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SynAgent MCP - Cross-Agent CLI Bridge

codex_implement

Synthesize complex code, algorithms, refactorings, or boilerplate by requesting OpenAI Codex in read-only sandbox mode from a specification.

Instructions

Request OpenAI Codex to synthesize complex code, algorithms, structural refactorings, or boilerplate in read-only sandbox mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel to use (default: "gpt-6.1-sol", options: "gpt-6.1-sol", "gpt-6.0-sol", "luna", "astra").
context_filesNoPaths to files that provide context, contracts, interfaces, or existing implementations.
specificationYesDetailed specification and functional requirements for the code.
user_confirmedNoMandatory true confirmation if using the top-tier "astra" model.
workspace_pathNoOptional absolute path to workspace root.
reasoning_effortNoReasoning effort depth (default: "xhigh").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose one key behavioral trait: it operates in read-only sandbox mode. However, it omits other important traits such as return format, whether it writes files, or synchronous/asynchronous behavior.

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?

A single, front-loaded sentence with no wasted words. Every part of the sentence contributes to understanding the tool's function.

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?

For a complex code-synthesis tool with no annotations and no output schema, the description is minimal. It conveys the core action and sandbox mode, but lacks details about the return value, execution model, or how context files are used.

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 100%, so the schema already documents all six parameters. The description adds no parameter-specific information, so the baseline of 3 applies.

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 specific verb (synthesize) and resource (complex code, algorithms, structural refactorings, boilerplate), making clear it is a code-generation tool. However, it does not explicitly distinguish itself from siblings like codex_analyze or codex_review_code, so it falls short of a 5.

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 implies usage by listing what can be synthesized, but offers no explicit when-to-use or when-not-to-use guidance relative to the sibling tools. No alternatives are mentioned.

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