agent-tuning

SkillAI & models

Use when changing agent model or effort configuration, adapter mappings, or eval candidate profiles.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the agent-tuning skill

What this skill tells your AI

The instructions your AI receives, as published by kunchenguid/no-mistakes in .agents/skills/agent-tuning/SKILL.md and read by ahel’s review.

Unified Agent Tuning (internal/agentcfg)

  • agentcfg is the single owner of the harness-neutral model/effort surface and of the mapping down to each harness's native mechanism (claude/copilot --effort, codex -m + -c model_reasoning_effort, grok --reasoning-effort, pi --thinking, opencode's session-message model/variant, acpx --model for cursor/acp:<target>). Add a harness there, not in an adapter or in eval. rovodev and antigravity are deliberately declared unmappable, so a request for them is a config error rather than a flag that is silently ignored.
  • agent.NewWithOptions is the one funnel: it validates Options.Profile and splices the mapped args after the operator's raw agent_args_override args, so both the pipeline (cfg.AgentProfileFor) and eval replay (Candidate.Profile()) reach every harness by the same path. Never re-derive a model or effort flag at a call site.
  • Precedence is fixed: a raw agent_args_override flag that already pins a knob natively wins and the mapped value is not emitted, which is what keeps every pre-agent_config configuration byte-identical and stops a harness receiving one knob twice. agent_config is global-only for the same reason as agent_args_override.
  • Eval candidates are agent,model=<model>[,effort=<level>] (the previous agent+model spelling is refused with a migration message), effort is part of the persisted candidate identity, and agentNeutralGlobalConfig strips agent, agent_args_override, and agent_config so a replay never inherits the capturing machine's pins.
  • Keep eval replay identity comparison centralized in agentcfg.ServedMatchesRequested; do not compare an adapter's reported model directly at call sites. The user-facing normalization semantics and candidate guidance live in docs/src/content/docs/reference/eval.md.
  • Regressions: internal/agentcfg, internal/agent/profile_test.go, internal/config/config_agent_config_test.go, internal/daemon/pipeline_agent_profile_test.go, TestParseCandidate*, TestReplayPinsCandidateModelAndEffortOnTheHarness, TestCaptureStripsEveryHarnessPinFromThePinnedConfig, TestServedMatchesRequested, TestReplayPiModelIdentityComparison.

Signals

GitHub stars
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Last commit
Sep 2026
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Catalog kind
skill
Gateway key
agent-tuning
Source
github.com/kunchenguid/no-mistakes