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 regen-coordination/org-os-template --skill idea-scoutgit clone --depth 1 https://github.com/regen-coordination/org-os-templateWrote 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/regen-coordination/org-os-template/idea-scout)<a href="https://agentmods.dev/skills/regen-coordination/org-os-template/idea-scout"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/idea-scout/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/regen-coordination/org-os-template/idea-scout"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/idea-scout.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 | $0.00013 | $0.01296 |
| Opus 5 | $0.00006 | $0.00648 |
| Sonnet 5 | $0.00003 | $0.00259 |
| Haiku 4.5 | $0.00001 | $0.00130 |
Grade A, and why
idea-scout 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 8d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Scout
When to Use
Activate after knowledge processing (blog posts, podcast episodes, meeting insights have been added to knowledge/). Run periodically to surface new ecosystem gaps and opportunities.
Also activate when:
- Operator asks "what gaps exist in our ecosystem?"
- After processing a batch of new content
- During autoresearch improvement loops
- When MASTERPLAN.md activations include idea scouting
Procedure
Step 1: Read Current State
- Read
data/knowledge-manifest.yaml— understand which domains exist and their coverage - Read
data/ideas.yaml— understand existing ideas to avoid duplicates - Read
data/projects.yaml— understand active work to identify adjacencies - Read
data/relationships.yaml— understand partner capabilities
Step 2: Scan Knowledge for Patterns
For each knowledge domain in knowledge/:
- Read the
_index.yamlfor domain overview - Scan topic pages for:
- Gaps mentioned: "there is no...", "missing...", "need for..."
- Repeated themes: Topics appearing across multiple sources
- Unmet needs: Problems described without solutions
- Emerging trends: New patterns not yet addressed by projects
- Cross-domain opportunities: Insights from combining domains
Step 3: Evaluate Candidates
For each potential idea, evaluate:
- Novelty: Is this already in ideas.yaml or projects.yaml?
- Relevance: Does it align with the org's mission (SOUL.md)?
- Feasibility: Can the org's skills and network address this?
- Evidence: How many sources mention this gap?
- Impact: How significant would filling this gap be?
Step 4: Surface Ideas
For ideas that pass evaluation:
- Create entry in
data/ideas.yaml:
- id: "idea-[incremental]"
title: "[Descriptive title]"
status: "surfaced"
source: "knowledge/[domain]/[topic].md"
submitted_by: "agent"
champions: []
ecosystem_gap: "[One-sentence gap description]"
description: "[2-3 sentence description]"
hatched_repo: null
skills_needed: ["[skill-1]", "[skill-2]"]
resources:
- "knowledge/[domain]/[related-topic].md"
compensation:
model: null
pool: null
created: "[today]"
updated: "[today]"
votes: 0
comments: []
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.
- 8d ago First seen · 173 lines · 13 tokens per session scan A 1c3eb3f9493a
idea-scout is a skill published in the GitHub repository regen-coordination/org-os-template (5 stars, last pushed 6d ago), licensed MIT. It adds 13 tokens to every session and 1,296 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 2026-09-03.
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