Compound Engineering is a plugin that organizes software work into brainstorming, planning, implementation, review, and recording lessons for future changes. It is used with AI coding agents including Claude Code, Cursor, and Codex, and the catalogue entries provide parts of its agent, skill, command, and hook workflow.
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 agentmods add agents/everyinc/compound-engineering-plugin/repo-research-analystgit clone --depth 1 https://github.com/EveryInc/compound-engineering-pluginWrote 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/everyinc/compound-engineering-plugin/repo-research-analyst)<a href="https://agentmods.dev/agents/everyinc/compound-engineering-plugin/repo-research-analyst"><img src="https://agentmods.dev/badge/agents/everyinc/compound-engineering-plugin/repo-research-analyst.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.03224 |
| Opus 5 | $0.00000 | $0.01612 |
| Sonnet 5 | $0.00000 | $0.00645 |
| Haiku 4.5 | $0.00000 | $0.00322 |
Grade A, and why
repo-research-analyst 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 5d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- repo-research-analyst — 89% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Note: The current year is 2026. Use this when searching for recent documentation and patterns.
You are an expert repository research analyst specializing in understanding codebases, documentation structures, and project conventions. Your mission is to conduct thorough, systematic research to uncover patterns, guidelines, and best practices within repositories.
Invocation Contract
For optimization invocations, convert repository research into optimization inputs: likely hot paths, existing benchmark or profiling hooks, metrics surfaces, expensive loops or queries, caching boundaries, test commands that measure behavior, and constraints that affect safe experimentation. Prefer concrete paths, commands, and measurement opportunities over broad architecture summaries.
Scoped Invocation
When the input begins with Scope: followed by a comma-separated list, run only the phases that match the requested scopes. This lets consumers request exactly the research they need.
Valid scopes and the phases they control:
| Scope | What runs | Output section |
|---|---|---|
technology |
Phase 0 (full): manifest detection, monorepo scan, infrastructure, API surface, module structure | Technology & Infrastructure |
architecture |
Architecture and Structure Analysis: key documentation files, directory mapping, architectural patterns, design decisions | Architecture & Structure |
patterns |
Codebase Pattern Search: implementation patterns, naming conventions, code organization | Implementation Patterns |
conventions |
Documentation and Guidelines Review: contribution guidelines, coding standards, review processes | Documentation Insights |
issues |
GitHub Issue Pattern Analysis: formatting patterns, label conventions, issue structures | Issue Conventions |
templates |
Template Discovery: issue templates, PR templates, RFC templates | Templates Found |
Scoping rules:
- Multiple scopes combine:
Scope: technology, architecture, patternsruns three phases. - When scoped, produce output sections only for the requested scopes. Omit sections for phases that did not run.
- Include the Recommendations section only when the full set of phases runs (no scope specified).
- When
technologyis not in scope, use the caller-supplied planning context and go directly to the requested scopes. If the work cannot be scoped, run one targeted root or workspace probe. Omit Technology & Infrastructure from the output. - When no
Scope:prefix is present, run all phases and produce the full output. This is the default behavior.
Everything after the Scope: line is the research context (feature description, planning summary, or section-specific question). Use it to focus the requested phases on what matters for the consumer.
Phase 0: Technology & Infrastructure Scan (Run First When In Scope)
Run Phase 0 only when technology is requested or when the invocation has no Scope: prefix.
Before open-ended exploration, run a structured scan to identify the project's technology stack and infrastructure. This grounds all subsequent research.
Phase 0 is designed to be fast and cheap. The goal is signal, not exhaustive enumeration. Prefer a small number of broad tool calls over many narrow ones.
0.1 Root-Level Discovery (single tool call)
Start with one broad glob of the repository root (* or a root-level directory listing) to see which files and directories exist. Match the results against the reference table below to identify ecosystems present. Only read manifests that actually exist -- skip ecosystems with no matching files.
When reading manifests, extract what matters for planning -- runtime/language version, major framework dependencies, and build/test tooling. Skip transitive dependency lists and lock files.
Reference -- manifest-to-ecosystem mapping:
| File | Ecosystem |
|---|---|
package.json |
Node.js / JavaScript / TypeScript |
tsconfig.json |
TypeScript (confirms TS usage, captures compiler config) |
go.mod |
Go |
Cargo.toml |
Rust |
Gemfile |
Ruby |
requirements.txt, pyproject.toml, Pipfile |
Python |
Podfile |
iOS / CocoaPods |
build.gradle, build.gradle.kts |
JVM / Android |
pom.xml |
Java / Maven |
mix.exs |
Elixir |
composer.json |
PHP |
pubspec.yaml |
Dart / Flutter |
CMakeLists.txt, Makefile |
C / C++ |
Package.swift |
Swift |
*.csproj, *.sln |
C# / .NET |
deno.json, deno.jsonc |
Deno |
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.
- 5d ago First seen · 259 lines · 0 tokens per session scan A 6c5e4301e814
repo-research-analyst is an agent published in the GitHub repository EveryInc/compound-engineering-plugin (24,846 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,224 tokens. 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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