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 skills add ldclabs/anda-bot --skill deep-researchgit clone --depth 1 https://github.com/ldclabs/anda-botWrote 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/ldclabs/anda-bot/deep-research)<a href="https://agentmods.dev/skills/ldclabs/anda-bot/deep-research"><img src="https://agentmods.dev/badge/skills/ldclabs/anda-bot/deep-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ldclabs/anda-bot/deep-research"><img src="https://agentmods.dev/badge/skills/ldclabs/anda-bot/deep-research.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00070 | $0.01654 |
| Opus 5.5 | $0.00028 | $0.00662 |
| Sonnet 5.5 | $0.00014 | $0.00331 |
| Haiku 4.5 | $0.00007 | $0.00165 |
Grade A, and why
deep-research 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 21d 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.
This is a copy
91% identical to deep-research — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Skill
Overview
This skill provides a methodology for web research that gathers information from multiple angles, depths, and sources before you write.
When to Use This Skill
Use it for:
Research Questions
- User asks "what is X", "explain X", "research X", "investigate X"
- User wants to understand a concept, technology, or topic in depth
- The question requires current, comprehensive information from multiple sources
- A single web search would be insufficient to answer properly
Content Generation (Pre-research)
- Creating presentations (PPT/slides)
- Creating frontend designs or UI mockups
- Writing articles, reports, or documentation
- Producing videos or multimedia content
- Any content that requires real-world information, examples, or current data
Core Principle
Ground current, specialized, or contested claims in sources you have actually read, because general knowledge goes stale. A multi-faceted topic needs several searches from different angles, not one.
Research Methodology
Phase 1: Broad Exploration
Start with broad searches to understand the landscape:
- Initial Survey: Search for the main topic to understand the overall context
- Identify Dimensions: From initial results, identify key subtopics, themes, angles, or aspects that need deeper exploration
- Map the Territory: Note different perspectives, stakeholders, or viewpoints that exist
Example:
Topic: "AI in healthcare"
Initial searches:
- "AI healthcare applications [current year]"
- "artificial intelligence medical diagnosis"
- "healthcare AI market trends"
Identified dimensions:
- Diagnostic AI (radiology, pathology)
- Treatment recommendation systems
- Administrative automation
- Patient monitoring
- Regulatory landscape
- Ethical considerations
Phase 2: Deep Dive
For each important dimension identified, conduct targeted research:
- Specific Queries: Search with precise keywords for each subtopic
- Multiple Phrasings: Try different keyword combinations and phrasings
- Fetch Full Content: Use available search, browser, or network-capable tools to read important sources in full, not just snippets
- Follow References: When sources mention other important resources, search for those too
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.
- 21d ago Changed · +3 tokens per session 559ecb25de42
- 1mo ago First seen · 191 lines · 67 tokens per session scan A 5c78e15c386a
deep-research is a skill published in the GitHub repository ldclabs/anda-bot (26 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 1,654 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to deep-research, differing in 32 lines, and is treated as a copy.
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