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Multi-agent orchestration layer for DeepSeek with prompt caching optimization. Provides autonomous execution, team-based parallelization, and interactive chat modes for code generation and analysis tasks.
Critical gaps across naming, descriptions, and schemas. Tool names lack action verbs (omd_autopilot, omd_team, omd_chat are prefixed with 'omd_' rather than verb_noun). Most descriptions are present but generic, they explain WHAT the tool does but lack WHEN to use it or prerequisites. Input schemas exist but are minimal: most parameters lack type constraints, enums, or validation guidance. No output schemas documented. Error handling is absent, no recovery guidance, no categorization of retryable vs fatal errors. The bash, write, edit tools are destructive but lack confirmation patterns or dry-run support. Overall, this reads as a prototype rather than production-grade tooling.
Spawn a sub-agent to handle a focused sub-task. The sub-agent runs to completion and returns its result. Use this for: delegating research, parallel sub-tasks, or offloading well-scoped work. Available agent types: architect, executor, debugger, reviewer, explore.
Execute shell commands in the project directory. Returns stdout, stderr, and exit code.
Edit a file by replacing a specific substring with new content. Useful for targeted modifications.
Search for files matching a glob pattern. Returns list of matching file paths.
Search for text patterns in files. Returns matching lines with file paths and line numbers.
Run a task through the full autonomous pipeline: explore codebase → architect designs plan → executor implements → reviewer adversarially checks. Returns the final result with review verdict. Use this for: implementing features, fixing bugs, refactoring, or any task that needs end-to-end execution.
Tool names lack action verbs. 'omd_autopilot', 'omd_team', 'omd_chat' use a prefix instead of verb_noun pattern (e.g., 'run_autopilot', 'execute_team_task'). LLMs infer intent from names, these names obscure the action.
No output schemas documented. Tools return results but LLMs cannot plan downstream calls without knowing response structure. E.g., omd_autopilot returns 'final result with review verdict' but no schema for what fields are present.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 50 | 2026-07-28+ | v2 |
Single-turn chat with a coding agent. The system automatically routes your question to the right specialist: executor for implementation, debugger for bugs, architect for design, explore for codebase questions, reviewer for code review. Use this for: quick questions, code explanations, finding things in the codebase.
Read the Architecture Decision Record (ADR) log. Shows past design decisions, review verdicts, and their rationales. Use for: understanding why something was built a certain way.
Explore the codebase — search for files, read code, find patterns. Read-only, no files are modified. Use this for: understanding existing code, finding where something is defined, tracing dependencies.
Read the project memory (MEMORY.md). Contains accumulated knowledge about the codebase that persists across sessions — project structure, conventions, key decisions.
List recent OMD sessions with their status and task summaries.
Run a task with a team of N parallel workers. An architect breaks the task into independent sub-tasks, workers execute in parallel, and a reviewer checks the combined result. Use this for: large refactors, multi-file changes, or any task that can be parallelized.
Read the contents of a file. Supports text files and returns content as string.
Write content to a file. Creates the file if it doesn't exist, overwrites if it does.
Destructive tools (bash, write, edit) lack confirmation or dry-run patterns. No error guidance on recovery. Agents can delete files or run arbitrary commands without safeguards.
Parameter descriptions are generic and lack constraints. 'command' in bash has no guidance on what commands are safe, what timeouts apply, or what errors mean. 'pattern' in grep lacks regex syntax hints.
No error handling or recovery guidance. Tools return success/failure but do not tell LLMs what to do next, whether to retry, or what caused the failure.