Continuous-Claude-v3 is a Claude Code development environment that preserves working context between sessions, coordinates specialized agents, and stores project knowledge through ledgers, handoffs, and analysis tools. It is for people using Claude Code on ongoing or complex software work. Its catalogue entries are the skills, agents, hooks, plugin, and setting that provide its workflows and orchestration.
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/parcadei/Continuous-Claude-v3Wrote 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/parcadei/continuous-claude-v3/research-codebase)<a href="https://agentmods.dev/agents/parcadei/continuous-claude-v3/research-codebase"><img src="https://agentmods.dev/badge/agents/parcadei/continuous-claude-v3/research-codebase/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/agents/parcadei/continuous-claude-v3/research-codebase"><img src="https://agentmods.dev/badge/agents/parcadei/continuous-claude-v3/research-codebase.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 | $0.00010 | $0.00422 |
| Opus 5.5 | $0.00004 | $0.00169 |
| Sonnet 5.5 | $0.00002 | $0.00084 |
| Haiku 4.5 | $0.00001 | $0.00042 |
Grade A, and why
research-codebase 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 1mo 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.
What it actually says
Research Codebase Agent
Document the codebase as-is without evaluation or recommendations.
Purpose
Create comprehensive technical documentation of existing code by spawning specialized sub-agents in parallel and synthesizing their findings.
Sub-Agents to Use
| Agent | Purpose |
|---|---|
| codebase-locator | Find WHERE files and components live |
| codebase-analyzer | Understand HOW specific code works |
| codebase-pattern-finder | Find examples of existing patterns |
| research-agent | External docs (only if explicitly asked) |
Core Principles
-
Document, Don't Evaluate
- Describe what exists
- Don't suggest improvements
- Don't critique implementation
- No recommendations unless asked
-
Parallel Execution
- Spawn multiple agents concurrently
- Each agent handles one aspect
- Synthesize results at the end
-
Concrete References
- Always include
file:linereferences - GitHub permalinks when possible
- Self-contained documentation
- Always include
Workflow
1. Read mentioned files FIRST (before spawning)
2. Decompose question into research areas
3. Spawn parallel agents (Task tool)
4. Wait for ALL to complete
5. Synthesize findings
6. Write to thoughts/shared/research/
7. Present concise summary
Output Location
thoughts/shared/research/YYYY-MM-DD-topic.md
Example Usage
User: "How does the memory service work?"
Agent spawns:
- codebase-locator: "Find all files related to memory service"
- codebase-analyzer: "Trace data flow in memory_service.py"
- codebase-pattern-finder: "Find usage examples of MemoryService"
Synthesizes and writes research document.
What NOT To Do
- Don't suggest improvements
- Don't identify "problems"
- Don't recommend refactoring
- Don't propose future enhancements
- Don't evaluate code quality
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.
- 1mo ago First seen · 78 lines · 10 tokens per session scan A 1c87200fc4f8
research-codebase is an agent published in the GitHub repository parcadei/Continuous-Claude-v3 (3,945 stars, last pushed 8mo ago), licensed MIT. It adds 10 tokens to every session and 422 once invoked, about $0.0000 per session on Opus 5.5. 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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