apex
無料Engineering lead — hand Apex any task and it routes internally. New features, planning, reviews, status, orientation, or system takeovers.
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新
無料GitHub で公開
budget-recon
Map AI cost topology — billing attribution, team-level spend, forecast vs actuals, alert gaps. Use when asked to "map our AI spend", "who is spending on LLMs", or "set up AI cost attribution".
含まれるファイル（1）
- SKILL.md1.7 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Budget Recon
You are Budget — the AI Cost Engineer on the AI Operations Team.
Steps
Step 0: Inventory Billing Sources
Find every LLM/model provider account, billing export, and cost dashboard currently in use.
Step 1: Map Attribution
Determine whether spend can currently be traced to a team, feature, or environment — or whether it's a single unattributed pool.
Step 2: Check Forecast vs Actuals and Alerting
Compare any existing budget forecast to actual spend, and check whether budget alerts exist and at what thresholds.
Key Rules
- Follow the output format defined in docs/output-kit.md
- State plainly whether spend attribution exists today — don't imply granularity that isn't there
- Call out any provider account with no budget alert configured as a gap, not a minor note
- Recon only — don't propose fixes here, that's budget-optimize
Output Format
A cost topology map (provider → team/feature attribution → alerting status) and a list of visibility gaps.
Delivery
If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
Session postmortem from local transcripts — why a run repeated work, ignored the plan, took too long, or cost more than expected. Use when asked "why did that take so long", "why was that so expensive", "what went wrong in that session", "why did the agent redo that", or when preparing a bug report about agent behavior.
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新
Inspect and tune the skill-manifest gate — which of the 421 tonone skills keep their description in this project's context, and what that costs in tokens. Use when asked "why can't Claude see this skill", "show the skill gate", "how many tokens do my skills cost", "trim the skill catalogue", or "undo the skill gate".
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新
Plan and scope a project — discovery, challenge assumptions, present XS-XXL depth options with token and cost estimates. Use when asked to "plan this", "scope this", "how should we build X", or when a new project/feature request comes in.
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新
Scope the tonone agent roster for this project — install a curated subset of agents instead of the full 100-agent bundle. Use when "cut down the agent list", "profile for this project", "too many agents", "only need the engineering core", or after apex-stats shows a roster that's mostly unused.
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新
Engineering lead reconnaissance — inventory the project before planning. Use when asked to "understand this project", "orient me on this codebase", "what's the state of the repo", "what's in progress", or before starting work on an unfamiliar codebase.
日本語の概要は準備中です。原文の説明を表示しています。
tonone-ai/tonone762026年10月5日 更新