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.
git clone --depth 1 https://github.com/Eivor79/ai-debate-pluginWrote 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/eivor79/ai-debate-plugin/review-status)<a href="https://agentmods.dev/commands/eivor79/ai-debate-plugin/review-status"><img src="https://agentmods.dev/badge/commands/eivor79/ai-debate-plugin/review-status/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/eivor79/ai-debate-plugin/review-status"><img src="https://agentmods.dev/badge/commands/eivor79/ai-debate-plugin/review-status.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 | $0.00021 | $0.00269 |
| Opus 5 | $0.00010 | $0.00134 |
| Sonnet 5 | $0.00004 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
review-status 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 8d 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
Summarize the current ai_debate state for the repository.
Resolve the ai_debate root (directory containing run_auto.ps1; default llm_wiki/ai_debate).
If a topic folder is given ($1), show its detail: status.json fields, the document list, and the latest numbered doc / decision.md.
Otherwise, scan every <topic>/status.json and report a compact table:
- topic, priority, status, owner, actionable (owner is an automated agent + actionable status + not blocked + not locked),
blocked_reason/next_action. - Group by: needs human (
owner=humanor non-emptyblocked_reason), in flight (owner=claude/codex), idle/decided.
Then tail the last ~15 lines of run_auto.log.jsonl (if present) and summarize recent results (ok / timeout / nonzero / no_progress / doc_without_state / human_handoff / turn_error) with topic and duration.
Highlight anything that needs the user's attention first (human-pending or blocked topics).
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.
- 8d ago First seen · 19 lines · 21 tokens per session scan A b2d4f735d39b
review-status is a command published in the GitHub repository Eivor79/ai-debate-plugin (1 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 269 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 2026-08-31.
Other commands, from other repositories
octo-schedule
Manage scheduled workflow jobs for the Claude Octopus scheduler.
octo-scheduler
Manage the Claude Octopus scheduled workflow runner daemon.
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
specmanager-build
Build one phase of a SpecManager feature's plan via the builder subagent. Stops at the phase boundary; never advances.
linear-bulk
Apply the same change to many Linear issues at once. Dry-run by default.
standup
Show a daily standup summary with completed, in-progress, and blocked tasks across all active epics.