analysis-pipeline
Reverse engineering - multi-source product intelligence analysis with provenance tracking. Master methodology for all analysis…
Layer 1 skill for community intelligence gathering. Search channels, extraction methodology, consensus analysis, version-aware behavioral changes, structural contamination guard. Loaded by the analyzer agent for community intelligence gathering.
Claude Code
$ npx -y skills add prime-radiant-inc/greenfield --skill community-intelligence --agent claude-code
Codex
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a codex -y
Cursor
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a cursor -y
Gemini CLI
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a gemini-cli -y
GitHub Copilot
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a github-copilot -y
OpenCode
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a opencode -y
Windsurf
$ npx skills add prime-radiant-inc/greenfield --skill community-intelligence -a windsurf -y
name: community-intelligence description: Layer 1 skill for community intelligence gathering. Search channels, extraction methodology, consensus analysis, version-aware behavioral changes, structural contamination guard. Loaded by the analyzer agent for community intelligence gathering.
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.
Use Community Intelligence mode when:
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/`.
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.
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";
}| # | Search Pattern | Purpose | |---|----------------|---------| | 1 | `{product} tutorial` | Step-by-step guides | | 2 | `{product} getting started guide blog` | Setup walkthroughs | | 3 | `{product} walkthrough` | End-to-end usage | | 4 | `{product} how to use` | Practical usage | | 5 | `{product} step by step` | Sequential instructions | | 6 | `{product} setup guide` | Configuration guides | | 7 | `{product} tips and tricks` | Advanced behavioral observations | | 8 | `{product} advanced usage` | Power-user behavioral observations | | 9 | `{product} site:medium.com` | Medium posts | | 10 | `{product} site:dev.to` | Dev.to posts | | 11 | `{product} site:hashnode.dev` | Hashnode posts |
| # | Search Pattern | Purpose | |---|----------------|---------| | 1 | `{product} site:stackoverflow.com` | Community Q&A | | 2 | `{product} site:reddit.com` | Reddit discussions | | 3 | `{product} site:news.ycombinator.com` | HN discussions | | 4 | `{product} site:github.com discussions` | GitHub Discussions | | 5 | `{product} forum` | Product-specific forums | | 6 | `{product} unexpected behavior` | Behavioral surprises | | 7 | `{product} how does {feature} work` | Feature-specific behavioral questions |
| # | Search Pattern | Purpose | |---|----------------|---------| | 1 | `site:github.com {product} is:issue "expected" "actual"` | Bug reports with behavioral contracts | | 2 | `site:github.com {product} is:issue label:bug` | Known bugs (behavioral deviations) | | 3 | `site:github.com {product} is:issue "steps to reproduce"` | Reproducible behavioral observations | | 4 | `site:gitlab.com {product} issues` | GitLab issue tracker |
Issue tracker content is extremely high-value because bug reports document the gap between expected and actual behavior — both are behavioral specifications.
| # | Search Pattern | Purpose | |---|----------------|---------| | 1 | `{product} review` | Product reviews | | 2 | `{product} comparison` | Comparative behavioral analysis | | 3 | `{product} vs {competitor}` | Behavioral differences described precisely | | 4 | `{product} marketplace review` | Marketplace reviews (VS Code, npm, etc.) | | 5 | `{product} extension review` | Extension/plugin marketplace reviews | | 6 | `{product} pros cons` | Feature-level behavioral assessments |
| # | Search Pattern | Purpose | |---|----------------|---------| | 1 | `{product} changelog` | Official version history | | 2
Reverse engineer clean behavioral specs from any codebase. Greenfield reads source code, documentation, SDKs, runtime behavior, and binaries, then produces behavioral specifications, test vectors, acceptance criteria, and a full provenance trail.
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Ask which skill or flow fits your situation. A router over the skills in this repo.