Skip to main content
Glama
everlastingQAQ

chatgpt-local-coding-agent

workspace_apply_back

Destructive

Apply reviewed code changes from a diff to the original repository after confirmation.

Instructions

After diff review and local confirmation, conflict-check and apply only reviewed paths to the original repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
purposeYes
review_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations declare destructiveHint=true, and the description aligns by stating 'apply ... to the original repository,' implying modifications. The description adds the 'conflict-check' step, which is useful behavioral context. However, it doesn't detail what happens on conflict or whether the operation is reversible. With destructiveHint already set, the description adds some value but not extensive detail.

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 a single sentence, concise and front-loaded with the action. It provides the key context in a short string, which is efficient and to the point.

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?

The tool has an output schema (though not provided in detail), and the annotations include destructiveHint. The description covers the main purpose and usage step. Given the simple parameters and clear purpose, it is mostly complete. However, it could benefit from explaining the output or side effects more, but with output schema present, that burden is reduced.

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

Parameters3/5

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

Schema description coverage is 0%, meaning the description must compensate. The description names 'review_id' and 'purpose' indirectly? Actually, it mentions 'reviewed paths' and 'diff review' but does not explicitly map to 'review_id' or 'purpose'. It doesn't explain how 'purpose' is used or what values it takes. Since there are only 2 params, a good description could easily explain them, but this one does not. Baseline is low because coverage is 0%, and the description adds minimal param semantics.

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 the action ('apply back') and the resource ('reviewed paths to the original repository'). It specifies the operation is about applying previously reviewed changes after diff review and local confirmation, which distinguishes it from generic apply tools. However, it doesn't explicitly differentiate from sibling tools like workspace_diff or workspace_status, though the focus on applying back is distinct.

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 provides usage context: 'After diff review and local confirmation, conflict-check and apply only reviewed paths to the original repository.' This indicates when to use the tool (after diff review) and what it does (conflict-check and apply). It doesn't explicitly mention alternatives or when not to use it, but the context is clear enough for an agent.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/everlastingQAQ/chatgpt-local-coding-agent'

If you have feedback or need assistance with the MCP directory API, please join our Discord server