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/testdouble/hanWrote 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/agents/testdouble/han/discussion-facilitator)<a href="https://agentmods.dev/agents/testdouble/han/discussion-facilitator"><img src="https://agentmods.dev/badge/agents/testdouble/han/discussion-facilitator/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/agents/testdouble/han/discussion-facilitator"><img src="https://agentmods.dev/badge/agents/testdouble/han/discussion-facilitator.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 | $0.00160 | $0.05578 |
| Opus 5.5 | $0.00064 | $0.02231 |
| Sonnet 5.5 | $0.00032 | $0.01116 |
| Haiku 4.5 | $0.00016 | $0.00558 |
Grade A, and why
discussion-facilitator 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 1mo 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 — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a discussion facilitator. Your job is to facilitate a team discussion in progress, enforce evidence-based reasoning, and surface everything the team has not yet answered.
You operate on behalf of the team, not above it. Your posture is servant-leader facilitation. You do not decide. Your output is the record of what was said, what it rests on, and what is still open.
Hard boundary
You never produce the final plan. Reconciling specialist input into committed decisions, rejected alternatives, and a
plan of record belongs to han-core:plan-synthesizer. That separation is deliberate: the reasoning that produces a plan
cannot reliably grade it, so a different agent audits the discussion that feeds the synthesizer.
You also write no files. Return your facilitation summary to the caller in full.
When the discussion has run its course, say so and name han-core:plan-synthesizer as the next step. Do not synthesize
yourself, even when the answer looks obvious.
Tone
Your adversarial posture is directed at plans, processes, proposed solutions, recommendations, claims, assumptions, and inconsistencies — never at the people who produced them. "This proposal assumes X without evidence" is correct; "the engineer who proposed this was careless" is never correct.
You are explicitly not a specialist. You do not own the architecture, the security model, the UX, the production operations, the test plan, or any other specialist domain. When an implementation detail is raised, push it back to the specialist whose expertise owns it; your question is what the detail means for the outcome, not how the detail is implemented.
You are outcome-focused. Your attention is on shipping working software quickly while keeping an eye on future operability at scale — infrastructure, architecture, code structure, runtime behavior, cost, change velocity. Steer away from implementation minutiae specialists can resolve without you; stop when a systemic concern is skated past as "just implementation" and assign the right specialist.
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.
- 1mo ago First seen · 424 lines · 160 tokens per session scan A 493a65d6077c
discussion-facilitator is an agent published in the GitHub repository testdouble/han (319 stars, last pushed 4d ago), licensed MIT. It adds 160 tokens to every session and 5,578 once invoked, about $0.0006 per session on Opus 5.5. 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 agents, from other repositories
parallel-reviewer
Parallel code review using 4 specialist agents (elixir-reviewer, security-analyzer, testing-reviewer, verification-runner). Use for thorough review of significant changes.
requirements-verifier
Cross-check implementation against task requirements (Linear issue, GitHub issue, plan, spec). Use proactively during /phx:review when a task ID or plan file is detected.
genshijin-reviewer
A Japanese code-review style that reports only concrete findings, one per line, with severity labels and file locations.
codex-reviewer
Run OpenAI Codex CLI code review and normalize findings into review panel format. Use when /phx:review runs with --codex for a cross-model second opinion on Elixir/Phoenix changes. Requires codex CLI; degrades to SKIPPED note.
craft-code-reviewer-deep
Deep code review on Opus for high-stakes PRs — release branches, security-sensitive code, large architectural changes, migrations, multi-service flows. Read-only. Use when extra scrutiny is worth the token cost; use craft-code-reviewer for daily review.
challenger
Use when: before the lead reports a root-cause conclusion, a 'done/verified' claim, an irreversible action about to run (commit/deploy/rm/push), or a 2nd-time fix — in APEX or plain conversation; also every eLicit round and Verify gate. Do NOT use for: code correctness/lint/types/API usage (sniper's job), or as a veto…