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 commands/saigonxiii/evc/deep-researchgit clone --depth 1 https://github.com/SaigonXIII/evcWrote 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/commands/saigonxiii/evc/deep-research)<a href="https://agentmods.dev/commands/saigonxiii/evc/deep-research"><img src="https://agentmods.dev/badge/commands/saigonxiii/evc/deep-research.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 | $0.00000 | $0.00660 |
| Opus 5 | $0.00000 | $0.00330 |
| Sonnet 5 | $0.00000 | $0.00132 |
| Haiku 4.5 | $0.00000 | $0.00066 |
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 3d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research
Multi-source research with cited reports. Searches the web, synthesizes findings, delivers structured output.
Trigger
User invokes /deep-research or says "research", "deep dive", "investigate", "competitive analysis", "what's the current state of"
Steps
1. Clarify scope
Ask clarifying questions only if the scope is genuinely ambiguous — otherwise proceed with reasonable defaults. Never block an autonomous or scheduled run on a question the context already answers.
2. Plan sub-questions
Break the topic into the sub-questions that actually decompose it. Example:
- Topic: "Direct and indirect competitors in our category"
- Who are the main players?
- What's their positioning and core value prop?
- How do they price and go to market?
- What audience are they targeting?
- Market size, growth, and notable shifts in the last 12 months?
3. Execute multi-source search
Search each sub-question from more than one angle — rephrase, approach by entity, by category, by time period. Scale source count to the question: a narrow factual check may need three sources; a market landscape may need dozens. Cross-verify every load-bearing claim. Prioritize: official sites, docs, reputable news > blogs > forums.
4. Deep-read key sources
WebFetch the most promising URLs and read full content. Do not rely only on search snippets for anything that matters to the conclusion.
5. Parallel research (for broad topics)
Delegate independent sub-questions to parallel subagents — decide the count and split by what the topic needs. Each agent searches, reads sources, returns findings. Main session synthesizes.
6. Synthesize report
# [Topic]: Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*
## Executive Summary
[3-5 sentences]
## 1. [First Theme]
[Findings with inline citations]
- Key point ([Source Name](url))
## 2. [Second Theme]
...
## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]
## Sources
1. [Title](url) — [one-line summary]
## Methodology
Searched [N] queries. Analyzed [M] 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.
- 3d ago First seen · 84 lines · 0 tokens per session scan A 7bb8017e9dfd
deep-research is a command published in the GitHub repository SaigonXIII/evc (56 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 660 tokens. 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 commands, from other repositories
review-tool
Research a tool or product for skill-gap, architecture, and verb-fit per the Anatomy framework.
setup
First-run setup — replace the fictional company and authors with yours.
review-content
Review content for brand alignment, lead placement, bio consistency, and proof points.
voice-check
Check a draft against the author's voice profile and flag deviations.
content-status
Scan all content directories and report status of drafts, ideas, and published content.
draft-blog
Scaffold a blog post with proper structure, voice, and frontmatter.