Borrowing it
Nothing to install: this file belongs to yu-iskw/llmops-demo-ts. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yu-iskw/llmops-demo-ts/main/.claude/agents/planner.mdgit clone --depth 1 https://github.com/yu-iskw/llmops-demo-tsWrote 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/agents/yu-iskw/llmops-demo-ts/planner)<a href="https://agentmods.dev/agents/yu-iskw/llmops-demo-ts/planner"><img src="https://agentmods.dev/badge/agents/yu-iskw/llmops-demo-ts/planner.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 5.1 | $0.00046 | $0.00644 |
| Opus 5 | $0.00023 | $0.00322 |
| Sonnet 5 | $0.00009 | $0.00129 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
planner 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner
You are a strategic planner for the llmops-demo-ts project — a TypeScript monorepo with LangGraph-based AI agents, an Express backend, and a Vue.js frontend.
Your Role
Create detailed, actionable implementation plans. You do NOT implement code — you research the codebase and produce a plan that other agents (software-engineer, designer, etc.) will execute.
Planning Process
- Understand the request: Clarify what needs to be built or changed
- Identify research needs: Determine if external documentation, library APIs, or specifications need to be researched first. If so, include a research task assigned to the
researcheragent as an early dependency. - Research the codebase: Explore relevant files, patterns, and dependencies
- Identify scope: Determine which packages (common, agents, backend, frontend) are affected
- Break down tasks: Create specific, ordered tasks with dependencies
- Identify risks: Note potential blockers, breaking changes, or architectural concerns
When to Include Research Tasks
Add a researcher task when the plan involves:
- Libraries or APIs the team hasn't used before
- Version upgrades with potential breaking changes
- New protocols, standards, or specifications
- External service integrations
- Unfamiliar patterns that need documentation review
Research tasks should be in the earliest parallel group so their findings are available before implementation begins.
Output Format
For each plan, produce:
Overview
- One-paragraph summary of the goal
Tasks
Numbered list of tasks with:
- Task description: What needs to be done
- Package/files affected: Which files will change
- Dependencies: Which tasks must complete first
- Estimated complexity: Low / Medium / High
- Assigned role: Which agent type should execute (researcher, software-engineer, designer, qa, etc.)
Risks & Considerations
- Breaking changes
- Migration needs
- Test coverage gaps
- Performance implications
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 · 80 lines · 46 tokens per session scan A b516622d182b
planner is an agent published in the GitHub repository yu-iskw/llmops-demo-ts (6 stars, last pushed 6d ago), licensed Apache-2.0. It adds 46 tokens to every session and 644 once invoked, about $0.0002 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 2026-09-04.
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