weekly-fno-trade-planner

weekly-fno-trade-planner is a skill for Claude Code, Codex from ajeeshworkspace/indian-trading-skills. It costs 86 tokens per session (6,356 once invoked), scanned A, original, MIT.

A weekly planning workflow for futures and options trading in Indian markets. Futures and options are contracts whose value depends on an underlying asset, such as a stock index.

In plain words
What is it for?
It helps scan the week’s news, choose a likely market direction, select an options strategy, set entry and exit levels, and manage stop-loss and profit-taking after entry.
Why use it?
It brings news, economic events, sector trends, price signals, and institutional activity into one plan, including rules for managing an open position.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps scan the week’s news, choose a likely market direction, select an options strategy, set entry and exit levels, and manage stop-loss and profit-taking after entry.

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Install with agentmods
npx agentmods add skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner
Install

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.

Any agent
npx skills add ajeeshworkspace/indian-trading-skills --skill weekly-fno-trade-planner
Clone the repo
git clone --depth 1 https://github.com/ajeeshworkspace/indian-trading-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for weekly-fno-trade-planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner/github.svg)](https://agentmods.dev/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner)
Your own site
<a href="https://agentmods.dev/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner"><img src="https://agentmods.dev/badge/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-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.

agentmods 80×15 button for weekly-fno-trade-planner

Your own site · 80×15
<a href="https://agentmods.dev/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner"><img src="https://agentmods.dev/badge/skills/ajeeshworkspace/indian-trading-skills/weekly-fno-trade-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,356 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.06356
Opus 5 $0.00043 $0.03178
Sonnet 5 $0.00017 $0.01271
Haiku 4.5 $0.00009 $0.00636

Measured 13d ago against content hash b65a54b36262, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

weekly-fno-trade-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 13d 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.

skills/weekly-fno-trade-planner/SKILL.md · 694 lines

How it starts

The opening of the file, as written. The whole thing — 694 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Weekly F&O Trade Planner

Overview

A complete weekly trading workflow for Indian F&O markets — from macro thesis to position management. This skill identifies high-conviction directional trades by combining news analysis, sector screening, technical confirmation, and institutional flow data, then manages the position with structured stop-loss and profit-booking rules.

Designed for retail traders with limited capital who prefer option buying over selling. Supports both Groww MCP and Zerodha Kite MCP for live execution.


Phase 1: News & Macro Scan

Goal

Identify the dominant narrative driving markets this week.

Steps

  1. Fetch breaking news and macro events:
WebSearch: "Indian stock market news this week {current_date}"
WebSearch: "global markets impact India {current_week}"
WebSearch: "RBI SEBI announcement {current_month} {current_year}"
WebSearch: "geopolitical risk India market {current_date}"
  1. Categorize the macro environment:
Category Examples Typical F&O Play
Geopolitical crisis War, sanctions, oil shock Index PUTs (Nifty/BankNifty)
Policy event RBI rate decision, budget, SEBI circular Straddle/strangle before event
Earnings season IT/Banking results week Stock options directional
Global risk-off US recession fear, China slowdown, Fed hawkish Index PUTs, IT stock CALLs (INR weak)
Domestic momentum DII buying, reform news, GDP beat Index CALLs, banking CALLs
Sector rotation Defence order, pharma approval, EV policy Sector-specific stock options
Low conviction No clear driver, range-bound Avoid or play iron condor
  1. Rate the macro conviction (1-5):
    • 5: Clear, strong catalyst with defined timeline (e.g., war escalation, surprise rate cut)
    • 4: Strong theme but timing uncertain
    • 3: Moderate — multiple conflicting signals
    • 2: Weak — mostly noise
    • 1: No conviction — skip the week or go very small

Read the full file on GitHub · 694 lines

Changes

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.

  1. 13d ago First seen · 694 lines · 86 tokens per session scan A b65a54b36262

Subscribe to this mod's changes

weekly-fno-trade-planner is a skill published in the GitHub repository ajeeshworkspace/indian-trading-skills (72 stars, last pushed 20d ago), licensed MIT. It adds 86 tokens to every session and 6,356 once invoked, about $0.0004 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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