Build legality-checked, coherence-gated LLM pipeline harnesses with typed payloads.
npx skills add https://github.com/thistleknot/skills --skill agentic-harness
Please help me install this Agent Skill. Skill: agentic-harness Source: https://github.com/thistleknot/skills/tree/main/agentic-harness Command: npx skills add https://github.com/thistleknot/skills --skill agentic-harness
agentic-harness solves the problem of unstable, illegal, or incoherent outputs produced by autonomous LLM coding pipelines by turning them into a legality-checked, state-tracked, self-repairing workflow.
Tell an AI to use agentic-harness to run a bounded coding pipeline, enforce legality and coherence gates, and only finalize when the expected artifacts reopen and verification passes.
High-intent search queries and answers about installing and using this skill.
To stop autonomous LLM pipelines from producing unstable outputs, use a legality-checked, coherence-gated harness that enforces structured typed payloads and state-tracked transitions at every machine-to-machine boundary to prevent truncation and ambiguity.
Implementing self-repairing logic in an agentic workflow requires a failure-class-aware mechanism that fixes the underlying issue rather than applying a band-aid, validated by a minimal reproduction and a full harness verification run.
A coherence gate in automated LLM pipeline execution is an explicit validation flag that prevents a task from being marked complete until a representative run actually passes, replacing chatty keep-going behavior with validated state transitions.
To route complex decisions across multiple critic agents, run conservative, balanced, and creative critics simultaneously, then aggregate their blocking issues into an ACCEPT, REVISE, or ESCALATE routing decision for the orchestrator.
Yes, you can and should use structured response wire formats for inter-node communication in agentic pipelines to enforce typed payloads at every boundary, which prevents prose-driven truncation and ambiguity between orchestrator and verifier steps.
The best way to verify multi-stage automated coding tasks without manual intervention is to build a state machine over the conversation that uses external tool-validated binary gates and a coherence sentinel to finalize only when verification passes.
lossyrobValidate PAW workflow state and queue the next activity with a TRANSITION RESULT payload.
harkersReview bounded work for correctness and output evidence-linked findings with a disposition.
jame581Provide a centralized typed EventBus for decoupled Godot 4.x node communication.
vh2224Coordinate multi-LLM engineering workflows with durable markdown state.
