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 skills/lingochunk/mcp/lingochunk-guidednpx skills add lingochunk/mcp --skill lingochunk-guidedgit clone --depth 1 https://github.com/lingochunk/mcpWrote 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/lingochunk/mcp/lingochunk-guided)<a href="https://agentmods.dev/skills/lingochunk/mcp/lingochunk-guided"><img src="https://agentmods.dev/badge/skills/lingochunk/mcp/lingochunk-guided.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 | $0.00096 | $0.01917 |
| Opus 5 | $0.00048 | $0.00958 |
| Sonnet 5 | $0.00019 | $0.00383 |
| Haiku 4.5 | $0.00010 | $0.00192 |
Grade A, and why
lingochunk-guided 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 4d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Guided path writer
A LingoChunk guided path turns one episode into an ordered sequence of study sections, each holding a short lesson focused on one thing (comprehension, grammar, speaking or vocabulary). The app can generate those lessons with its own internal writer; this skill lets you write them instead, part by part, following the SAME brief the internal writer receives. Because you write into the same sections, your parts render identically: the journey strip, the Read stage, remembered progress and the second wave all work the same, and quality is guaranteed to match or beat the internal writer.
Uses the lingochunk MCP tools. If they are not available, tell the user to add
the LingoChunk MCP server (see the plugin README) and stop.
When to use
- "Build a guided path over episode 12 and write the lessons."
- "Fill in the next part of my guided path for this episode."
- "Generate the whole guided course for yesterday's episode, but you write it."
For a single standalone lesson (not a section of a guided path), use
lingochunk-lesson instead. For a conversation about an episode rather than an
artefact, use lingochunk-discuss.
The one thing to understand
The pedagogy arrives at runtime, in the brief. This skill deliberately does
NOT teach how to write a guided part - no arc, no per-focus recipes, no level
rules. All of that is assembled server-side for the specific episode, level and
section, and handed to you inside get_guided_writer_brief. Follow the brief's
instructions over any generic lesson instincts you have. When the brief and your
habits disagree, the brief wins.
The loop
- Plan the path.
plan_guided_path(submission_id)triggers the server-side planner (it segments the episode into sections and picks each section's focus) and polls it to ready. Planning is server-side and cheap; it spends none of your tokens but DOES count against the user's daily guided budget. Calling it when a path already exists is safe.
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.
- 4d ago First seen · 148 lines · 96 tokens per session scan A 2717462d6cc1
lingochunk-guided is a skill published in the GitHub repository lingochunk/mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 1,917 once invoked, about $0.0005 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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