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search_via_parent

Without local embeddings, delegate semantic search to the parent process to query the shared database for notes or dialog.

Instructions

Delegate a semantic search to the parent process (or any peer with embeddings loaded). For light children spawned with THREADKEEPER_NO_EMBEDDINGS=1, this is how you reach into the shared DB's semantic index without loading PyTorch yourself.

Mechanism: posts a 'search_request' signal addressed to the parent's cid (auto-resolved via tasks.parent_cid; falls back to broadcast if none). The parent's search_proxy daemon answers with a 'search_response' signal. This tool blocks until reply or timeout_s.

scope: 'notes' (default) or 'dialog'. mode: 'hybrid'|'semantic'|'fts' (dialog scope only). k: top-N results, 1..100.

Returns formatted result lines, or 'timeout' if no parent answers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
modeNohybrid
queryYes
scopeNonotes
timeout_sNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

The description explains mechanism, blocking behavior, and return values, but annotations set readOnlyHint=false while the tool performs a read-only search. This contradiction lowers the score to 1.

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 well-structured with front-loaded purpose, mechanism, and parameter details. It is dense but clear, though slightly verbose in the mechanism explanation.

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

Completeness4/5

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

Given the tool's complexity (5 params, no schema coverage, output schema exists), the description covers purpose, mechanism, parameters, and return behavior adequately. It lacks detail on output format but is sufficient.

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

Parameters5/5

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

With 0% schema coverage, the description adds full meaning to all parameters: scope, mode, k, query, timeout_s. It provides defaults, valid values, and bounds (e.g., k=1..100).

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 clearly states the tool delegates semantic search to the parent process, explaining the mechanism and distinguishing from sibling tools like 'search' or 'dialog_search'. It specifies verb and resource.

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

Usage Guidelines4/5

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

Explicitly says to use when child has THREADKEEPER_NO_EMBEDDINGS=1 to avoid loading PyTorch. It implies usage context but does not explicitly state when not to use or compare to alternatives.

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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