Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add punt-labs/prfaq/plugin install prfaq-devWrote 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/punt-labs/prfaq/meeting)<a href="https://agentmods.dev/commands/punt-labs/prfaq/meeting"><img src="https://agentmods.dev/badge/commands/punt-labs/prfaq/meeting.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.01605 |
| Opus 5 | $0.00006 | $0.00803 |
| Sonnet 5 | $0.00002 | $0.00321 |
| Haiku 4.5 | $0.00001 | $0.00161 |
Grade A, and why
meeting 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 6d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR/FAQ Review Meeting
Run an interactive review meeting where four personas — a principal engineer, a target customer, a skeptical executive, and a builder-visionary — debate the weak spots in your PR/FAQ document. You are the PM and final decision-maker.
Steps
-
Find the document. If
$ARGUMENTSspecifies a path, use it. Otherwise, search forprfaq.texin the project root using Glob. If no document exists, tell the user to run/prfaqfirst — the meeting validates an existing document, it doesn't generate one. -
Read the meeting guide. Load
${CLAUDE_PLUGIN_ROOT}/skills/prfaq/references/meeting-guide.mdfor the full meeting flow, synthesis guidelines, and persona details. Also load${CLAUDE_PLUGIN_ROOT}/skills/prfaq/references/plain-style.md— generative prose rules (no em dash, no negative parallelism, no corporate-register vocabulary, no value-claim filler, no explaining the document to the reader). The four persona agents load this guide themselves for their own structured responses, but the debate narrative you synthesize in step 6c is authored directly by you, never written to a file before the user sees it, and never reachesprose_lint.py's hook — this guide is the only check on it. -
Run the pre-meeting scan. Read the full
.texdocument. Extract\prfaqstage{value}to calibrate expectations (see Stage Calibration in the meeting guide). Identify 5-8 hot spots using the four risk-lens questions first (feasibility, value/customer reality, strategic fit/viability, ambition — see Phase 0 in the meeting guide) — documentation issues (unsupported claims, vague language, thin evidence, hedging gaps) are valid but must be at most half the agenda. Rank each as Critical, Warning, or Suggestion — calibrated to the document's stage. -
Get the opening assessment. Launch a single
prfaq:meeting-executive(Alex) agent, standalone, with the document's stage, the Risk Assessment table, and the hot spot titles/severities from step 3. Tell Alex explicitly: this is a meeting-opening assessment, not a section evaluation — reply in 3-5 sentences of continuous prose, not the structured format (see the Exception inmeeting-executive.md). Ask for a 3-5 sentence holistic opening read, organized around Phase 0b's three questions (problem worth solving / strong and differentiated solution / build it now) in the meeting guide. Present it to the user before the agenda. If the agent call fails, times out, or returns ungrounded content, tell the user the opening assessment could not be generated and proceed to the agenda without one.
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.
- 6d ago First seen · 47 lines · 12 tokens per session scan A 077a11243bfc
meeting is a command published in the GitHub repository punt-labs/prfaq (25 stars, last pushed 5d ago), licensed MIT. It adds 12 tokens to every session and 1,605 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 2026-08-30.
Other commands, from other repositories
oracle-dev
Generate property-based test harness using Lean 4 model as oracle.
refine-dev
Verify code refines Z specification via abstraction function and commutativity checks.
refine
Verify code refines Z specification via abstraction function and commutativity checks.
contracts-dev
Generate runtime contracts (preconditions, postconditions, invariants) from a Z specification.
prove-dev
Generate Lean 4 proof obligations from a Z specification.
prove
Generate Lean 4 proof obligations from a Z specification.