菜单
On-demand backlog snapshot and lifecycle stage summary. Regenerates BACKLOG.md from GitHub Issues and displays item counts per stage. Use this skill when you need to check backlog status, view stage counts, regenerate BACKLOG.md, or get a lifecycle overview.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | ~aod-status |
| description | On-demand backlog snapshot and lifecycle stage summary. Regenerates BACKLOG.md from GitHub Issues and displays item counts per stage. Use this skill when you need to check backlog status, view stage counts, regenerate BACKLOG.md, or get a lifecycle overview. |
Utility skill for the AOD Lifecycle. Provides an on-demand snapshot of the project backlog by regenerating BACKLOG.md from GitHub Issues and displaying a summary of items per lifecycle stage.
No governance gates — this is a read-only utility command.
Run board reconciliation to fix any label↔board column drift before generating the snapshot:
source .aod/scripts/bash/github-lifecycle.sh && aod_gh_reconcile_board
This compares each open issue's stage:* label to its board column and fixes mismatches. If the board or gh is unavailable, it skips silently.
Run the backlog regeneration script with JSON output mode:
bash .aod/scripts/bash/backlog-regenerate.sh --json
Parse the JSON output to extract:
file: path to regenerated BACKLOG.mdtotal: total number of GitHub Issuesstages: object with counts per stage (discover, define, plan, build, deliver, untracked)If the script fails or gh is unavailable: Display a warning and attempt to read the existing BACKLOG.md file instead. If no BACKLOG.md exists either, report that no backlog data is available.
Present a formatted summary table:
AOD LIFECYCLE STATUS
| Stage | Count |
|----------|-------|
| Discover | {n} |
| Define | {n} |
| Plan | {n} |
| Build | {n} |
| Deliver | {n} |
| Untracked| {n} |
|----------|-------|
| Total | {n} |
BACKLOG.md regenerated at {file_path}.
If the current git branch matches a feature pattern (NNN-*), display the active feature context:
git branch --show-currentspecs/{NNN}-*/ directoryActive Feature: {NNN}-{name}
spec.md: {PM approved / not approved / missing}
plan.md: {dual approved / not approved / missing}
tasks.md: {triple approved / not approved / missing}
If not on a feature branch, skip this section.
gh CLI unavailable: Warn and fall back to reading existing BACKLOG.md (may be stale).aod/scripts/bash/github-lifecycle.sh — reconciliation functions.aod/scripts/bash/backlog-regenerate.sh — regeneration script (JSON mode)docs/product/_backlog/BACKLOG.md — fallback if script failsspecs/{NNN}-*/spec.md, plan.md, tasks.md — active feature contextaod_gh_reconcile_board — fixes label↔board drift before snapshotdocs/product/_backlog/BACKLOG.md — regenerated from GitHub IssuesDomain knowledge for the tachi orchestrator agent: input format detection, DFD classification, trust boundary notation, STRIDE-per-Element dispatch rules, coverage requirements per component type, coverage matrix model, SARIF 2.1.0 generation specification, output schema tables for threats.md, baseline correlation, structural validation checklist, and error handling templates. Loaded on-demand by the orchestrator during specific pipeline phases.
Domain knowledge for quantitative risk scoring — four-dimensional scoring model (CVSS 3.1, exploitability, scalability, reachability), CVSS base vector mappings, composite score formulas, severity band thresholds, and governance field derivation rules. Consumed by the risk-scorer agent during scoring pipeline execution.
Shared reference files consumed by multiple tachi agents. Contains canonical definitions for severity bands, STRIDE+AI categories, and finding format that serve as the single source of truth across the pipeline. Agents Read individual reference files on-demand rather than maintaining inline copies.
Generate standardized checkpoint reports for multi-phase implementation projects. Use this skill when pausing implementation at strategic milestones (phase completion, user story completion, critical features) to create comprehensive progress reports with task breakdowns, metrics, knowledge base entries, and resume instructions.
Guided post-init workshop that helps new AOD Kit adopters establish product vision and design identity. Two-part flow: Part 1 (Vision) asks 5 guided questions to populate product-vision.md; Part 2 (Design) browses archetypes to generate brand files (brand.md, tokens.css, anti-patterns.md). Supports --vision and --design flags for partial execution. Use when a developer invokes /aod.foundation after running make init.
Manage stack packs — activate, remove, list, and scaffold technology-specific conventions for AI coding agents. Use when developers want to select a stack, set up conventions, or manage pack lifecycle.