oppertunity-party: Skill for Claude Code

.agents/skills/tech-course/SKILL.md

tech-course is a skill for Claude Code from mcwalrus/oppertunity-party. It costs 165 tokens per session (2,210 once invoked), scanned A, original, MIT.

A course builder that creates a complete learning path for a technology, including a landing README, numbered lessons, and a practical cheatsheet. The lessons are ordered so each one builds on earlier ideas.

In plain words
What is it for?
Use it to create a self-contained course with explanations, reasons, concepts, exercises, self-checks, and takeaways for a chosen technology.
Why use it?
It helps working engineers learn from first principles without encountering concepts before they have been explained.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is mcwalrus/oppertunity-party's own configuration. It tells Claude Code how to work on oppertunity-party 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 oppertunity-party configures →

Reuse

Borrowing it

Nothing to install: this file belongs to mcwalrus/oppertunity-party. 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/mcwalrus/oppertunity-party/main/.agents/skills/tech-course/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/mcwalrus/oppertunity-party

Made for: Claude Code.

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 tech-course

README.md
[![agentmods](https://agentmods.dev/badge/skills/mcwalrus/oppertunity-party/tech-course/github.svg)](https://agentmods.dev/skills/mcwalrus/oppertunity-party/tech-course)
Your own site
<a href="https://agentmods.dev/skills/mcwalrus/oppertunity-party/tech-course"><img src="https://agentmods.dev/badge/skills/mcwalrus/oppertunity-party/tech-course/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 tech-course

Your own site · 80×15
<a href="https://agentmods.dev/skills/mcwalrus/oppertunity-party/tech-course"><img src="https://agentmods.dev/badge/skills/mcwalrus/oppertunity-party/tech-course.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 165 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,210 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 $0.00165 $0.02210
Opus 5.5 $0.00066 $0.00884
Sonnet 5.5 $0.00033 $0.00442
Haiku 4.5 $0.00016 $0.00221

Measured 1mo ago against content hash 128518c89ff7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tech-course 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.

.agents/skills/tech-course/SKILL.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tech Course Builder

Produce a complete, ground-up course on a technology for working engineers — mental-model-first, dependency-ordered, and immediately runnable. The course is a multi-file tree: a landing README.md, dependency-ordered units under course/, and a CHEATSHEET.md they keep using after they finish. The single load-bearing property is that each unit depends only on earlier ones and anchors every new concept to something the reader already knows. Success looks like a course a fluent-but-new engineer can follow top to bottom without ever hitting a forward reference, and a cheatsheet that survives as a day-to-day reference.

Values

  • Dependency-correctness over coverage. A unit that forward-references a later concept is a defect. Getting the order right matters more than including every feature.
  • Mental models over feature enumeration. Teach the load-bearing intuitions first; features hang off them.
  • Anchored analogy over abstract explanation. Relate each new idea to a tool the reader already uses, then state explicitly where the analogy breaks down.
  • Opinionated over neutral. State "avoid X", "use Y for new projects" — but only from grounded knowledge. Every recommendation traces to a primary source (see Workflow Step 2), never to memory. A course that refuses to recommend wastes the reader's judgment budget; a course that recommends from a guess misleads it.
  • Minimal runnable snippets over prose. Every snippet does one thing and is copy-pasteable, with expected output shown as a → result comment in the snippet's native comment syntax.

Constraints

  • Never generate full unit content before the user confirms the syllabus — the unit list (titles + one-line practical goal each) and the 3–5 core mental models. This checkpoint is what keeps units dependency-correct; skipping it is the one unrecoverable failure.
  • Resolve the audience background before generating anything. Every analogy and every "this surprises everyone coming from X" aside anchors to it. If it is not stated and not obvious from context, ask.
  • Never propose a syllabus or write content from memory alone. Ground in primary sources first — tech-doc-research for concepts, fresh-data for versions, setup commands, and recommendations — for every course, however well you know the technology. The syllabus and content must derive from that research, not merely follow it. See Workflow Step 2 and references/grounding-workflow.md, which also defines the fallback when sources are thin so the skill never deadlocks on its own precondition.
  • Before writing, check the target. Write directly only if the files you would overwrite are tracked and committed (so git checkout restores them). If the target is not a git working tree, OR the colliding file is untracked or has uncommitted changes, do not overwrite: write into a dedicated ./<technology>-course/ subdirectory, or confirm with the user first.
  • Every unit depends only on earlier units. Foundational units come first and are marked non-skippable.
  • Every unit follows the per-unit template in Output Format exactly — same section order, every time, so readers always know where to look.
  • Do not explain what the audience already knows (terminals, variables). Do explain everything specific to the technology from first principles.

Read the full file on GitHub · 173 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago First seen · 173 lines · 165 tokens per session scan A 128518c89ff7

Subscribe to this mod's changes

tech-course is a skill published in the GitHub repository mcwalrus/oppertunity-party (0 stars, last pushed 2mo ago), licensed MIT. It adds 165 tokens to every session and 2,210 once invoked, about $0.0007 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 2026-08-31.

Related

Other skills, from other repositories

interview-prep

Use when the user wants to prepare for an interview tracked in Job Search HQ. Triggers: /interview-prep, "prep me for the X interview", "interview prep for ", "help me get ready for my final round", or accepting the prompt offered by /update-status when an interview is scheduled. Researches the company live and builds…

Miracle-Aligner/job-search-hq · 109 tokens

hr-onboarding

A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".

nexu-io/open-design · 62 tokens

lean-formalize

Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…

wanshuiyin/Auto-claude-code-research-in-sleep · 81 tokens

eli5

Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.

companion-inc/feynman · 63 tokens

deck-course-module

A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.

nexu-io/html-anything · 25 tokens

explore-unknowns

Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…

dzhng/skills · 162 tokens