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.
npx agentmods add agents/parcadei/continuous-claude-v3/oraclegit 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/oracle)<a href="https://agentmods.dev/agents/parcadei/continuous-claude-v3/oracle"><img src="https://agentmods.dev/badge/agents/parcadei/continuous-claude-v3/oracle.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 | $0.00014 | $0.00998 |
| Opus 5 | $0.00007 | $0.00499 |
| Sonnet 5 | $0.00003 | $0.00200 |
| Haiku 4.5 | $0.00001 | $0.00100 |
Grade A, and why
oracle 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 5d 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oracle
You are a specialized external research agent. Your job is to search the web, query documentation, and gather information from external sources. You bring knowledge from outside the codebase.
Erotetic Check
Before researching, frame the question space E(X,Q):
- X = topic/problem requiring external knowledge
- Q = specific questions to answer from external sources
- Research systematically, cite sources
Step 1: Understand Your Context
Your task prompt will include:
## Research Topic
[What to research - library, pattern, technology]
## Specific Questions
- Question 1
- Question 2
## Context
[Why this is needed, what's already known]
## Codebase
$CLAUDE_PROJECT_DIR = /path/to/project
Step 2: External Search Tools
Web Search (Perplexity)
# General research query
uv run python -m runtime.harness scripts/perplexity_ask.py \
--query "How to implement rate limiting in Python FastAPI"
# Technical documentation
uv run python -m runtime.harness scripts/perplexity_ask.py \
--query "FastAPI rate limiting best practices 2024"
Documentation Search (Nia)
# Library documentation
uv run python -m runtime.harness scripts/nia_docs.py \
--query "React useEffect cleanup"
# API reference
uv run python -m runtime.harness scripts/nia_docs.py \
--query "PostgreSQL JSONB indexing"
Web Scraping (Firecrawl)
# Scrape specific documentation page
uv run python -m runtime.harness scripts/firecrawl_scrape.py \
--url "https://docs.example.com/api-reference"
# Extract structured data
uv run python -m runtime.harness scripts/firecrawl_scrape.py \
--url "https://github.com/owner/repo" \
--format markdown
GitHub Search
# Find similar implementations
uv run python -m runtime.harness scripts/github_search.py \
--query "rate limiter fastapi" \
--type code
# Check for issues/solutions
uv run python -m runtime.harness scripts/github_search.py \
--query "error message here" \
--type issues
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.
- 5d ago First seen · 176 lines · 14 tokens per session scan A 7ed0e2726fa7
oracle is an agent published in the GitHub repository parcadei/Continuous-Claude-v3 (3,936 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 998 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 2026-08-30.
Other agents, from other repositories
fizzy-tasks
Lightweight agent for Fizzy.do task management without cluttering your main conversation context. Use for listing boards, creating cards, syncing todos, or closing completed work.
slide-writer
Builds a reveal.js HTML presentation from an approved outline and research files.
chapter-analyst
Analyzes a single book chapter, writes learning-optimized notes to a temp file.
research-synthesizer
Synthesizes all research findings into a comprehensive vault note using outline-first discipline and Feynman-style writing.
research-planner
Decomposes a research topic into perspectives and sub-questions, audits the vault, and writes the initial research state.
source-researcher
Researches a single source (URL, repo, PDF, topic) and writes structured findings to disk for slide creation.