource ('persisted knowledge artifacts'), clearly stating the action and target. The phrase 'directly' and 'snippet matches' adds specificity, and the naming distinguishes it from siblings like chat.search and chat.grep.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided about when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or competing sibling tools. The implied use case is search, but there is no direct comparison to chat.search or chat.grep.

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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