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/comisai/comis/content-moderationnpx skills add comisai/comis --skill content-moderationgit clone --depth 1 https://github.com/comisai/comisWhat 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 | $0.00056 | $0.00766 |
| Opus 5 | $0.00028 | $0.00383 |
| Sonnet 5 | $0.00011 | $0.00153 |
| Haiku 4.5 | $0.00006 | $0.00077 |
Grade A, and why
mod-sim-console 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a trust & safety reviewer working a simulated moderation queue. You resolve each reported item using the moderation console tools. This skill explains how to use the tools — deciding what actually violates policy is your job.
Your tools (mcp:mod-sim/*)
Observe (read-only — gather evidence):
get_queue— the items awaiting review and how many reports each has. Report count is volume, not a verdict.get_item { id }— the full content and metadata (author, text, context) for one item.get_reports { id }— the individual reports against an item: who filed each, the reason, and the report source.reporter_history { reporter }— a reporter's reliability record (account age, prior reports, confirmed/dismissed rate, links to other accounts).policy_lookup { query }— look up the community-policy rules by key or keyword.similar_items { id }— prior moderated items resembling this one, with how they were resolved.
Act (consequential):
open_review { summary }— start a review; returns areviewid. Do this first.decide { review, id, verdict, rationale }— record a per-item decision:keeporremove. Decide each queue item.escalate { review, id, reason }— hand an item to a senior reviewer if you can't decide.action_account { review, account, action }—warnorsuspendan account. This has real cost if the account is a legitimate user — the tool will warn you.label { review, id, label }— attach a non-removal label to an item for the record.submit_verdict { review, note }— submit the review for grading. This returns the graded result over all your per-item decisions.
How to run a review
open_reviewto get areviewid; pass thatreviewto the actions that follow.get_queue, then for each item pull its content (get_item), its reports (get_reports), and the relevant policy (policy_lookup) before you decide.decideakeep/removeverdict for every item in the queue, with arationale.- Use
reporter_historyandsimilar_itemsto inform your decisions;labelorescalateas appropriate. - Only
action_accountwhen you are confident the account is behind a genuine violation — a wrong action has real cost. submit_verdictonce you've decided every item. This is graded.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 41 lines · 56 tokens per session scan A dfacb2914b27
mod-sim-console is a skill published in the GitHub repository comisai/comis (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 56 tokens to every session and 766 once invoked, about $0.0003 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.
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gitnexus-debugging
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug".
gitnexus-impact-analysis
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