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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3npx agentmods add skills/parcadei/continuous-claude-v3/system_overviewWrote 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/skills/parcadei/continuous-claude-v3/system_overview)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/system_overview"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/system_overview/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/skills/parcadei/continuous-claude-v3/system_overview"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/system_overview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.00669 |
| Opus 5 | $0.00011 | $0.00334 |
| Sonnet 5 | $0.00004 | $0.00134 |
| Haiku 4.5 | $0.00002 | $0.00067 |
Grade A, and why
system-overview 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 8d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Overview
Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination.
When to Use
- User asks "how does this work?"
- User asks "what can you remember?"
- User asks "what's different about this setup?"
- User runs
/system_overview
Response
CONTINUOUS CLAUDE SYSTEM OVERVIEW
=================================
MEMORY LAYER (PostgreSQL + pgvector)
------------------------------------
- 78,000+ temporal facts from past sessions
- Learnings extracted automatically at session end
- Semantic search with embeddings
RECALL: uv run python opc/scripts/recall_temporal_facts.py --query "your topic"
HOOKS (9 event types registered)
--------------------------------
SessionStart → Load continuity ledger, rebuild symbol index
UserPromptSubmit → Skill activation check, context injection
PreToolUse → Smart search routing (Grep → TLDR for code)
PostToolUse → File claims, compiler feedback
PreCompact → Save state before context compaction
Stop → Extract learnings, create handoffs
SubagentStart → Register spawned agents
SubagentStop → Coordination, handoff creation
SessionEnd → Cleanup
CONTINUITY SYSTEM
-----------------
Ledger: thoughts/ledgers/CONTINUITY_CLAUDE-{session}.md
Handoffs: thoughts/shared/handoffs/{session}/*.yaml
Commands:
/resume_handoff <path> - Continue from handoff
/create_handoff - Create snapshot for transfer
TLDR CODE INTELLIGENCE
----------------------
5-layer analysis: AST → Call Graph → CFG → DFG → PDG
95% token savings vs reading raw files
Auto-intercepts Grep for .py/.ts/.go/.rs files
Pre-built index: /tmp/claude-symbol-index/symbols.json
SETUP
-----
Run: uv run python opc/scripts/setup/wizard.py
Options:
[1] SQLite only (simple, offline)
[2] PostgreSQL + pgvector (semantic search)
Key Files
| Component | Location |
|---|---|
| Hook registration | .claude/settings.json |
| Hook implementations | .claude/hooks/src/*.ts |
| Rules (auto-injected) | .claude/rules/*.md |
| Skills | .claude/skills/*/SKILL.md |
| Setup wizard | opc/scripts/setup/wizard.py |
| Recall script | opc/scripts/recall_temporal_facts.py |
| Store learning | opc/scripts/core/store_learning.py |
| Symbol index builder | opc/scripts/build_symbol_index.py |
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.
- 8d ago First seen · 90 lines · 22 tokens per session scan A 4730ef5fa28e
system-overview is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 22 tokens to every session and 669 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 2026-09-03.
Other skills, from other repositories
sfl
Save For Later: checkpoint this window so a fresh session (or /nil) can resume it later. Use when the user types /sfl, "save for later", or "checkpoint this window". Writes a live per-window entry under /.claude/sfl/ (plus an optional durable note in the user's own memory system), then shows the green Saved-for-Later…
synthesize
Deep cross-domain synthesis engine for the vault. Triggers on "synthesize X", "what do I know about X", "connect ideas about X", "cross-domain analysis of X", "map everything in the vault about X". Searches comprehensively, surfaces non-obvious patterns and tensions, then challenges the user to generate original…
init
Initialize an Obsidian vault with the agent-ready Zettelkasten system — creates directory structure, templates, CLAUDE.md, MCP config, and hooks.
kb-lint
Use to health-check an llmkb knowledge base — run llmkb lint and fix what it reports, then do the judgment-level checks code cannot: contradictions between pages, stale claims superseded by newer sources, and missing concept pages.
kb-init
Use to create a new llmkb knowledge base for a project — scaffold it with llmkb init, then interview the user briefly to tailor SCHEMA.md to the project's domain and conventions.
vault-graph
Use when analyzing vault structure, finding orphan notes, discovering missing connections, identifying bridge concepts, or checking vault health from a graph perspective. Triggers on "vault graph", "map vault", "find orphans", "missing links", "vault structure", "knowledge graph".