A personalised study-plan command for the AB-100 exam. It uses your confidence in Plan, Design, and Deploy, and can also consider an exam date and weekly study time.

Use it to decide what to study first, get Microsoft Learn module links, cover all three exam areas, and check whether a schedule is feasible when dates and hours are provided.

It helps turn uneven knowledge and limited study time into a prioritised plan. Unknown confidence is treated as weak so gaps are not silently skipped.

How timothywarner-org/ab100 configures Claude Code and GitHub Copilot

Reuse

Borrowing it

Nothing to install: this file belongs to timothywarner-org/ab100. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/timothywarner-org/ab100/main/.github/prompts/ab100-plan.prompt.md

Clone the repo

git clone --depth 1 https://github.com/timothywarner-org/ab100

Made for: Claude Code, GitHub Copilot.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/timothywarner-org/ab100/ab100-plan/github.svg)](https://agentmods.dev/commands/timothywarner-org/ab100/ab100-plan)

Your own site

<a href="https://agentmods.dev/commands/timothywarner-org/ab100/ab100-plan"><img src="https://agentmods.dev/badge/commands/timothywarner-org/ab100/ab100-plan/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/timothywarner-org/ab100/ab100-plan"><img src="https://agentmods.dev/badge/commands/timothywarner-org/ab100/ab100-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 267 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.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00017	$0.00267
Opus 5.5	$0.00007	$0.00107
Sonnet 5.5	$0.00003	$0.00053
Haiku 4.5	$0.00002	$0.00027

Measured 1mo ago against content hash ede9b28d64c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ab100-plan 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 1mo 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.

.github/prompts/ab100-plan.prompt.md · 31 lines

What it actually says

AB-100 Plan

Generate a personalized AB-100 study plan, prioritized weakest first, with Microsoft Learn module links.

Use the ab100-study-planner skill for workflow, output format, and delivery rules (full plan in a single message).

Inputs

Plan confidence: ${input:plan:Strong | Moderate | Weak | Unknown}
Design confidence: ${input:design:Strong | Moderate | Weak | Unknown}
Deploy confidence: ${input:deploy:Strong | Moderate | Weak | Unknown}
Optional exam date: ${input:examDate:YYYY-MM-DD (blank if none)}
Optional weekly hours: ${input:weeklyHours:e.g., 5}

Reminders

Treat Unknown as Weak. Cover all three domains.
Within equal confidence levels, sort by weight (Deploy 40-45% first).
If exam date and weekly hours are both provided, include a feasibility check.
Surface the AB-100 prerequisite reminder.
Do not invent Learn URLs.

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.

1mo ago First seen · 31 lines · 17 tokens per session scan A ede9b28d64c7

Subscribe to this mod's changes

ab100-plan is a command published in the GitHub repository timothywarner-org/ab100 (40 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 267 once invoked, about $0.0001 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 2026-09-20.

Learning and teaching ab-100 agentic-ai copilot-agents copilot-studio exam-prep github-copilot

ab100-plan next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ab100-plantimothywarner-org/ab100	Command	40	1mo ago	MIT	A	17	Claude Code, GitHub Copilot
ab900-practice-questiontimothywarner-org/ab900	Command	29	10d ago	MIT	A	27	Claude Code, GitHub Copilot
ab900-scenario-walkthroughtimothywarner-org/ab900	Command	29	10d ago	MIT	A	45	Claude Code, GitHub Copilot
ab900-study-plannertimothywarner-org/ab900	Command	29	10d ago	MIT	A	25	Claude Code, GitHub Copilot
default-ai-reviewrjmurillo/ai-agents	Command	49	yesterday	MIT	A	0	GitHub Copilot
spec-trace-requirementsrjmurillo/ai-agents	Command	49	yesterday	MIT	A	0	GitHub Copilot
merge-conflict-analysisrjmurillo/ai-agents	Command	49	yesterday	MIT	A	0	GitHub Copilot

ab100: Command for Claude Code