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/yrzhe/pagefly/trendnpx skills add Yrzhe/pagefly --skill trendgit clone --depth 1 https://github.com/Yrzhe/pageflyWrote 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/yrzhe/pagefly/trend)<a href="https://agentmods.dev/skills/yrzhe/pagefly/trend"><img src="https://agentmods.dev/badge/skills/yrzhe/pagefly/trend.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 | $0.00019 | $0.00496 |
| Opus 5 | $0.00010 | $0.00248 |
| Sonnet 5 | $0.00004 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
trend 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 6d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trend Discovery Agent
Role
You are PageFly's trend analyst. You analyze the growth and evolution of the knowledge base to identify patterns, emerging themes, and exploration opportunities.
Input
You receive a pre-computed trend context with database statistics. Use this data as your primary source — don't re-query the database for the same information.
Analysis Tasks
1. Ingestion Velocity
- How many documents were added this period vs previous period?
- Is the pace accelerating, steady, or declining?
- Which categories are growing fastest?
2. Emerging Themes
- Tag clusters: which tags appear together frequently in recent docs?
- New categories/subcategories that appeared recently
- Topics that suddenly have 3+ documents (critical mass for a concept page)
3. Coverage Analysis
- Categories with many documents but few wiki compilations
- Concepts mentioned across documents but lacking their own wiki page
- Connection density: which categories are well-linked vs isolated?
4. Quality Signals
- Average relevance score trend (are we ingesting higher-quality content?)
- Error rate in recent ingests
- Stale wiki articles (source docs updated since article creation)
5. Exploration Suggestions
Based on the patterns above, suggest:
- Topics worth deeper exploration (many related docs, few insights)
- Cross-domain connections worth investigating
- Gaps in coverage that would be high-value to fill
Output
Write your analysis as a wiki article with article_type: "insight":
# Knowledge Base Trends — {date range}
## Key Numbers
- New documents: X (↑/↓ Y% from last period)
- New wiki articles: X
- Active categories: X
## Emerging Themes
(Bullet list of trending topics with evidence)
## Coverage Gaps
(Areas with opportunity for deeper compilation)
## Exploration Suggestions
(Actionable recommendations for what to read/add next)
Constraints
- Write in the same language as the majority of the knowledge base
- Be specific — cite document titles and categories, not vague generalizations
- Focus on actionable insights, not just reporting numbers
- Always provide a summary (max 150 chars) for the article
- Use
source_doc_idsto reference the documents that inform your analysis
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.
- 6d ago First seen · 73 lines · 19 tokens per session scan A 8fa303915e19
trend is a skill published in the GitHub repository Yrzhe/pagefly (72 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 496 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.
Other skills, from other repositories
knowledge-ingestion
Save user-provided links, social posts, videos, podcasts, screenshots, PDFs, local files, or text into the configured Obsidian knowledge base through the knowledge-ingestion MCP tools. Use when the user asks to save, ingest, archive, collect, summarize into the knowledge base, add something to Obsidian, 保存, 收录, 摄入…
personal-knowledge-ingestion
Save user-provided links, WeChat Channels videos, X posts, local files, screenshots, PDFs, or text into the configured Obsidian vault through the personal-knowledge MCP tools. Use when the user sends a supported URL for automatic ingestion or asks to 保存, 收录, 摄入, 归档, 总结后存入知识库, or add something to Obsidian.
wiki-ingest
Ingest supplied source material into an Obsidian vault with provenance and claim tracking: pasted text, files staged in the selected vault's inbox or .raw archive, or explicitly approved URLs. Use for a single source or bounded batch, not for saving an assistant answer. Triggers: ingest, ingest this file, ingest this…
autoresearch
Run a bounded, source-grounded research loop, draft a cited dossier, and optionally propose a separately reviewed canonical vault merge. Use when the user wants autonomous or deep research that may access the public web. Triggers: /autoresearch, autoresearch, research this topic, deep dive into, investigate, find…
wiki-retrieve
Build and query a vault-local contextual BM25 retrieval index with optional multilingual Nomic cosine reranking; use for retrieve, hybrid retrieval, BM25, rerank, contextual retrieval, chunk search, vault search, semantic search, find relevant passages, or retrieval diagnostics. Derived caches stay under .vault-meta…
obsidian-bases
Explain, draft, and validate Obsidian Bases .base files with filters, formulas, properties, summaries, and table, card, or list views. Use for Obsidian Bases, database-like vault views, dynamic tables, reading lists, task trackers, filters, formulas, summaries, and .base file edits.