agent-discussion

A terminal display format for showing opinions, findings, and recommendations from several software agents in a structured way.

In plain words
What is it for?
Use it for code reviews, security or accessibility findings, performance discussions, debates, and summaries of where agents agree or disagree.
Why use it?
It makes multi-agent reviews easier to scan by separating contributions, showing severity, and highlighting evidence and agreement.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/jeremydev87/codingbuddy/agent-discussion
Any agent
npx skills add JeremyDev87/codingbuddy --skill agent-discussion
Clone the repo
git clone --depth 1 https://github.com/JeremyDev87/codingbuddy

Made for: Claude Code, Codex.

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,797 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00041 $0.01797
Opus 5 $0.00020 $0.00898
Sonnet 5 $0.00008 $0.00359
Haiku 4.5 $0.00004 $0.00180

Measured 2d ago against content hash d43a8b9bf5ec, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-discussion 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.

packages/rules/.ai-rules/skills/agent-discussion/SKILL.md · 200 lines

How it starts

The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Discussion Formatter

Overview

When multiple specialist agents contribute opinions, findings, or recommendations, raw text output becomes unreadable. This skill defines a structured terminal format that makes agent debates scannable, severity-aware, and action-oriented.

Core principle: Every agent contribution must be visually distinct, severity-tagged, and traceable to evidence.

Iron Law:

NEVER MIX AGENT OUTPUTS INTO UNSTRUCTURED PROSE — ALWAYS USE THE BOX FORMAT

When to Use

  • Rendering output from parallel specialist agents (security, accessibility, performance, etc.)
  • Displaying code review findings from multiple reviewers
  • Presenting debate/discussion between agents with differing opinions
  • Summarizing consensus or disagreement across agent recommendations
  • EVAL mode consolidated output

Use this ESPECIALLY when:

  • 3+ agents contribute findings on the same topic
  • Agents disagree and the user needs to see both sides
  • Severity levels vary across findings

When NOT to Use

  • Single agent output (no debate to format)
  • Non-terminal output (HTML, JSON API responses)
  • Log-style sequential output where ordering matters more than structure

Format Specification

Agent Contribution Block

Each agent's finding is rendered in a box with metadata:

┌─ {emoji} {agent-name} ─────────────────────────┐
│ {SEVERITY} [{LEVEL}]: {title}                   │
│ {description spanning multiple lines with       │
│ proper indentation and wrapping}                 │
│                                                  │
│ Evidence: {file:line — code or observation}       │
│ Recommendation: {actionable next step}           │
└──────────────────────────────────────────────────┘

Agent Identifiers

Each agent type has a fixed emoji prefix for visual scanning:

Agent Emoji Color Hint
security-specialist 🔒 Red
accessibility-specialist Blue
performance-specialist Yellow
code-quality-specialist 📏 Green
architecture-specialist 🏛️ Purple
test-strategy-specialist 🧪 Cyan
event-architecture-specialist 📨 Orange
integration-specialist 🔗 Teal
observability-specialist 📊 Gray
migration-specialist 🔄 Magenta
seo-specialist 🔍 Lime
ui-ux-design-specialist 🎨 Pink
documentation-specialist 📝 White
code-reviewer 👀 Indigo

Read the full file on GitHub · 200 lines

Changes

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.

  1. 2d ago First seen · 200 lines · 41 tokens per session scan A d43a8b9bf5ec

Subscribe to this mod's changes

agent-discussion is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 1,797 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 2026-08-30.

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