dongarandClaude Opus 5 cf85648719
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Add LLM-backed planning agent (A4/A11/A13) — step 5a
- planner.py: LLMPlanningAgent offers exactly two tools, submit_plan
  and ask_human, so gating stays structural at the tool layer; no
  proceed tool exists. System prompt requires explicit, low-inference
  plans because a weaker model executes them (A13)
- Model output is appended to the canonical log as it arrives, before
  being interpreted, so a crash mid-planning leaves a truthful
  transcript
- A bad turn (prose instead of a tool call, malformed arguments, or a
  failed call) retries once, then raises PlanningError; the
  orchestrator gates to AWAIT_INPUT rather than inventing a plan
- Orchestrator: appends every operator message, plan_submitted, and
  gate_opened to the transcript, so re-planning sees rejection
  feedback as conversation rather than out-of-band parameters; pins
  the A11 role mapping at task start
- llm.py: non-JSON or non-object tool arguments now raise LLMError
  instead of escaping as JSONDecodeError — observed from llama3.2,
  which emits truncated argument strings
- Live planning test is opt-in on NISSE_LIVE_PLANNER_MODEL: planning
  escalates unconditionally (A12) and the local model does not hold
  the tool-call contract, so it awaits a frontier route

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-07 14:47:12 +00:00

Nisse

Two self-hosted AI agents sharing a common library, named for the Nordic farm spirit that keeps the place running overnight and expects to be treated well in return.

Package Role
nisse-core/ Shared library both agents sit on (Part A)
nisse-dev/ Dev Agent — plans and implements software projects (Part B)
nisse-ops/ Sysadmin Agent — operates infrastructure (Part C)

One repository, three packages. The library does not exist as code yet: it is extracted from nisse-dev once that agent works (build-order step 10), as a package split within this tree.

Architecture

The system-level specification lives at docs/Architecture-Build-Spec.md. It covers the shared library, both agents, the supporting services, the build order, and the remaining open decisions.

S
Description
LLM Agents for specialized tasks.
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2026-10-07 22:39:30 +00:00
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