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Chainsaw MCP Server

Chainsaw: export a result

chainsaw_result_export
Read-onlyIdempotent

Export stored result data as CSV or JSONL text for reports or other tools, with paging to handle large results.

Instructions

Render a stored result as CSV or JSONL text for reports or other tools.

Large results are capped by rows and encoded response bytes; resume next_offset. CSV pages repeat their header. For stored text files resume next_byte_offset; those UTF-8 chunks may split records and must be concatenated before parsing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoColumns for CSV (dotted paths or shorthand). Default overview set.
formatNocsv, jsonl, or text (an alias of csv). CSV flattens the standard columns of hunts and searches; analysis handles use their sampled top-level keys.csv
handleYesResult handle returned by a hunt, search, dump or analysis tool.
offsetNo
max_rowsNoRow cap for the export.
max_bytesNoEncoded response byte budget.
byte_offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior5/5

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

Annotations already declare read-only/idempotent/non-destructive, and the description adds substantial behavioral detail beyond them: results are row- and byte-capped, CSV pages repeat their header, and text-file UTF-8 chunks may split records and must be concatenated before parsing. These are exactly the operational traits an agent needs and cannot get from the schema.

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?

Four sentences, front-loaded with the core purpose followed by paging caveats. Every sentence carries useful information about resumption and encoding, though the phrasing is slightly fragmented.

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?

With no output schema and 7 parameters, the description compensates by covering format selection, row/byte caps, and resumption contracts. Missing only explicit guidance on the handle lifecycle and error conditions, which the schema partially covers.

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 71% and the description supplements it by explaining the offset/byte_offset resumption semantics and the header-repetition behavior of CSV paging, which the schema titles alone do not convey. It stops short of detailing the fields/format interaction fully, so not a 5.

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?

States a clear verb (render/export) and resource (stored result) plus output formats (CSV, JSONL). It does not explicitly name a sibling to distinguish from, but 'for reports or other tools' frames the use case well enough for an agent to identify it as the reporting/serialization path.

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 description advises when resumption is needed (next_offset for row-capped results, next_byte_offset for stored text files), which implies usage guidance. However it never states when to pick this tool over siblings like chainsaw_result_page or chainsaw_result_chunk, leaving the selection decision to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.