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 prime-radiant-inc/greenfield --skill community-intelligencegit clone --depth 1 https://github.com/prime-radiant-inc/greenfieldWrote 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/prime-radiant-inc/greenfield/community-intelligence)<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/community-intelligence"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/community-intelligence/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/prime-radiant-inc/greenfield/community-intelligence"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/community-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 218 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 322 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.03972 |
| Opus 5 | $0.00020 | $0.01986 |
| Sonnet 5 | $0.00008 | $0.00794 |
| Haiku 4.5 | $0.00004 | $0.00397 |
Grade A, and why
community-intelligence 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 10d 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 — 394 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Community Intelligence Methodology
Extract behavioral specifications from user-generated content: tutorials, blog posts, reviews, forum threads, issue reports, video transcripts, and changelogs. These are external observations of behavior by real users — zero structural contamination, pure behavioral surface.
When to Use This Mode
Use Community Intelligence mode when:
- The target product has active users who write about it
- Official documentation has gaps (community fills in what docs miss)
- You need observed behavior to corroborate or contradict official claims
- Edge cases, defaults, and undocumented behavior need coverage
- Version-specific behavioral changes need tracking
This mode runs independently of all other intelligence sources. It requires only web access. All output is public origin and goes to workspace/public/community/.
Why Community Content Matters
Official documentation describes intended behavior. Community content describes observed behavior. The gap between the two is where edge cases, undocumented features, surprising defaults, and breaking changes live.
A tutorial author who writes "when I ran tool --flag, it output X" has performed a runtime observation. A GitHub issue that says "expected Y but got Z" documents a behavioral contract violation. A blog post walkthrough that shows step-by-step output is equivalent to a test vector recorded by a human.
1. Search Channels
Search proceeds across six channels. Execute multiple patterns per channel before moving on.
digraph community_search {
rankdir=TB;
"Start community research" [shape=doublecircle];
"Channel 1: Tutorials & blog posts" [shape=box];
"Channel 2: Forums & Q&A" [shape=box];
"Channel 3: Issue trackers" [shape=box];
"Channel 4: Reviews & marketplace" [shape=box];
"Channel 5: Version-specific content" [shape=box];
"Channel 6: Video content" [shape=box];
"Diminishing returns?" [shape=diamond];
"Source budget exhausted?" [shape=diamond];
"Build consensus analysis" [shape=box];
"Write claims, consensus, gaps" [shape=box];
"Research complete" [shape=doublecircle];
"Start community research" -> "Channel 1: Tutorials & blog posts";
"Channel 1: Tutorials & blog posts" -> "Channel 2: Forums & Q&A";
"Channel 2: Forums & Q&A" -> "Channel 3: Issue trackers";
"Channel 3: Issue trackers" -> "Channel 4: Reviews & marketplace";
"Channel 4: Reviews & marketplace" -> "Channel 5: Version-specific content";
"Channel 5: Version-specific content" -> "Channel 6: Video content";
"Channel 6: Video content" -> "Diminishing returns?";
"Diminishing returns?" -> "Build consensus analysis" [label="yes"];
"Diminishing returns?" -> "Source budget exhausted?" [label="no"];
"Source budget exhausted?" -> "Build consensus analysis" [label="yes"];
"Source budget exhausted?" -> "Channel 1: Tutorials & blog posts" [label="no, continue"];
"Build consensus analysis" -> "Write claims, consensus, gaps";
"Write claims, consensus, gaps" -> "Research complete";
}
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.
- 10d ago First seen · 394 lines · 41 tokens per session scan A 783f12f91d62
community-intelligence is a skill published in the GitHub repository prime-radiant-inc/greenfield (275 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 3,972 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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