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/fomo-driven-development/strategic-claude-base/researchgit clone --depth 1 https://github.com/Fomo-Driven-Development/strategic-claude-baseWrote 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/fomo-driven-development/strategic-claude-base/research)<a href="https://agentmods.dev/commands/fomo-driven-development/strategic-claude-base/research"><img src="https://agentmods.dev/badge/commands/fomo-driven-development/strategic-claude-base/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 | $0.00011 | $0.02571 |
| Opus 5 | $0.00005 | $0.01286 |
| Sonnet 5 | $0.00002 | $0.00514 |
| Haiku 4.5 | $0.00001 | $0.00257 |
Grade A, and why
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 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.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are tasked with conducting comprehensive research across the codebase to answer user questions by spawning parallel sub-agents and synthesizing their findings.
Topic provided: $1
Flag Parsing
Check if flags are present in the provided arguments:
- If the arguments contain '--with-codex', set CODEX_RESEARCH=true for later use
- If the arguments contain '--greenfield', set GREENFIELD_MODE=true for later use
- Parse the remaining arguments as the research topic (strip flags from topic processing)
- The '--with-codex' flag enables additional research using the codex-researcher agent alongside standard agents
- The '--greenfield' flag skips codebase research agents for greenfield projects (new projects without existing codebase)
Research Process
If no topic was provided or if you need to specify what to research, please tell me: What topic or area would you like me to research?
Steps to follow after receiving the research query:
-
Read any directly mentioned files first:
- If the user mentions specific files (tickets, docs, JSON), read them FULLY first
- IMPORTANT: Use the Read tool WITHOUT limit/offset parameters to read entire files
- CRITICAL: Read these files yourself in the main context before spawning any sub-tasks
- This ensures you have full context before decomposing the research
-
Analyze and decompose the research question:
- Break down the user's query into composable research areas
- Take time to ultrathink about the underlying patterns, connections, and architectural implications the user might be seeking
- Identify specific components, patterns, or concepts to investigate
- Create a research plan using TodoWrite to track all subtasks
- Consider which directories, files, or architectural patterns are relevant
Step 2.5: Architecture Decision Records (ADR) Review
-
Discover and read all relevant ADRs:
- Use Glob to find all ADR files:
.strategic-claude-basic/decisions/ADR_*.md - Read all ADRs with status: accepted, proposed (skip rejected, superseded)
- Extract key decisions, rationale, and consequences that may impact research
- Note any decisions that directly affect the research topic or approach
- Use Glob to find all ADR files:
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 · 220 lines · 11 tokens per session scan A 3ed72accafa8
research is a command published in the GitHub repository Fomo-Driven-Development/strategic-claude-base (2 stars, last pushed 9mo ago), licensed MIT. It adds 11 tokens to every session and 2,571 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.