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 qlty-checkgit 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/qlty-check)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/qlty-check"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/qlty-check/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/qlty-check"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/qlty-check.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 | $0.00017 | $0.00675 |
| Opus 5 | $0.00009 | $0.00338 |
| Sonnet 5 | $0.00003 | $0.00135 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
qlty-check 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qlty Code Quality
Universal code quality tool supporting 70+ linters for 40+ languages via qlty CLI.
When to Use
- Check code for linting issues before commit/handoff
- Auto-fix formatting and style issues
- Calculate code metrics (complexity, duplication)
- Find code smells
Quick Reference
# Check changed files with auto-fix
uv run python -m runtime.harness scripts/qlty_check.py --fix
# Check all files
uv run python -m runtime.harness scripts/qlty_check.py --all
# Format files
uv run python -m runtime.harness scripts/qlty_check.py --fmt
# Get metrics
uv run python -m runtime.harness scripts/qlty_check.py --metrics
# Find code smells
uv run python -m runtime.harness scripts/qlty_check.py --smells
Parameters
| Parameter | Description |
|---|---|
--check |
Run linters (default) |
--fix |
Auto-fix issues |
--all |
Process all files, not just changed |
--fmt |
Format files instead |
--metrics |
Calculate code metrics |
--smells |
Find code smells |
--paths |
Specific files/directories |
--level |
Min issue level: note/low/medium/high |
--cwd |
Working directory |
--init |
Initialize qlty in a repo |
--plugins |
List available plugins |
Common Workflows
After Implementation
# Auto-fix what's possible, see what remains
uv run python -m runtime.harness scripts/qlty_check.py --fix
Quality Report
# Get metrics for changed code
uv run python -m runtime.harness scripts/qlty_check.py --metrics
# Find complexity hotspots
uv run python -m runtime.harness scripts/qlty_check.py --smells
Initialize in New Repo
uv run python -m runtime.harness scripts/qlty_check.py --init --cwd /path/to/repo
Direct CLI (if qlty installed)
# Check changed files
qlty check
# Auto-fix
qlty check --fix
# JSON output
qlty check --json
# Format
qlty fmt
Requirements
- qlty CLI: https://github.com/qltysh/qlty
- MCP server:
servers/qlty/server.pywraps CLI - Config:
.qlty/qlty.tomlin repo (runqlty initfirst)
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 · 104 lines · 17 tokens per session scan A b057e21bf791
qlty-check is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 17 tokens to every session and 675 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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