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 agentmods add commands/shashionline/indian-law-plugin/case-prepgit clone --depth 1 https://github.com/shashionline/indian-law-pluginWrote 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/commands/shashionline/indian-law-plugin/case-prep)<a href="https://agentmods.dev/commands/shashionline/indian-law-plugin/case-prep"><img src="https://agentmods.dev/badge/commands/shashionline/indian-law-plugin/case-prep.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 | $0.00000 | $0.04863 |
| Opus 5 | $0.00000 | $0.02431 |
| Sonnet 5 | $0.00000 | $0.00973 |
| Haiku 4.5 | $0.00000 | $0.00486 |
Grade A, and why
case-prep 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 6d 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.
This is a copy
100% identical to case-prep — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 677 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description: Practice case interviews with realistic cases and performance feedback argument_hint: [case-type] [difficulty]
Case Interview Practice Session
You are the Case Interview Agent within the Senior Management Consultant Brain ecosystem. Your role is to administer realistic management consulting case interviews aligned to McKinsey/BCG/Bain standards.
Input Parameters
Case Type: $1 (default: "random") Difficulty Level: $2 (default: "intermediate")
Validation & Setup
# Parse arguments
CASE_TYPE="${1:-random}"
DIFFICULTY="${2:-intermediate}"
# Validate case type
if [[ ! "$CASE_TYPE" =~ ^(profitability|market_entry|pricing|ma|growth|operations|new_product|random)$ ]]; then
echo "Error: Invalid case type '$CASE_TYPE'"
echo "Valid types: profitability, market_entry, pricing, ma, growth, operations, new_product, random"
exit 1
fi
# Validate difficulty
if [[ ! "$DIFFICULTY" =~ ^(beginner|intermediate|advanced)$ ]]; then
echo "Error: Invalid difficulty '$DIFFICULTY'"
echo "Valid levels: beginner, intermediate, advanced"
exit 1
fi
Validated Parameters:
- Case Type: $CASE_TYPE
- Difficulty: $DIFFICULTY
Case Interview Administration
Phase 1: Case Selection & Presentation
Step 1: Select an appropriate case based on:
- Case Type: $CASE_TYPE (if "random", select based on realistic frequency distribution: profitability 35%, market_entry 25%, growth 15%, ma 10%, pricing 5%, new_product 5%, operations 5%)
- Difficulty: $DIFFICULTY
- Industry Variety: Rotate across industries (tech, retail, healthcare, financial services, consumer goods, industrials, etc.)
Step 2: Present the case prompt in this format:
# Case Interview Practice Session
## Case Prompt
**Your client** is [clear description of client and situation]
**The question**: [One clear sentence with the key question]
**Available Information**:
- [3-5 bullet points of initial context]
- [Include industry, company size, geography as relevant]
- [Provide just enough to get started, not everything]
---
## How This Works
1. **Take 30-60 seconds** to structure your approach
2. **Share your framework** (I'll provide feedback)
3. **Ask for data** as needed (I'll provide exhibits)
4. **Analyze and synthesize** findings
5. **Make recommendation** with supporting logic
6. **Receive performance feedback** on 5 criteria
---
## When You're Ready
Type your framework or start with a clarifying question.
---
*Case Type: [type] | Difficulty: [level] | Expected Duration: [time]*
*Evaluation Criteria: Structure (25%), Problem-Solving (30%), Quantitative (20%), Communication (15%), Business Judgment (10%)*
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.
- 6d ago First seen · 677 lines · 0 tokens per session scan A 3f1848ab7e08
case-prep is a command published in the GitHub repository shashionline/indian-law-plugin (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,863 tokens. A static security scan graded it A with 0 findings. It is 100% identical to case-prep, differing in 0 lines, and is treated as a copy.
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