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memcp_chunk_context

Breaks a loaded context into smaller, numbered parts for selective access. Supports line, paragraph, heading, character, or regex splitting with configurable size and overlap.

Instructions

Split a stored context into navigable numbered chunks.

Args:
    name: Context name (must already be loaded)
    strategy: Splitting strategy — auto, lines, paragraphs, headings, chars, regex
    chunk_size: Size per chunk (lines for 'lines', chars for 'chars', tokens for 'paragraphs')
    overlap: Overlap between chunks (lines or chars)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
overlapNo
strategyNoauto
chunk_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations present, so the description carries the burden. It discloses the prerequisite (name must be loaded) and strategy options, but does not mention side effects, error behavior, or whether the operation is read-only.

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 short, front-loaded with the purpose, and efficiently uses bullet-style parameter definitions. Every sentence provides necessary 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 tool has 4 parameters (1 required) and an output schema, the description covers parameter semantics and prerequisites. It could mention that output provides chunk indices, but likely the output schema handles that.

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?

With 0% schema description coverage, the description adds value by explaining each parameter's meaning (e.g., size units per strategy). Some details like default behavior for chunk_size=0 could be clearer.

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 verb 'split' and resource 'stored context into navigable numbered chunks'. It is specific and distinguishes from siblings like memcp_peek_chunk which likely views chunks.

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 implies usage context (splitting a loaded context) and explains parameters, but does not explicitly state when to use this over alternatives or provide exclusions.

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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