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ab100: Skill for Claude Code

.github/skills/ab100-study-planner/SKILL.md

ab100-study-planner is a skill for Claude Code, Codex from timothywarner-org/ab100. It costs 66 tokens per session (1,388 once invoked), scanned A, original, MIT.

A study-planning workflow for Microsoft’s AB-100 exam, which tests designing, planning, and deploying AI-powered business solutions.

In plain words
What is it for?
Creating personalized exam schedules with estimated study time, exam-domain priorities, and links to Microsoft Learn material.
Why use it?
It turns a learner’s confidence ratings into a focused plan that spends more time on weaker exam areas.

Skill for Claude CodeCodex

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

This is timothywarner-org/ab100's own configuration. It tells Claude Code and Codex how to work on ab100 itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ab100 configures →

not rated 40repo 1mo ago A scan 66 tokens original MIT
View source ↗ timothywarner-org/ab100 techtrainertim.com
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/skills/ab100-study-planner/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/timothywarner-org/ab100

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.

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README.md
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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.

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Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,388 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.01388
Opus 5.5 $0.00026 $0.00555
Sonnet 5.5 $0.00013 $0.00278
Haiku 4.5 $0.00007 $0.00139

Measured 2mo ago against content hash 7004dc08c820, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ab100-study-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 2mo 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/skills/ab100-study-planner/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: ab100.study_planner.personalized

Description: Generates a personalized AB-100 study plan based on the user's self-assessed confidence across exam domains, prioritizing weak areas with estimated hours and Microsoft Learn module links.

Grounding

Required sources:

  • docs/ab100-exam-objectives.md (canonical AB-100 skills measured, synced verbatim from the Microsoft Learn study guide)
  • Microsoft Learn (access via the Microsoft Learn MCP server using microsoft_docs_search for current Learn module URLs)
  • Use microsoft_docs_fetch to verify Learn module links are current and active

Workflow

  1. Present domains with weights. Show the three AB-100 domains and their exam weight percentages:

    Domain Exam Weight
    Plan AI-powered business solutions 25-30%
    Design AI-powered business solutions 25-30%
    Deploy AI-powered business solutions 40-45%

  2. Offer optional finer-grained confidence ratings. The Deploy domain carries the most weight and has four subdomains. If the user wants a more targeted plan, offer to rate each subdomain separately:

    Plan subdomains:

    • Analyze requirements for AI-powered business solutions
    • Design overall AI strategy for business solutions
    • Evaluate costs and benefits (ROI)

    Design subdomains:

    • Design AI and agents for business solutions
    • Design extensibility of AI solutions
    • Orchestrate configuration for prebuilt agents and apps

    Deploy subdomains:

    • Analyze, monitor, and tune AI-powered business solutions
    • Manage the testing of AI-powered business solutions
    • Design the ALM process for AI-powered business solutions
    • Design responsible AI, security, governance, risk management, and compliance

  3. Ask for confidence ratings. Ask the user to rate their confidence in each area using one of these levels:

    • Strong -- comfortable with most objectives; needs only light review.
    • Moderate -- familiar with the concepts but needs targeted practice.
    • Weak -- limited experience; needs focused study.
    • Unknown -- not sure; treat as weak.

Read the full file on GitHub · 115 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. 2mo ago First seen · 115 lines · 66 tokens per session scan A 7004dc08c820

Subscribe to this mod's changes

ab100-study-planner is a skill published in the GitHub repository timothywarner-org/ab100 (40 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 1,388 once invoked, about $0.0003 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 2026-08-30.

Learning and teachingPlanningab-100agentic-aicopilot-agentscopilot-studioexam-prepgithub-copilot
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