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/shobcoder/shob/research-knowledgenpx skills add shobcoder/shob --skill research-knowledgegit clone --depth 1 https://github.com/shobcoder/shobWhat 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 | $0.00053 | $0.02158 |
| Opus 5 | $0.00026 | $0.01079 |
| Sonnet 5 | $0.00011 | $0.00432 |
| Haiku 4.5 | $0.00005 | $0.00216 |
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 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 — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research — GOD MODE
Trigger
/deep-research <query> or when user says "research this deeply", "go deep on",
"full research report on", "investigate this thoroughly".
Core Philosophy
Raw search results are noise. Verified synthesis is signal. Every claim needs a source. Every conflict needs a resolution. A great deep research report is a structured intelligence brief, not a search summary.
Architecture
Query
└── Phase 1: Decompose → Sub-questions
└── Phase 2: Parallel Search → Raw Sources
└── Phase 3: Crawl & Extract → Claims
└── Phase 4: Cross-Reference → Verify / Conflict
└── Phase 5: Synthesize → Report
└── Phase 6: Quality Gates → Deliver
Phase 1 — Query Decomposition
Break the user's query into 3–7 atomic sub-questions. Each must be:
- Independently searchable
- Non-overlapping with others
- Ordered from foundational to advanced
Example:
Query: "Is Company X profitable?"
Sub-questions:
- What is Company X's current revenue model?
- What are its reported ARR and revenue figures?
- What is its burn rate and cost structure?
- What do investors say about its path to profitability?
- How does it compare to competitors on unit economics?
Phase 2 — Multi-Source Search Strategy
For each sub-question, issue 2–4 targeted searches using varied query angles:
[primary term] [year]
[primary term] site:official OR filetype:pdf
[primary term] analysis OR breakdown OR report
[primary term] vs [competitor]
Source Priority Tiers:
| Tier | Type | Trust Weight |
|---|---|---|
| 1 | Official docs, SEC filings, company blogs, government data, peer-reviewed papers | 1.0 |
| 2 | Major news outlets (Reuters, Bloomberg, FT), industry analysts (Gartner, CB Insights) | 0.85 |
| 3 | Tech blogs, newsletters, podcasts | 0.65 |
| 4 | Forums, Reddit, social media | 0.40 |
Minimum sources per report: 8 unique domains Target for complex topics: 15–25 sources
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 · 305 lines · 53 tokens per session scan A 6043d336dd6e
deep-research is a skill published in the GitHub repository shobcoder/shob (582 stars, last pushed 10d ago), licensed MIT. It adds 53 tokens to every session and 2,158 once invoked, about $0.0003 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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