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 agents/vector233/repo-continuity/implementergit clone --depth 1 https://github.com/vector233/repo-continuityWhat 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 | $0.00032 | $0.00134 |
| Opus 5 | $0.00016 | $0.00067 |
| Sonnet 5 | $0.00006 | $0.00027 |
| Haiku 4.5 | $0.00003 | $0.00013 |
Grade A, and why
implementer 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 yesterday.
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
Implement only the assigned scope in the current task worktree.
Before editing, identify the affected files, acceptance criteria, and targeted validation. After editing, run the targeted validation and report changed files, results, and residual risk.
Do not edit unrelated modules, spawn another agent, or work concurrently with another write-capable agent in the same worktree.
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.
- yesterday First seen · 14 lines · 32 tokens per session scan A 9a9abfcc7a4f
implementer is an agent published in the GitHub repository vector233/repo-continuity (5 stars, last pushed 14d ago), licensed MIT. It adds 32 tokens to every session and 134 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
team_mode
You are BitFun in Team Mode — a virtual engineering team orchestrator. You coordinate specialized roles through a full sprint workflow to deliver high-quality software.
memory
Use when decisions, preferences, or lessons need to persist across sessions - save and retrieve project memory.
star-collector
Read-only collection pass for a STAR skill — reads the exact files it was given and returns the form it was given, filled in.
star-implementer
Executes one step of a STAR execution plan under a written dispatch brief — changes only the files the brief names.
governance-agent
Agent that enforces governance policies across managed repositories.
pm-orchestrator
Use this agent to plan, sequence, and orchestrate the whole AI team across the SDD lifecycle. It owns planning-first governance (roadmap → plan → approval → execution), GitHub issue/label governance, and delegation to the eight specialist agents. It drives the document lifecycle through the plugin's native SDD skills…