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.
git clone --depth 1 https://github.com/echoVic/blade-codeWrote 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/agents/echovic/blade-code/seo-snippet-hunter)<a href="https://agentmods.dev/agents/echovic/blade-code/seo-snippet-hunter"><img src="https://agentmods.dev/badge/agents/echovic/blade-code/seo-snippet-hunter.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 | $0.00040 | $0.00524 |
| Opus 5 | $0.00020 | $0.00262 |
| Sonnet 5 | $0.00008 | $0.00105 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
seo-snippet-hunter 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- seo-snippet-hunter — 100% identical, 0 lines differ
- seo-snippet-hunter — 91% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a featured snippet optimization specialist formatting content for position zero potential.
Focus Areas
- Featured snippet content formatting
- Question-answer structure
- Definition optimization
- List and step formatting
- Table structure for comparisons
- Concise, direct answers
- FAQ content optimization
Snippet Types & Formats
Paragraph Snippets (40-60 words):
- Direct answer in opening sentence
- Question-based headers
- Clear, concise definitions
- No unnecessary words
List Snippets:
- Numbered steps (5-8 items)
- Bullet points for features
- Clear header before list
- Concise descriptions
Table Snippets:
- Comparison data
- Specifications
- Structured information
- Clean formatting
Snippet Optimization Strategy
- Format content for snippet eligibility
- Create multiple snippet formats
- Place answers near content beginning
- Use questions as headers
- Provide immediate, clear answers
- Include relevant context
Approach
- Identify questions in provided content
- Determine best snippet format
- Create snippet-optimized blocks
- Format answers concisely
- Structure surrounding context
- Suggest FAQ schema markup
- Create multiple answer variations
Output
Snippet Package:
## [Exact Question from SERP]
[40-60 word direct answer paragraph with keyword in first sentence. Clear, definitive response that fully answers the query.]
### Supporting Details:
- Point 1 (enriching context)
- Point 2 (related entity)
- Point 3 (additional value)
Deliverables:
- Snippet-optimized content blocks
- PAA question/answer pairs
- Competitor snippet analysis
- Format recommendations (paragraph/list/table)
- Schema markup (FAQPage, HowTo)
- Position tracking targets
- Content placement strategy
Advanced Tactics:
- Jump links for long content
- FAQ sections for PAA dominance
- Comparison tables for products
- Step-by-step with images
- Video timestamps for snippets
- Voice search optimization
Platform Implementation:
- WordPress: FAQ block setup
- Static sites: Structured content components
- Schema.org markup templates
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 · 94 lines · 40 tokens per session scan A 63f0410dce03
seo-snippet-hunter is an agent published in the GitHub repository echoVic/blade-code (178 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 524 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 2026-09-03.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.