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kaidewu01
by kaidewu01

tech_search

Retrieve observations from your personal knowledge graph with full-text search. Filter by project and use length-only mode to pinpoint relevant memory entries.

Instructions

Recupera observaciones por FTS (como mem_search) (R8).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
projectNo
only_lenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. It does convey that this is a retrieval operation using full-text search, which strongly implies read-only behavior. However, it does not explain how the project or only_len parameters affect results, nor does it describe any other behavioral nuances.

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

Conciseness4/5

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

The description is a single, front-loaded sentence that wastes little space. The '(R8)' tag is cryptic and adds little value for an agent, but it is small noise rather than a structural problem.

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?

An output schema exists, so return-value details are less critical, but the description still omits important operational context: what scope 'observaciones' refers to, how project filtering behaves, what only_len returns, and when this differs from sibling search tools. For a tool with no annotations and three parameters, this is not complete enough.

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

Parameters2/5

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

Schema description coverage is 0%, so the description needed to explain the parameters. It implies that 'query' is the full-text search string, but says nothing about 'project' or 'only_len'. This is only partial compensation for the missing schema descriptions.

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

Purpose4/5

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

The description clearly states the verb ('Recupera') and resource ('observaciones') and the method (FTS), so an agent knows this is a full-text search tool. It does not explicitly differentiate from sibling search tools like personal_search or conversation_search, beyond the 'observaciones' focus and the reference to mem_search.

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

Usage Guidelines3/5

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

The phrase 'como mem_search' implies the intended use case: perform a full-text search similar to the existing mem_search tool. However, it does not explicitly say when to prefer tech_search over alternatives, nor does it describe exclusions or edge cases.

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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