Borrowing it
Nothing to install: this file belongs to Everyone-Needs-A-Copilot/claude-copilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Everyone-Needs-A-Copilot/claude-copilot/main/.claude/commands/continue.mdgit clone --depth 1 https://github.com/Everyone-Needs-A-Copilot/claude-copilotWrote 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/commands/everyone-needs-a-copilot/claude-copilot/continue)<a href="https://agentmods.dev/commands/everyone-needs-a-copilot/claude-copilot/continue"><img src="https://agentmods.dev/badge/commands/everyone-needs-a-copilot/claude-copilot/continue/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/commands/everyone-needs-a-copilot/claude-copilot/continue"><img src="https://agentmods.dev/badge/commands/everyone-needs-a-copilot/claude-copilot/continue.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.03501 |
| Opus 5.5 | $0.00000 | $0.01400 |
| Sonnet 5.5 | $0.00000 | $0.00700 |
| Haiku 4.5 | $0.00000 | $0.00350 |
Grade A, and why
continue 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 7d 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 — 450 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Continue Previous Work
Resume a conversation by loading context from Memory Copilot and Task Copilot.
Work lifecycle
Read .claude/agents/_shared/work-lifecycle.md once per task and apply its proportional start/resume, during-work, handoff, finish and later-use checkpoints, including direct invocation. Use the existing task and maintained narrative; selective memory pointers must not duplicate them. Preserve exact destructive approval and recovery, original authority and required assets. Substantial QA-required work needs an observable WORK-LIFECYCLE criterion before acceptance freezes; cleanup status and product acceptance remain separate.
Command Argument Handling
This command supports an optional stream name argument for resuming work on specific parallel streams:
Usage:
/continue- Interactive mode (check pause checkpoints, then resume main initiative or select from streams)/continue Stream-B- Resume work on specific stream directly
Step 0: Check for Paused Tasks (Priority Check)
Before generic paused-task discovery, when a Task Copilot task ID is known or selected, ask the journey authority for its exact continuation:
cc journey resume --task <N> --json
# Add --run <run-id> when the response requires disambiguation.
If it returns an active journey, dispatch only its exact next_specialist using
the returned prepared agent_prompt_fragment at byte 0 of the Agent prompt.
Assemble the complete prompt and bind its exact SHA-256 with cc journey bind-prompt before dispatch, exactly as /protocol requires.
Do not rerun flow detection, choose another specialist, reconstruct Knowledge,
or treat a prepared envelope as dispatched. If it returns stored completion
evidence, perform no Agent dispatch. If it reports no journey, continue with the
generic paused-task behavior below. Invalid, ambiguous, drifted, or malformed
journey state fails closed and must not fall through to an optimistic generic
resume. Dispatch receipts mean observed/authorized only, not successful agent
completion.
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.
- 7d ago Changed · -20 lines 8f46333a585b
- 1mo ago First seen · 470 lines · 0 tokens per session scan A 5cec14f382c2
continue is a command published in the GitHub repository Everyone-Needs-A-Copilot/claude-copilot (14 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,501 tokens. 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 2026-09-04.
Other commands, from other repositories
instinct-import
Import instincts from external sources.
learn
Extract patterns and learnings from current session.
context-save
Save project context, decisions, and progress for a later session.
export-closedloop-learnings
Exports pending ClosedLoop learnings to global location with deduplication.
recall-save
Generate / overwrite .recall/context.md with Recall's local offline summarizer.
cleanup
Sweep /.claude disk hygiene to stated retentions, clean up stale plans from repos, audit plugin health, and compact agent memory files.