no-mistakes: Skill for Claude Code

.agents/skills/agent-tuning/SKILL.md

agent-tuning is a skill for Claude Code from kunchenguid/no-mistakes. It costs 27 tokens per session (1,117 once invoked), scanned A, original, MIT.

A skill for configuring which AI model and reasoning effort an agent uses across different command-line and coding-agent systems.

In plain words
What is it for?
It validates agent profiles, maps settings to each supported harness, respects explicit command-line overrides, and passes the resulting configuration through the standard agent-creation path.
Why use it?
It keeps model and effort settings in one place and prevents adapters or individual call sites from applying conflicting options.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: installed under .agents/ (shared by several agents); mentions Codex; mentions OpenCode.

This is kunchenguid/no-mistakes's own configuration. It tells Claude Code how to work on no-mistakes itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything no-mistakes configures →

About the project

no-mistakes is a local Git proxy that validates changes in an isolated worktree before forwarding a push to the real remote and opening a pull request. It is for developers and coding agents that want automated checks, safe fixes, CI repair, and human review before changes are published.

kunchenguid/no-mistakes · 8,945 stars · on GitHub · kunchenguid.github.io

Reuse

Borrowing it

Nothing to install: this file belongs to kunchenguid/no-mistakes. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/kunchenguid/no-mistakes/main/.agents/skills/agent-tuning/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/kunchenguid/no-mistakes

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agent-tuning

README.md
[![agentmods](https://agentmods.dev/badge/skills/kunchenguid/no-mistakes/agent-tuning/github.svg)](https://agentmods.dev/skills/kunchenguid/no-mistakes/agent-tuning)
Your own site
<a href="https://agentmods.dev/skills/kunchenguid/no-mistakes/agent-tuning"><img src="https://agentmods.dev/badge/skills/kunchenguid/no-mistakes/agent-tuning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-tuning

Your own site · 80×15
<a href="https://agentmods.dev/skills/kunchenguid/no-mistakes/agent-tuning"><img src="https://agentmods.dev/badge/skills/kunchenguid/no-mistakes/agent-tuning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,117 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.01117
Opus 5.5 $0.00011 $0.00447
Sonnet 5.5 $0.00005 $0.00223
Haiku 4.5 $0.00003 $0.00112

Measured 7d ago against content hash a24d4d7b0ef8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agent-tuning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/agent-tuning/SKILL.md · 25 lines

How it starts

The opening of the file, as written. The whole thing — 25 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 model/variant, acpx --model for cursor/acp:<target>). OpenCode 2 maps the profile into the session-creation model reference; OpenCode 1 keeps its session-message mapping. 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.
  • Opt-in Pi run pins (axi run / rerun --model, --effort) resolve in config/pi_profile.go, persist immutably in runs.pi_profile, and are applied before agent construction on launch and recovery. Raw selection flags conflict at creation; later raw/role/global model changes cannot replace a run pin. Unpinned runs retain the precedence above. Semantics owner: docs/src/content/docs/reference/global-config.md (Per-run Pi profiles); regressions: *_pi_profile* / pi_profile_test.go in config, db, daemon, CLI and e2e.
  • 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.

Per-Run Pi Profile Pin

  • A per-run Pi pin (axi run / rerun --model/--effort) is immutable once the run exists (runs.pi_profile, plus an immutability trigger) and must be fully validated before it supersedes an active validation: startRunWithIntentSourceLocked resolves model/effort against global defaults and agent_args_override.pi, then validates agent eligibility only after the freshly fetched trusted default-branch policy produces the effective repository agent selection (ResolvePiProfile, validatePiProfileAgentsBeforeCancel). Under the default trust policy this lets a trusted project agent: pi replace a global auto or non-Pi scalar/list, while the existing allow_repo_commands opt-in instead delegates repository agent selection to the pushed copy; effective non-Pi fallbacks and review_agents are still refused. The post-merge ValidatePiProfileAgents/ApplyPiProfile pass at worktree setup and ApplyPiProfile in loadRecoveredConfig remain the enforcement after cancellation. User semantics are owned by docs/src/content/docs/reference/global-config.md (Per-run Pi profiles). Regressions: internal/config/pi_profile_test.go, internal/daemon/pi_profile_test.go (TestPiProfileTrustedRepoPiOverrideAcceptsGlobalAuto, TestPiProfileInvalidLaunchDoesNotSupersedeActiveRun, TestPiProfileTrustedRepoAgentOverrideDoesNotSupersedeActiveRun, TestPiProfileRecoveryUsesPersistedPinAndLegacyUsesLiveConfig), internal/db/pi_profile_test.go, internal/cli/pi_profile_test.go, e2e TestLivePiProfileTrustedPiOverridesGlobalAuto, TestLivePiProfileFeatureBranchPiCannotOverrideGlobalAuto, and TestPiRunProfileSurvivesGlobalChangesAcrossEveryDuty.

Read the full file on GitHub · 25 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago Changed · +3 lines a24d4d7b0ef8
  2. 15d ago Changed cbda1a7e50f1
  3. 29d ago Changed · +4 lines · +6 tokens per session eddc9eba33cd
  4. 1mo ago Changed · +1 lines cbd1df7af6ae
  5. 1mo ago Changed · +1 lines f6a24f09e3e6
  6. 1mo ago First seen · 16 lines · 21 tokens per session scan A 33630e1157a9

Subscribe to this mod's changes

agent-tuning is a skill published in the GitHub repository kunchenguid/no-mistakes (8,945 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 1,117 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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