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 skills add parcadei/Continuous-Claude-v3 --skill tldr-overviewgit 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/skills/parcadei/continuous-claude-v3/tldr-overview)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/tldr-overview"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/tldr-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/tldr-overview"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/tldr-overview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00018 | $0.00482 |
| Opus 5 | $0.00009 | $0.00241 |
| Sonnet 5 | $0.00004 | $0.00096 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
tldr-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 9d 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
TLDR Project Overview
Get a token-efficient overview of any project using the TLDR stack.
Trigger
/overviewor/tldr-overview- "give me an overview of this project"
- "what's in this codebase"
- Starting work on an unfamiliar project
Execution
1. File Tree (Navigation Map)
tldr tree . --ext .py # or .ts, .go, .rs
2. Code Structure (What Exists)
tldr structure src/ --lang python --max 50
Returns: functions, classes, imports per file
3. Call Graph Entry Points (Architecture)
tldr calls src/
Returns: cross-file relationships, main entry points
4. Key Function Complexity (Hot Spots)
For each entry point found:
tldr cfg src/main.py main # Get complexity
Output Format
## Project Overview: {project_name}
### Structure
{tree output - files and directories}
### Key Components
{structure output - functions, classes per file}
### Architecture (Call Graph)
{calls output - how components connect}
### Complexity Hot Spots
{cfg output - functions with high cyclomatic complexity}
---
Token cost: ~{N} tokens (vs ~{M} raw = {savings}% savings)
When NOT to Use
- Already familiar with the project
- Working on a specific file (use targeted tldr commands instead)
- Test files (need full context)
Programmatic Usage
from tldr.api import get_file_tree, get_code_structure, build_project_call_graph
# 1. Tree
tree = get_file_tree("src/", extensions={".py"})
# 2. Structure
structure = get_code_structure("src/", language="python", max_results=50)
# 3. Call graph
calls = build_project_call_graph("src/", language="python")
# 4. Complexity for hot functions
for edge in calls.edges[:10]:
cfg = get_cfg_context("src/" + edge[0], edge[1])
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.
- 9d ago First seen · 85 lines · 18 tokens per session scan A f3f07ad21a35
tldr-overview is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 18 tokens to every session and 482 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.
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Unified settings hub for headsup (Claude Code's iTerm2 status hooks). One command with a section as the first word, then that section's args. Sections: newtabs (New Claude Tab / Cmd-Opt-C launch mode), colors (idle/processing/waiting tab colors), label (this tab's title + badge), notify (the 'Claude is waiting' macOS…
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headsup-colors
Customize headsup's global iTerm2 tab colors for Codex sessions: idle, working, and waiting. Use when the user asks to change Codex/headsup tab colors.
headsup-notifications
Manage macOS notifications for Codex tabs that have been waiting longer than a configured threshold.
fizzy-workflow
Use for guided Fizzy.do workflows: "set up Fizzy", "configure Fizzy for this project", "sync my work to Fizzy", "review my Fizzy progress", "end of session cleanup". Provides step-by-step guidance for common operations.