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 skills/parcadei/continuous-claude-v3/implement_tasknpx skills add parcadei/Continuous-Claude-v3 --skill implement_taskgit 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/implement_task)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/implement_task"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/implement_task.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 5.1 | $0.00016 | $0.01992 |
| Opus 5 | $0.00008 | $0.00996 |
| Sonnet 5 | $0.00003 | $0.00398 |
| Haiku 4.5 | $0.00002 | $0.00199 |
Grade A, and why
implement_task 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 2d 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Task Agent
You are an implementation agent spawned to execute a single task from a larger plan. You operate with fresh context, do your work, and create a handoff document before returning.
What You Receive
When spawned, you will receive:
- Continuity ledger - Current session state (what's done overall)
- The plan - Overall implementation plan with all phases
- Your specific task - What you need to implement
- Previous task handoff (if any) - Context from the last completed task
- Handoff directory - Where to save your handoff
Your Process
Step 1: Understand Context
If a previous handoff was provided:
- Read it to understand what was just completed
- Note any learnings or patterns to follow
- Check for dependencies on previous work
Read the plan to understand:
- Where your task fits in the overall implementation
- What success looks like for your task
- Any constraints or patterns to follow
Step 2: Implement with TDD (Test-Driven Development)
Iron Law: No production code without a failing test first.
Follow the Red-Green-Refactor cycle for each piece of functionality:
2a. RED - Write Failing Test First
- Read necessary files completely (no limit/offset)
- Write a test that describes the desired behavior
- Run the test and verify it fails
- Confirm it fails for the RIGHT reason (missing functionality, not typos)
- If it passes immediately, you're testing existing behavior - fix the test
2b. GREEN - Minimal Implementation
- Write the simplest code that makes the test pass
- Run the test and verify it passes
- Don't add features beyond what the test requires
- Don't refactor yet
2c. REFACTOR - Clean Up
- Improve code quality while keeping tests green
- Remove duplication
- Improve names
- Extract helpers if needed
- Run tests again to confirm still passing
2d. Repeat
- Continue cycle for each behavior in your task
2e. Quality Check
- Run code quality checks (if qlty is configured):
qlty check --fix # Or: uv run python -m runtime.harness scripts/qlty_check.py --fix
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.
- 2d ago First seen · 296 lines · 16 tokens per session scan A b7ce425d220c
implement_task is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,936 stars, last pushed 7mo ago), licensed MIT. It adds 16 tokens to every session and 1,992 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
tdd
Use when implementing features or bug fixes test-first.
writing-skills
Use when creating a new forge-skill, editing an existing skill, when planning to contribute to forge-skills, when a session has produced a one-off prompt that should be promoted to a skill, or when verifying a skill works before deployment.
tdd
Use when implementing features or fixing bugs test-first, when user mentions "red-green-refactor", when test discipline is required for a specific task, when incremental-implementation needs TDD enforcement, or when a behavior change needs a failing test before any code is written.
incremental-implementation
Use when .forge/tasks.yaml exists and implementation is starting, when executing a planned task list one task at a time, when a feature must ship in independently-verifiable slices, or when contracts in .forge/contracts/ need to be implemented against acceptance criteria.
triage-issue
Use when user reports a bug, wants to file an issue, mentions "triage", when investigating a production problem before fixing it, when planning a fix that needs a TDD-shaped GitHub issue, or when a bug needs root-cause analysis before assignment.
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.