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 oaustegard/claude-skills --skill convening-expertsgit clone --depth 1 https://github.com/oaustegard/claude-skillsWrote 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/oaustegard/claude-skills/convening-experts)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/convening-experts"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/convening-experts/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/oaustegard/claude-skills/convening-experts"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/convening-experts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.02026 |
| Opus 5 | $0.00034 | $0.01013 |
| Sonnet 5 | $0.00013 | $0.00405 |
| Haiku 4.5 | $0.00007 | $0.00203 |
Grade A, and why
convening-experts 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 yesterday.
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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SURFACE ROUTING — read first
This skill hand-rolls subagent orchestration via raw Anthropic API calls. A managed runtime now does the same job. Which one to use depends on your surface:
- In Claude Code (incl. CCotw): use the native runtime, NOT this skill. If you
can invoke
/deep-research, trigger a run with theworkflowkeyword, set/effort ultracode, or spawn Task subagents — do that instead. The runtime gives 16-concurrent / 1000-agent ceilings, an approval gate, adversarial cross-review, and in-session resume that this skill would otherwise reimplement badly. Dynamic workflows shipped in research preview (Claude Code v2.1.154+, 2026). - In claude.ai chat or the bare API (no workflow runtime): use this skill.
Parallel API instances over httpx is the only fan-out path here.
muninn_utils.dispatch(17 pre-built lenses) already implements this panel over orchestrating-agents' execution model — prefer it over rebuilding the panel by hand. Proceed below.
Discriminator: do you have a native subagent/Task tool or a workflow command? Yes → native. No → this skill. Never reimplement the runtime where it already exists.
Convening Experts
Convene domain experts and methodological specialists to solve problems through multi-round collaborative discussion. Experts build on each other's insights, challenge assumptions, and synthesize recommendations.
Panel Format
Single-Round Consultation
For simpler problems requiring multiple viewpoints:
- Assemble panel (3-5 experts based on problem domain)
- Each expert provides independent perspective (parallel, not sequential)
- Synthesize recommendations with attribution
Multi-Round Discussion
For complex problems requiring collaborative reasoning:
- Round 1: Each expert analyzes problem independently
- Round 2: Experts respond to each other's insights, building on or challenging points
- Round 3 (if needed): Converge on synthesis, resolve disagreements
- Final synthesis: Integrated recommendations with decision framework
What ships with it
8 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.
- CHANGELOG.md 944 B
- examples/process-improvement-example.md 8.1 KB
- examples/strategic-decision-example.md 5.2 KB
- examples/technical-troubleshooting-example.md 11 KB
- README.md 224 B
- references/ancient-philosophers.md 6.4 KB
- references/consulting-frameworks.md 2.1 KB
- references/msd-domain-experts.md 1.3 KB
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.
- yesterday Changed · -95 lines 6cfddae6c613
- 11d ago First seen · 319 lines · 67 tokens per session scan A fb800144a4c4
convening-experts is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 2,026 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 2026-08-30.
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