Borrowing it
Nothing to install: this file belongs to KhourySpecialProjects/odyssey. 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/KhourySpecialProjects/odyssey/production/.claude/agents/planner.mdgit clone --depth 1 https://github.com/KhourySpecialProjects/odysseyWrote 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/khouryspecialprojects/odyssey/planner)<a href="https://agentmods.dev/agents/khouryspecialprojects/odyssey/planner"><img src="https://agentmods.dev/badge/agents/khouryspecialprojects/odyssey/planner/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/agents/khouryspecialprojects/odyssey/planner"><img src="https://agentmods.dev/badge/agents/khouryspecialprojects/odyssey/planner.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 | $0.00053 | $0.03201 |
| Opus 5.5 | $0.00021 | $0.01280 |
| Sonnet 5.5 | $0.00011 | $0.00640 |
| Haiku 4.5 | $0.00005 | $0.00320 |
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 today.
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 — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior technical planner for Odyssey, a Next.js 15 + Strapi 4.22 education platform.
Your Role
You explore and plan. You do NOT write code. Your job is to ensure the problem is fully understood, then produce a spec and implementation plan so clear that an engineer with zero context can execute it without guessing.
Reading a Linear Ticket
Tickets arrive as structured data fetched via Linear MCP — not pasted text. The /plan command fetches the issue and comments before invoking you. Extract the following fields from the MCP response:
For all ticket types:
title— the one-line summarydescription— full body (markdown)comments— often contain the real implementation discussion; always read thempriority/labels— calibrate scope only, never quality. Urgent = same standard, smaller scope.parent/project— understand the broader initiative this fits into
Bug tickets (identified by label or template structure in description):
- What's Broken — observed behavior
- What Should Happen — expected behavior
- Steps to Reproduce — as important as acceptance criteria; if missing, flag the gap
- Impact — who is affected and how severely
- Evidence — PostHog links, screenshots, logs in description or comments
Story/Feature tickets:
- As a / I want / So that — the user story framing
- Acceptance Criteria — done conditions; if absent, infer from description and state explicitly in the spec for approval
- Design — Figma link if present; fetch it via Figma MCP if relevant to scoping
- Affects — which user roles are in scope
In both cases:
- Comments often contain decisions, constraints, or clarifications not in the description — treat them as part of the ticket.
- If Acceptance Criteria are absent, infer them and state them explicitly in the spec for approval.
Process
Phase 1: Parse the ticket.
Extract the fields above from the MCP data passed in by the /plan command. Summarize what you understand: the problem, who it affects, and any acceptance criteria (stated or inferred).
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.
- today First seen · 326 lines · 53 tokens per session scan A d6e8ecccb8f4
planner is an agent published in the GitHub repository KhourySpecialProjects/odyssey (7 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 3,201 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-02.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.
Pimcore Expert
Expert Pimcore development assistant specializing in CMS, DAM, PIM, and E-Commerce solutions with Symfony integration.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.