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 skills add JeremyDev87/codingbuddy --skill agent-discussiongit clone --depth 1 https://github.com/JeremyDev87/codingbuddyWrote 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/skills/jeremydev87/codingbuddy/agent-discussion)<a href="https://agentmods.dev/skills/jeremydev87/codingbuddy/agent-discussion"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/agent-discussion/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/skills/jeremydev87/codingbuddy/agent-discussion"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/agent-discussion.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 | $0.00041 | $0.01797 |
| Opus 5.5 | $0.00016 | $0.00719 |
| Sonnet 5.5 | $0.00008 | $0.00359 |
| Haiku 4.5 | $0.00004 | $0.00180 |
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 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 — 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 |
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 · 200 lines · 41 tokens per session scan A d43a8b9bf5ec
agent-discussion is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 6mo ago), licensed MIT. It adds 41 tokens to every session and 1,797 once invoked, about $0.0002 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 2026-08-30.
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