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All ideas/devtools/A SaaS platform that unifies integration, execution, and result parsing of various AI agentic providers for software development, featuring a normalized interface and cost reporting.
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A SaaS platform that unifies integration, execution, and result parsing of various AI agentic providers for software development, featuring a normalized interface and cost reporting.

Scouted 2 hours ago

7.0/ 10
Overall score

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Score breakdown

Urgency7.0
Market size7.0
Feasibility8.0
Competition6.0
The pain

Lack of standardized integration and result handling for multiple agentic providers in AI-assisted development platforms.

Who'd pay

Software development teams, companies leveraging AI for code automation, and AI-assisted development platforms.

Signal that triggered it

"Add OpenCode as a first-class agentic backend in `pdd/agentic_common.py` and `pdd/prompts/agentic_common_python.prompt`."

Original post

Add OpenCode agentic provider execution and result parsing

Published: 2 hours ago

Repository: promptdriven/pdd Author: prompt-driven-github[bot] PDD Command Hint: change+sync Add OpenCode as a first-class agentic backend in `pdd/agentic_common.py` and `pdd/prompts/agentic_common_python.prompt`. Scope: - Accept `PDD_AGENTIC_PROVIDER=opencode` in the existing agentic provider selection path. - Invoke OpenCode non-interactively with `opencode run --dir <cwd> --format json --dangerously-skip-permissions`. - Pass generated PDD prompts to OpenCode through the same normalized provider interface used by Claude Code, Gemini CLI, and Codex CLI. - Parse OpenCode JSON/JSONL events including `text`, `tool_use`, `step_start`, `step_finish`, and `error` into PDD's existing `(success, output, cost)` result shape. - Sum `step_finish.part.cost` when present. - Add focused tests for OpenCode command construction, provider routing, JSON output parsing, error handling, and cost extraction in the existing agentic-common test area. Acceptance criteria: - `PDD_AGENTIC_PROVIDER=opencode` routes agentic work to OpenCode. - OpenCode JSON events produce normalized output and cost. - Tests cover success, error, and cost-reporting cases.

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