Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Insajin/autopus-adk --skill adaptive-qualitygit clone --depth 1 https://github.com/Insajin/autopus-adkWrote 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.
[](https://agentmods.dev/skills/insajin/autopus-adk/adaptive-quality)<a href="https://agentmods.dev/skills/insajin/autopus-adk/adaptive-quality"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/adaptive-quality/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.
<a href="https://agentmods.dev/skills/insajin/autopus-adk/adaptive-quality"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/adaptive-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.04326 |
| Opus 5 | $0.00008 | $0.02163 |
| Sonnet 5 | $0.00003 | $0.00865 |
| Haiku 4.5 | $0.00002 | $0.00433 |
Grade A, and why
adaptive-quality 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 387 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adaptive Quality Skill
Overview
Adaptive Quality is a sub-extension of Quality Mode. In Balanced mode only, task complexity determines the execution profile used for each task batch call. High-complexity tasks still receive the strongest reasoning path, while routine tasks stay on the standard path. In this workspace, OMP no longer falls back to haiku; OMP maps managed workers to Sol/Terra/Luna, while new projects leave the primary session on the user's model unless supervisor_model_policy: quality is selected; OMP keeps its configured default model.
Relationship to Quality Mode
| Mode | Behavior |
|---|---|
| Ultra | ALL tasks use the premium execution path. Complexity is IGNORED. |
| Balanced | Complexity determines the execution profile. Adaptive Quality applies. |
| Solo | No task batch items. Not applicable. |
Adaptive Quality is not a replacement for Quality Mode — it is a refinement that operates exclusively within Balanced mode.
Provider-specific mode selection
Mixed OMP and OMP projects can select Ultra or Balanced independently while retaining the existing global fallback:
quality:
default: balanced
providers:
claude: ultra
codex: balanced
Resolve the effective mode in this order: explicit per-run global --quality, persisted
quality.providers.<claude|codex>, persisted quality.default, then balanced. The global
per-run flag intentionally overrides both providers without rewriting YAML.
auto quality provider claude ultra --apply
auto quality provider codex balanced --apply
auto quality provider claude inherit --apply
claude-code is accepted as a CLI alias for canonical provider key claude. Provider-specific
--apply refreshes only that configured platform; auto quality <mode> --apply continues to
refresh every configured platform.
Complexity Assessment Criteria
The planner assesses each task before spawning an agent. The assessment considers:
| Factor | Weight |
|---|---|
file_count |
Number of files to be modified |
estimated_lines |
Expected lines of new/changed code |
requirement_count |
Number of distinct requirements |
dependency_count |
Number of packages/modules involved |
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.
- 11d ago First seen · 387 lines · 15 tokens per session scan A d0051b7e4dd6
adaptive-quality is a skill published in the GitHub repository Insajin/autopus-adk (111 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 4,326 once invoked, about $0.0001 per session on Opus 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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