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quilt_edit

Replace a unique text string in a file with new text and record the author attribution, ensuring exact credit when multiple agents share a checkout.

Instructions

Edit a file through Quilt instead of your raw editor. Replaces the unique old_string with new_string and records WHO authored the change at the moment of the edit — so attribution is exact even when several agents share this checkout, with no claims or reconcile guesswork. Pass why (your ticket/task). Prefer this over a plain file edit when coordinating a fleet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whyNoa short why for this edit, e.g. the ticket/task
pathYesfile path (repo-relative or absolute; stored repo-relative)
actorNoactor id to act as. Auto-derived per connection when omitted (from the client name, e.g. cursor-3fa2), so naming is optional for a single agent. Pass an explicit id (your role/task name) when several subagents share one server — they have no ambient identity to tell them apart — or when you want a stable id across runs.
new_stringYesthe replacement text
old_stringYesthe exact text to replace (must be unique in the file)
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the tool replaces a unique old_string, records authorship exactly, and avoids attribution guesswork. It does not mention error handling or side effects but adds behavioral context beyond 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: one paragraph with no redundant words. It front-loads the purpose, explains the key benefit, and gives a usage tip. Every sentence earns its place.

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

Completeness3/5

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

While parameters are well-covered and behavior is described, the description lacks context about the overall workflow (e.g., whether the edit is staged or auto-committed) and does not mention return values. For a file edit tool in a versioned system, more context would be helpful.

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?

The input schema has 100% description coverage. The description adds context for 'why' (ticket/task) and 'actor' (optional but useful for subagents), enhancing meaning beyond the schema definitions.

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?

The description clearly states it edits a file by replacing an old string with a new one, and records authorship. It distinguishes from a raw editor but not explicitly from sibling tool 'quilt_write'. The verb 'edit' and resource 'file through Quilt' are specific.

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 advises to pass 'why' and prefer this over plain file edit when coordinating a fleet. It gives a clear usage context but does not explicitly mention when not to use or compare to alternatives like 'quilt_write'.

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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