community-intelligence

community-intelligence is a skill for Claude Code from prime-radiant-inc/greenfield. It costs 41 tokens per session (3,972 once invoked), scanned A, original, Apache-2.0.

A method for gathering intelligence from community-written content such as tutorials, reviews, forum posts, issue reports, videos, and changelogs.

In plain words
What is it for?
Use it to search community sources, extract observed behavior, compare community evidence with official documentation, and analyze agreement across reports.
Why use it?
It helps uncover how a product behaves in real use, including edge cases, undocumented defaults, and version-specific changes.

Skill for Claude Code

Written for Claude Code: Claude Code plugin machinery.

Part of the greenfield plugin — 22 skills, 2 commands, 2 agents shipped together

Good fit Use it to search community sources, extract observed behavior, compare community evidence with official documentation, and analyze agreement across reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/prime-radiant-inc/greenfield/community-intelligence
Install

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.

Any agent
npx skills add prime-radiant-inc/greenfield --skill community-intelligence
Clone the repo
git clone --depth 1 https://github.com/prime-radiant-inc/greenfield

Made for: Claude Code.

Or install greenfield, the plugin that ships this one along with the rest of its 22 skills, 2 commands, 2 agents.

Wrote 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.

agentmods badge for community-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/community-intelligence/github.svg)](https://agentmods.dev/skills/prime-radiant-inc/greenfield/community-intelligence)
Your own site
<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.

agentmods 80×15 button for community-intelligence

Your own site · 80×15
<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>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,972 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 10d ago against content hash 783f12f91d62, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

skills/community-intelligence/SKILL.md · 394 lines

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";
}

Read the full file on GitHub · 394 lines

Changes

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.

  1. 10d ago First seen · 394 lines · 41 tokens per session scan A 783f12f91d62

Subscribe to this mod's changes

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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