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ck_result_peek

Read specific byte ranges from a completed delegate run's stdout to avoid loading large outputs into context. Use the result_ref and package_root to locate stored output, optimizing token usage.

Instructions

Peek at the full stdout of a previously completed ck_delegate embedded run without loading it all into context. Use result_ref and package_root returned by ck_delegate to locate the stored output. Supports byte-range reads: pass peek_bytes to limit how much to load, and offset to skip ahead. Use result_length (returned by ck_delegate) to decide whether to peek, pass the ref downstream, or skip loading entirely. This is the RLM variable-encapsulation pattern: treat large sub-agent outputs as named references, not inline blobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNoByte offset to start reading from (default 0).
package_rootYespackage_root returned by ck_delegate for the completed embedded run.
peek_bytesNoHow many bytes to read (default 2000, max 32000).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bytes_readNo
outputNo
total_bytesNo
truncatedNo
Behavior4/5

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

With no annotations, the description fully discloses that the operation is a read-only peek, supports byte-range reads, and has a max of 32000 bytes. It explains it uses stored output and does not load all into context. No behavioral traits are hidden, and there is no contradiction.

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 moderately concise with multiple sentences, each adding value. It is front-loaded with the main purpose, then details parameters and usage pattern. Slightly longer than necessary but not wasteful.

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 simplicity (3 parameters, 1 required) and presence of an output schema, the description covers the usage pattern well. It explains the RLM variable-encapsulation pattern, giving extra context. Could mention the return value type but output schema already provides 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?

Schema coverage is 100%, and the description adds context beyond the schema. It explains that offset and peek_bytes control byte-range reads, and that package_root comes from ck_delegate. It also mentions default values (2000 for peek_bytes) which the schema does not explicitly state in text.

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 peeks at stdout of a ck_delegate run without loading all into context. It specifies the verb 'peek', resource 'stdout', and scope. It distinguishes from siblings by referencing ck_delegate and the pattern of not loading full output.

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?

Provides explicit guidance on using result_ref and package_root from ck_delegate, and describes byte-range reads with peek_bytes and offset. It mentions using result_length to decide whether to peek, pass the ref, or skip. However, it does not explicitly state when not to use this tool or provide direct 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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