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 sergekostenchuk/ui-ux-agent-skill-system --skill task-plan-v2-orchestratorgit clone --depth 1 https://github.com/sergekostenchuk/ui-ux-agent-skill-systemWrote 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/sergekostenchuk/ui-ux-agent-skill-system/task-plan-v2-orchestrator)<a href="https://agentmods.dev/skills/sergekostenchuk/ui-ux-agent-skill-system/task-plan-v2-orchestrator"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/task-plan-v2-orchestrator/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/sergekostenchuk/ui-ux-agent-skill-system/task-plan-v2-orchestrator"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/task-plan-v2-orchestrator.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00119 | $0.01459 |
| Opus 5 | $0.00060 | $0.00730 |
| Sonnet 5 | $0.00024 | $0.00292 |
| Haiku 4.5 | $0.00012 | $0.00146 |
Grade A, and why
task-plan-v2-orchestrator 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 12d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Plan V2 Orchestrator
Use this skill for planning and orchestration artifacts, not for feature implementation itself.
Canonical Model
FEATURE-PREPARATION.mdis the pre-implementation gate.TASK-PLAN.mdis the canonical, editable control document.TASK-DASHBOARD.htmlis derived from Markdown and never the source of truth.
If the user asks for only one file, preserve the same logical separation inside that file.
Workflow
- Classify the request:
- create a new plan
- refactor an existing plan
- audit a plan
- prepare runtime-specific projections
- Read
references/field-layers.md. - If the user mentioned
Codex,Claude Code,Gemini, orAntigravity, also readreferences/runtime-adapters.md. - If the user wants HTML, dashboard, graph, kanban, or observability views, also read
references/dashboard-contract.md. - Start with the pre-implementation layer. If it is incomplete, do not mark implementation tasks as ready.
- Normalize every task into a stable task block with explicit fields instead of freeform prose.
- Model multi-agent execution as sequential by default.
- Add
Execution GovernanceandVerification Policybefore task execution. - Keep missing facts explicit as
TBD,unknown, oropen_question; do not invent them. - Treat critical
TBDfields as blockers forready,in_progress,approved, anddone. - Default to
NO-MOCKSandNO-PLACEHOLDERS. - If a mock or placeholder is temporarily unavoidable, convert it into an explicit alarm with replacement requirements and carry that alarm into every downstream prompt or runtime projection.
Multi-Agent Rules
- A task may have many agents, but only one current
owner_role. agent_sequenceis ordered and sequential unless the user explicitly asks for parallel lanes.agent_contractsmust define:- entry criteria
- expected outputs
- handoff target
- stop conditions
required_approvalsmust name roles or gates, not vague "review".max_review_loopsmust be finite.escalation_rulemust say what happens when review loops are exhausted or a blocker cannot be resolved locally.
What ships with it
8 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.
- agents/openai.yaml 267 B
- assets/CLAUDE-CODE.tasks-projection.md 1.5 KB
- assets/FEATURE-PREPARATION-CHECKLIST.md 2.9 KB
- assets/IMPLEMENTATION-PLAN.runtime.md 1.7 KB
- assets/TASK-PLAN-v2.template.md 11 KB
- references/dashboard-contract.md 3.1 KB
- references/field-layers.md 14 KB
- references/runtime-adapters.md 3.9 KB
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.
- 12d ago First seen · 114 lines · 119 tokens per session scan A 836dd286cb67
task-plan-v2-orchestrator is a skill published in the GitHub repository sergekostenchuk/ui-ux-agent-skill-system (23 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 119 tokens to every session and 1,459 once invoked, about $0.0006 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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