René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Feature Request: implement planning \u0026 multi step agent functionaliy","articleBody":"Summary\nAdd a planning layer and multi-step agent capability so agents can decompose tasks into ordered subtasks, maintain context across steps, and reliably execute multi-action workflows.\n\nMotivation\nCurrent single-turn agents are limited for complex tasks that require planning, intermediate decisions, or external actions (APIs, I/O). Enabling multi-step agents will:\n- Allow complex workflows (e.g., research → draft → verify → publish).\n- Improve reliability by making execution explicit and recoverable.\n- Make automation and orchestration use-cases practical.\n\nGoals\n- Provide a planner that decomposes high-level goals into discrete steps/actions.\n- Provide a step executor that runs actions sequentially, maintains context, and handles failures/retries.\n- Expose a clear API for building multi-step agents and plugging in tool actions (APIs, shell commands, database ops).\n- Persist context and execution history so agents can resume and audit runs.\n\nNon-goals\n- Building domain-specific planners (we provide general primitives).\n- Replacing orchestration systems (this complements them for agent-level planning).\n\nProposed design (high-level)\n- Planner component\n  - Input: goal + optional constraints\n  - Output: ordered list of steps (each step: description, required tools, expected output)\n  - Options: depth/iterations limits, cost/latency tradeoffs\n\n- Executor component\n  - Runs steps in order, invoking tool adapters\n  - Maintains and updates context/memory between steps\n  - Handles step failures (retry/backoff/skip/rollback) based on policy\n  - Emits structured logs and events\n\n- Tool Adapter layer\n  - Standard interface for external integrations (HTTP, DB, file, shell, LLM calls)\n  - Includes sandboxing/timeouts/rate-limit handling\n\n- Persistence \u0026 Resume\n  - Store plan, step states, intermediate outputs, and metadata\n  - Support resuming from the last successful step\n\n- Observability \u0026 Debugging\n  - Structured execution logs, step-level metrics, and traceability\n  - Optionally export to existing telemetry backends\n\nExample flow\n1. User: “Create a short blog post about X, include links and references.”\n2. Planner: [Research → Outline → Draft → Fact-check → Finalize]\n3. Executor:\n   - Step 1: Research — call search API, store references.\n   - Step 2: Outline — call LLM with references.\n   - Step 3: Draft — generate content from outline.\n   - Step 4: Fact-check — validate claims via APIs.\n   - Step 5: Finalize — produce final post and metadata.\n\nAPI / UX suggestions (pseudo)\n- plan = planner.create_plan(goal=\"Write blog post about X\", constraints={length:300-500})\n- run_id = executor.execute(plan, resume=false, on_step=callback)\n- executor.resume(run_id)\n\nAcceptance criteria (testable)\n- An agent can accept a high-level goal and produce a multi-step plan.\n- Steps are executed in order and intermediate outputs are accessible.\n- Failures are detected and a configurable retry strategy is applied.\n- Execution can be paused and resumed with preserved context.\n- Tool adapters can be added with a documented interface.\n- Logs show step-level inputs/outputs for auditing.\n\nImplementation notes / priorities\n- Phase 1: Minimal planner + sequential executor + in-memory persistence + 2-3 core tool adapters (HTTP, file, LLM).\n- Phase 2: Durable storage, advanced retry/rollback policies, UI for monitoring, plugin system.\n- Keep planner as a replaceable strategy so teams can swap simple heuristics for advanced planners..","author":{"url":"https://github.com/EliteSimSports","@type":"Person","name":"EliteSimSports"},"datePublished":"2025-12-23T21:42:03.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":0},"url":"https://github.com/56/codinit-dev/issues/56"}