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 agentmods add skills/10cg/aria/skill-snapshotnpx skills add 10CG/Aria --skill skill-snapshotgit clone --depth 1 https://github.com/10CG/AriaWrote 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/10cg/aria/skill-snapshot)<a href="https://agentmods.dev/skills/10cg/aria/skill-snapshot"><img src="https://agentmods.dev/badge/skills/10cg/aria/skill-snapshot.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00061 | $0.11277 |
| Opus 5 | $0.00030 | $0.05639 |
| Sonnet 5 | $0.00012 | $0.02255 |
| Haiku 4.5 | $0.00006 | $0.01128 |
Grade A, and why
state-scanner 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 4d 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 — 1,107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
状态扫描与智能推荐 (State Scanner v2.9)
版本: 2.9.0 | 角色: 十步循环统一入口
快速开始
我应该使用这个 Skill 吗？
使用场景:
- 开始任何开发任务前的状态检查
- 不确定应该使用哪个工作流
- 需要系统推荐最佳执行路径
- 查询多模块项目的整体进度
不使用场景:
- 已知要执行特定 Phase → 直接调用 Phase Skill
- 只想运行特定步骤 → 直接调用步骤 Skill
核心功能
| 功能 | 描述 |
|---|---|
| 状态感知 | 收集 Git 状态、UPM 进度、OpenSpec 状态、审计状态、自定义检查、变更分析 |
| 智能推荐 | 基于状态生成工作流推荐，附带理由说明 |
| 用户确认 | 展示选项，让用户确认或自定义工作流 |
| 工作流启动 | 将确认的工作流传递给 workflow-runner 执行 |
配置 (config-loader)
执行前读取 .aria/config.json，缺失则使用默认值。参见 config-loader。
| 字段 | 默认值 | 说明 |
|---|---|---|
state_scanner.confidence_threshold |
90 |
置信度阈值 (0-100) |
state_scanner.auto_execute_enabled |
false |
高置信度自动执行 |
state_scanner.auto_execute_rules |
["commit_only", "quick_fix", "doc_only"] |
允许自动执行的规则 |
state_scanner.audit_log_path |
".aria/audit.log" |
审计日志路径 |
workflow.auto_proceed |
false |
Phase 间自动推进 |
执行流程
阶段 0: 中断检测 (Pre-flight)
详细逻辑见 interrupt-recovery.md | 状态格式见 workflow-state-schema.md
检查 .aria/workflow-state.json — 不存在或损坏则跳过进入阶段 1 (损坏时备份并警告)。若 status=in_progress|suspended: (1) 验证 git_anchor.branch 匹配当前分支，不匹配仅 Abandon/Inspect; (2) 若 session.last_active_at<5min 且 session_id 不同，警告并发冲突; (3) 展示 [1]Resume [2]Abandon [3]Inspect — Resume→workflow-runner(resume=true)，Abandon→删除状态进入阶段1，Inspect→详情后重选。若 status=failed: 显示失败上下文，提供 [1]Retry [2]Abandon [3]Inspect。
阶段 1: 状态收集
收集内容:
git:
current_branch: 当前分支名
uncommitted_changes: 未提交的变更数
staged_files: 已暂存文件列表
unstaged_files: 未暂存文件列表
recent_commits: 最近 5 条提交
project:
phase_cycle: 从 UPM 读取当前 Phase/Cycle
active_module: 活跃模块 (mobile/backend/shared)
openspec_status: OpenSpec 变更状态
changes:
file_types: 变更文件类型分类 (code/test/docs/config)
change_count: 变更文件数量
complexity: 变更复杂度评估 (Level1/Level2/Level3)
architecture_impact: 是否影响架构文档
test_coverage: 是否有对应测试文件
skill_changes: # v1.7.0 新增: Skill 变更检测
detected: 是否有 SKILL.md 变更
modified_skills: 变更的 Skill 列表
ab_status: # 各 Skill 的 AB 验证状态
verified: 有新鲜 AB 结果的 Skill 列表
needs_benchmark: 缺少 AB 结果的 Skill 列表
audit: # 新增: 审计状态
enabled: true/false # audit.enabled 配置值
mode: adaptive/convergence/challenge/manual # audit.mode 配置值
active_checkpoints: # 启用的检查点列表 (非 "off" 的)
- post_spec
- post_implementation
- pre_merge
last_audit: # 最近一次审计报告 (如有)
checkpoint: post_spec # 检查点名称
timestamp: "2026-03-27T10:00:00Z"
verdict: PASS/PASS_WITH_WARNINGS/FAIL
converged: true/false
custom_checks: # v2.8.0 新增: 项目级自定义检查
configured: true/false # .aria/state-checks.yaml 是否存在
total: 3 # 检查项总数
passed: 2 # 通过数
failed: 1 # 失败数
results: # 各检查结果
- name: "benchmark-summary-freshness"
status: fail # pass/fail/timeout/error
severity: warning # info/warning/error
output: "STALE" # stdout 首行
fix: "python3 scripts/aggregate-results.py" # 修复建议 (如有)
- name: "db-migration-status"
status: pass
severity: info
output: "OK"
requirements: # 新增: 需求状态
configured: 是否配置需求追踪
prd_exists: PRD 文件是否存在
stories:
total: User Story 总数
ready: 就绪待实现
in_progress: 进行中
done: 已完成
coverage:
with_openspec: 有技术方案的 Story 数
without_openspec: 无技术方案的 Story 数
forgejo:
synced: 是否与 Forgejo 同步
drift: 是否有状态偏差
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 1,107 lines · 61 tokens per session scan A 199db958d89d
state-scanner is a skill published in the GitHub repository 10CG/Aria (2 stars, last pushed 5d ago), licensed MIT. It adds 61 tokens to every session and 11,277 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
promote-idea
Converts an album idea from IDEAS.md into an actual album project in one step. Use when the user says "promote [idea title]", "turn idea into album", or "start working on [idea]".
recap-doc
Post-development recap document generator. Use when: AI/Codex has implemented a feature and the user needs a guided walkthrough of what changed and why, with blind-spot detection and anticipated questions. Not for: Q&A follow-up (use /recap-ask), technical share-out for teammates (use /tech-brief), or generic code…
runbook
Generate and update feature release runbooks from existing docs and codebase. Use when: creating operational runbook, release handbook, deployment checklist, pre-release preparation. Not for: incident response (v2), code review (use codex-code-review), architecture design (use architecture).
requirement-forge-refiner
Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming conventions. Produces a formal requirement-standards.md that the requirement-quality atom reads via config resolution…
great_cto
Use when the CTO describes a feature, task, or project goal. Orchestrates the full SDLC pipeline automatically based on project type.
glab
Expert guidance for using the GitLab CLI (glab) to manage GitLab issues, merge requests, CI/CD pipelines, repositories, and other GitLab operations from the command line. Use this skill when the user needs to interact with GitLab resources or perform GitLab workflows.