Borrowing it
Nothing to install: this file belongs to TakaGoto/rag-learning-academy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TakaGoto/rag-learning-academy/main/.claude/skills/roadmap/SKILL.mdgit clone --depth 1 https://github.com/TakaGoto/rag-learning-academyWrote 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/takagoto/rag-learning-academy/roadmap)<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/roadmap"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/roadmap.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 5.1 | $0.00011 | $0.02196 |
| Opus 5 | $0.00005 | $0.01098 |
| Sonnet 5 | $0.00002 | $0.00439 |
| Haiku 4.5 | $0.00001 | $0.00220 |
Grade A, and why
roadmap 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Roadmap: Track Your Progress and Plan Ahead
Read the learner's progress data and present a clear picture of where they are, what they have accomplished, and what to do next.
Step 1: Load Progress Data
Read the following files from the progress/ directory:
learner-profile.md— track assignment, start date, backgroundmodule-tracker.md— lesson completion statusquiz-results.md— quiz scores and identified gapschallenges.md— completed challenges and scoresdebug-log.md— debugging sessionspapers-reviewed.md— papers studied
If progress/learner-profile.md does not exist, the learner has not started yet. Suggest running /start to begin their journey.
Step 2: Display Progress Overview
Present a clear summary with module badges and time estimates:
RAG Learning Academy — Your Progress
=====================================
Track: [Beginner/Intermediate/Advanced]
Started: [date] | Days active: [N] | Streak: [N]d
Module Progress:
[===========-------] 58% (21/36 lessons)
Module 1: Foundations [####] Complete ~2h done
Module 2: Document Processing [####] Complete ~3h done
Module 3: Embeddings [##--] 2/4 lessons ~1.5h left
Module 4: Vector Databases [----] Not started ~3h est.
...
Time remaining on your track: ~8.5 hours
Module Completion Badges
When a module is complete, show a badge next to it:
Module 1: Foundations [####] Complete [FOUNDATIONS]
Module 2: Document Processing [####] Complete [DATA WRANGLER]
Module 3: Embeddings [####] Complete [VECTOR NAVIGATOR]
Badge names by module:
| Module | Badge |
|---|---|
| 1 | FOUNDATIONS |
| 2 | DATA WRANGLER |
| 3 | VECTOR NAVIGATOR |
| 4 | DB ARCHITECT |
| 5 | RETRIEVAL ENGINEER |
| 6 | PROMPT CRAFTER |
| 7 | QUALITY GUARDIAN |
| 8 | PATTERN MASTER |
| 9 | PRODUCTION READY |
Time Estimates
Estimate time per module based on lesson count and type (core ~45min, optional ~30min). Show:
- Time spent (completed lessons)
- Time remaining (incomplete lessons in track)
- Total track estimate
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 · 217 lines · 11 tokens per session scan A d0041a6905ff
roadmap is a skill published in the GitHub repository TakaGoto/rag-learning-academy (18 stars, last pushed 5mo ago), licensed MIT. It adds 11 tokens to every session and 2,196 once invoked, about $0.0001 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 2026-08-30.
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