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build

Rebuild the search index from help sources, consolidating markdown and creating FTS index with chunking. Returns job ID for async progress tracking.

Instructions

Пересобрать индекс: распаковка .hbk -> консолидация md-корпуса -> индексация FTS + чанкование. Выполняется асинхронно: возвращает job_id сразу, результат и прогресс — через build_status. Может занять минуты. Параметры chunk_size/chunk_overlap (в символах) задают размер чанка и перекрытие при разбиении длинных статей.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoЯзык: ru/en (по умолчанию из конфига)
forceNoПересобрать даже если индекс актуален
cleanupNoУдалить corpus после индексации
sourcesNoИсточники для сборки (по умолчанию все из конфига)
chunk_sizeNoЦелевой размер чанка в символах (по умолчанию 1500)
chunk_overlapNoПерекрытие соседних чанков в символах (по умолчанию 200)
Behavior4/5

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

With no annotations present, the description carries the full burden and does well: it discloses asynchronous behavior (returns job_id immediately), potential runtime ('Может занять минуты'), and points to build_status for progress. It does not explicitly mention side effects like overwriting an existing index, but 'пересобрать' strongly implies it. This is meaningful behavioral context beyond a bare summary.

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 compact: three sentences that front-load the purpose and pipeline, then add async behavior, timing, and parameter clarification. There is no fluff or repetition; every sentence contributes essential information.

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 absence of an output schema and annotations, the description covers a reasonable amount: async job lifecycle, job_id return, progress via build_status, expected duration, and chunking semantics. It does not detail default values or side effects for force/cleanup, but the schema handles parameter-level details, leaving only minor gaps.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds extra meaning for chunk_size/chunk_overlap by explaining they are in characters and used when splitting long articles, which complements the schema's brief descriptions. This additional context justifies a slightly higher score.

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 leads with a specific verb and resource: 'Пересобрать индекс' (rebuild the index), and outlines the exact pipeline: unpack .hbk, consolidate md corpus, FTS indexing + chunking. It also distinguishes itself from the sibling tool build_status by stating that build returns a job_id and that result/progress are obtained via build_status. This is unambiguous.

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?

The description clearly indicates when to use this tool: when an index rebuild is needed. It also specifies the asynchronous nature and directs the agent to build_status for progress and results. However, it does not explicitly state when not to use it or mention alternatives such as search or discover, though the core use case is fairly obvious.

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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