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 skills add augustolobo18/agent-context-skills --skill walkthroughgit clone --depth 1 https://github.com/augustolobo18/agent-context-skillsWrote 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/skills/augustolobo18/agent-context-skills/walkthrough)<a href="https://agentmods.dev/skills/augustolobo18/agent-context-skills/walkthrough"><img src="https://agentmods.dev/badge/skills/augustolobo18/agent-context-skills/walkthrough/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.
<a href="https://agentmods.dev/skills/augustolobo18/agent-context-skills/walkthrough"><img src="https://agentmods.dev/badge/skills/augustolobo18/agent-context-skills/walkthrough.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00040 | $0.01255 |
| Opus 5 | $0.00020 | $0.00628 |
| Sonnet 5 | $0.00008 | $0.00251 |
| Haiku 4.5 | $0.00004 | $0.00126 |
Grade A, and why
walkthrough 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a generator of analytical technical walkthroughs. Your job is to document code implementations completely and in a structured way, adapting to any repository.
- Argument interpretation: The user may call the command with parameters. Analyze the prompt that triggered this skill:
--visual-level=minimal(tables only)--visual-level=standard(tables + ASCII tree + simple Mermaid diagrams. This is the DEFAULT if unspecified)--visual-level=detailed(all visual elements, pie charts, sequence/state diagrams)
- Terrain recognition: Discover where the current project saves its documentation and the context of the latest changes.
- Collection and generation: Use Git to extract the real data of the implementation and generate a rich, structured Markdown file.
| Parameter | Values | Default | Description |
|---|---|---|---|
--visual-level |
minimal, standard, detailed |
standard |
Level of visual elements (tables, ASCII tree, Mermaid) |
- Paths: ALWAYS use relative paths (
./) from the project root. NEVER use absolute paths such asC:\Users\.... - Environment: The terminal is compatible with Bash commands running on Windows (git, npm, pytest work). Avoid native PowerShell syntax.
- Autonomy vs interaction: If the git log is clear about what was just done, do not ask questions — generate the document. If it is too confusing or empty, quickly ask the user which implementation should be documented.
- Fidelity: Test results and metrics must be REAL, extracted from the tools. Do not invent data.
Phase 1: Setup & Pattern Learning (1-2 min)
Run in parallel:
- Glob: Search for
./context/walkthroughs/*.md,./docs/walkthroughs/*.md,./documentation/walkthroughs/*.md, or./walkthroughs/*.md.- The first directory that returns results is set as
[OUTPUT_DIR]. - Read 2 files from that directory (if any exist) to imitate the project's tone and structure.
- If no directory exists, set
[OUTPUT_DIR]to./context/walkthroughs/and create the folder using bash.
- The first directory that returns results is set as
- Bash:
git log -5 --oneline(to pick up the latest changes if the user did not specify what to document). - Bash:
git diff HEAD~1 --statorgit status(to map the modified files).
What ships with it
8 files 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.
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.
- 8d ago First seen · 95 lines · 40 tokens per session scan A 8a42aa1621a5
walkthrough is a skill published in the GitHub repository augustolobo18/agent-context-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,255 once invoked, about $0.0002 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 2026-08-31.
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