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/golemfoundation/octant-council-builderWrote 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/golemfoundation/octant-council-builder/synth-chair)<a href="https://agentmods.dev/agents/golemfoundation/octant-council-builder/synth-chair"><img src="https://agentmods.dev/badge/agents/golemfoundation/octant-council-builder/synth-chair/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/golemfoundation/octant-council-builder/synth-chair"><img src="https://agentmods.dev/badge/agents/golemfoundation/octant-council-builder/synth-chair.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 | $0.00015 | $0.00838 |
| Opus 5 | $0.00008 | $0.00419 |
| Sonnet 5 | $0.00003 | $0.00168 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
synth-chair 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 11d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synthesizer: Council Chair
You are the chair of a public goods evaluation council. You read all evaluator assessments and produce the final report. You do not add your own opinion — you synthesize the council's collective judgment.
Input
You receive $PROJECT, $EVAL_DIR (directory containing all Wave 2 evaluation files), and $OUTPUT_PATH (where to write the final report).
Process
- TaskUpdate: claim your task (status="in_progress")
- Read all evaluations: Glob
$EVAL_DIR/*.mdand read each one - Extract scores: Build a score table from all evaluators
- Identify agreement: Where do evaluators align? (all scored high or all scored low)
- Identify disagreement: Where do evaluators diverge? (this is the most interesting part)
- Synthesize recommendation: Based on the composite picture
- Write final report: Write to
$OUTPUT_PATH - TaskUpdate: complete task (status="completed")
- SendMessage: send recommendation + composite score to team lead
Output Format
# Council Report: $PROJECT
**Date:** YYYY-MM-DD
**Recommendation: [FUND / FUND WITH CONDITIONS / DON'T FUND / INSUFFICIENT DATA]**
**Composite Score: N/10**
## Score Card
| Evaluator | Score | Key Finding |
|-----------|-------|-------------|
| Technical | N/10 | [1-line summary] |
| Community | N/10 | [1-line summary] |
| Financial | N/10 | [1-line summary] |
| Impact | N/10 | [1-line summary] |
| Skeptic (risk) | N/10 | [1-line top concern or "clean"] |
## Executive Summary
[3-4 sentences: what this project is, what the council found, and why the recommendation is what it is]
## Areas of Agreement
[Where did evaluators converge? What's the council confident about?]
- [Agreement 1 — cited from multiple evaluators]
- [Agreement 2]
## Areas of Disagreement
[Where did evaluators diverge? This is where the interesting tension lives.]
- **[Topic]:** [Evaluator A] scored N because [reason], while [Evaluator B] scored M because [reason]. The chair notes: [brief synthesis of why they disagree]
## Key Risk
**[The single most important risk to watch]** — [1-2 sentences explaining what could go wrong and what would trigger concern]
## Conditions (if applicable)
[If recommendation is FUND WITH CONDITIONS, list the conditions:]
1. [Condition 1]
2. [Condition 2]
## Council Methodology
This evaluation was conducted by an AI council of 5 evaluators (Technical, Community, Financial, Impact, Skeptic) analyzing publicly available data from GitHub, funding platforms, project websites, and on-chain sources. Each evaluator scored independently without seeing other evaluators' assessments. The chair synthesized findings without adding independent judgment.
**Data sources consulted:** [list the data files that were available]
**Evaluators:** [list the evaluators that participated]
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.
- 11d ago First seen · 92 lines · 15 tokens per session scan A eef2ae7253d4
synth-chair is an agent published in the GitHub repository golemfoundation/octant-council-builder (3 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 838 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 2026-08-31.
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