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/s977043/plangate/subagent-dispatchnpx skills add s977043/PlanGate --skill subagent-dispatchgit clone --depth 1 https://github.com/s977043/PlanGateWrote 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/s977043/plangate/subagent-dispatch)<a href="https://agentmods.dev/skills/s977043/plangate/subagent-dispatch"><img src="https://agentmods.dev/badge/skills/s977043/plangate/subagent-dispatch.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 | $0.00058 | $0.01674 |
| Opus 5 | $0.00029 | $0.00837 |
| Sonnet 5 | $0.00012 | $0.00335 |
| Haiku 4.5 | $0.00006 | $0.00167 |
Grade A, and why
subagent-dispatch 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 3d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent Dispatch
high-risk/critical モードでタスクをロール別エージェントに分配するスキル。 依存関係グラフを生成し、並列実行可能なタスクを特定する。
目的
マルチエージェント実行を安全に行うために、以下を保証する。
- 各エージェントが適切なロールを担う(
subagent-team-designSkill のロール定義に基づく) - 並列実行による競合(同一ファイルの同時変更)を防ぐ
- 依存関係のある処理が正しい順序で実行される
手順(5 ステップ)
plan.mdの Work Breakdown からタスクを列挙する- 各タスクに
subagent-team-designSkill のロール定義(6 ロール)からロールを割り当てる - タスク間の依存関係を特定し、依存関係グラフを生成する
- 依存がないタスクを「並列実行可能」としてグループ化する
- 各タスクに
context-packagerを適用して Allowed Context を生成する
並列実行判定基準
| 条件 | 判定 |
|---|---|
| Allowed Context(Target Files)が重複しない | 並列可 |
| 共有状態(同一ファイル)を変更する | 逐次 |
| reviewee が実装完了するまで reviewer は待機 | 逐次 |
| 同一 pbi-input.md への仕様参照のみ | 並列可 |
入力
- 実行モード(high-risk / critical)
docs/working/TASK-XXXX/plan.md(Work Breakdown)docs/working/TASK-XXXX/test-cases.md.agents/skills/subagent-team-design/SKILL.md§ステップ 2(6 ロール定義)
出力: Dispatch パッケージ
## Dispatch パッケージ
### Mode: {high-risk | critical}
### フェーズ構成
#### Phase A(並列実行可能)
| エージェント | ロール | 担当タスク | Allowed Context |
|------------|--------|----------|----------------|
| Agent-1 | implementer | {タスク名} | {context-packager 出力へのリンク} |
| Agent-2 | implementer | {タスク名} | {context-packager 出力へのリンク} |
#### Phase B(Phase A 完了後)
| エージェント | ロール | 担当タスク | 入力 |
|------------|--------|----------|-----|
| Agent-3 | reviewer | 全実装のレビュー | Phase A の出力 |
| Agent-4 | security-reviewer | セキュリティレビュー | Phase A の出力 |
### 依存関係グラフ(Mermaid)
\`\`\`mermaid
graph TD
A[planner] --> B[implementer-1]
A --> C[implementer-2]
B --> D[reviewer]
C --> D
D --> E[Completion Gate]
\`\`\`
### 並列実行判定結果
- Agent-1 と Agent-2: Target Files が重複しない → 並列可
- Agent-3 と Agent-4: 同じ実装を入力として受け取る → 並列可
- Agent-1/2 → Agent-3/4: 実装完了後にレビュー開始 → 逐次
想定 phase
- WF-03 Solution Design(マルチエージェント設計時)
- WF-04 Build & Refine(実行前)
カテゴリ
- multi-agent
- orchestration
ファイルベース受け渡し(#581 要素3)
subagent へは会話履歴でなく dispatch/ 配下のファイルで渡す:
- task brief:
dispatch/task-NNN-brief.md(context-packager の Allowed Context) - report:
dispatch/task-NNN-report.md(実行コマンド・テスト結果・変更サマリ・懸念) - review package:
dispatch/task-NNN-review-package.md(reviewer 入力を brief/report/diff/evidence へのリンクで固定) - progress ledger:
dispatch/progress-ledger.md(進捗。compaction・モデル切替後はここから再開)
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.
- 3d ago First seen · 119 lines · 58 tokens per session scan A b53e6afff7e7
subagent-dispatch is a skill published in the GitHub repository s977043/PlanGate (2 stars, last pushed 3d ago), licensed MIT. It adds 58 tokens to every session and 1,674 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
skill-maintenance
Automated skill maintenance tool (v6 — Unified Registry + Snapshots). Full scan: [Orphan] migrate misplaced skills from category dirs OR standalone skills/<name>/ to auto-generated/, [Sync] auto-generated/ vs registry lifecycle diff (new/deleted/revived + description auto-sync via lifecycle field), [Reg]…
watch
File sentinel that monitors the working directory for changes and marker comments, then auto-triggers appropriate skills. Poll-based via git diff against the last scan commit. Writes intake items for batch processing and routes marker actions through /do. Use for automatic reactions to file changes; do NOT use for…
review
5-pass structured code review — correctness, security, performance, readability, consistency.
live-preview
Mid-build visual verification loop. Takes screenshots of components during construction, not just after. Catches visual regressions and invisible features before they compound. Requires Playwright or similar screenshot tool.
marshal
Meta-orchestrator that takes any direction — broad, specific, or vague — and autonomously chains skills and context into actionable work. Gathers context from codebase, docs, and memory. Only asks the user when it genuinely cannot proceed. Single-session orchestrator.
wiki
Markdown-first knowledge base where the LLM acts as librarian. Ingests raw sources, compiles and interlinks topic files, self-maintains an index. No vector DB or embeddings required -- uses LLM-native navigation over structured markdown up to 400K words.