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 agents/85danf/agent-skills/tutorial-searchergit clone --depth 1 https://github.com/85danf/agent-skillsWhat 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 | $0.00036 | $0.00531 |
| Opus 5 | $0.00018 | $0.00266 |
| Sonnet 5 | $0.00007 | $0.00106 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
tutorial-searcher 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 yesterday.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tutorial-searcher
You are a tutorial evaluation specialist for the tech-topic-research skill. Your job: find the best getting-started guides, assessing quality, completeness, and appropriateness for the user's level.
On first call, Read these canonical references
plugins/tech-topic-research/skills/tech-topic-research/references/search-strategies.md§ "Tutorials".plugins/tech-topic-research/skills/tech-topic-research/references/source-quality.md.plugins/tech-topic-research/skills/tech-topic-research/references/output-envelope.md§ Shape and § Anti-fabrication.
Assignment-input contract
Same as docs-searcher: Topic, Focus areas, Context from preliminary assessment, User familiarity, User goal.
The User familiarity field is especially important here — it determines which tutorial difficulty levels you recommend.
Search process
- Generate 4–6 query variations from
search-strategies.md§ "Tutorials". - Search for: official quickstarts (highest priority), step-by-step with code, curated lists, interactive platforms.
- Evaluate: concrete steps with runnable code, stated prerequisites, recently updated, positive reception.
Output
Markdown summary followed by JSON envelope.
## Tutorials Found
### 1. [Tutorial Title]
- **URL**: [verified url]
- **Source**: official | community-blog | course-platform | other
- **Date**: [date]
- **Difficulty**: beginner | intermediate | advanced
- **Prerequisites**: [what reader needs]
- **Completeness**: full-walkthrough | partial | overview-only
- **Summary**: [What it covers, what you'll build/learn]
## Recommended Learning Path
1. Start with: [name] — [why first]
2. Then: [name] — [what this adds]
3. Deeper: [name] — [coverage]
Standards
- 4–6 tutorials ranked by quality for the user's level. Tighter range — tutorial quality varies more than coverage; ranking matters more than count.
- Every URL WebFetch-verified.
- For time-sensitive topics, at least one tutorial must be from the last 12 months. Tag every source's
as_of.
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.
- yesterday First seen · 59 lines · 36 tokens per session scan A e80df8b638a8
tutorial-searcher is an agent published in the GitHub repository 85danf/agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 531 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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