Agent skill

Improve Codebase Architecture

by pietheinstrengholt in pietheinstrengholt/rssmonster

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

MITAuto-check passed

Install Improve Codebase Architecture

skills CLI
$ npx skills add pietheinstrengholt/rssmonster --skill improve-codebase-architecture -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pietheinstrengholt/rssmonster improve-codebase-architecture --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pietheinstrengholt/rssmonster.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/improve-codebase-architecture .claude/skills/improve-codebase-architecture && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
improve-codebase-architecture
GitHub stars
564
Used in
34 other repos
Token cost
~1.5k tokens
SKILL.md length
845 words
Files
3
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

  • Works in 3 steps: Explore → Present candidates as an HTML report → Grilling loop
  • Calls git

What it does

Improve Codebase Architecture is an agent skill from pietheinstrengholt/rssmonster. Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `HTML-REPORT.md` and `agents/openai.yaml`).

The repository describes itself as: Modern, self-hosted RSS reader with smart folders, powerful search, and a clean three-pane reading experience. Built with Vue and Express. The licence is MIT.

Example prompts

  • “/improve-codebase-architecture”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Explore
  2. Present candidates as an HTML report
  3. Grilling loop

What it can do on your machine

Read from SKILL.md and the folder at commit d2c278d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Improve Codebase Architecture loads about 1.5k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 845 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pietheinstrengholt/rssmonster at commit d2c278d, republished under its MIT licence (© pietheinstrengholt). 845 words, ~1,500 tokens.

Download SKILL.mdSave it as .claude/skills/improve-codebase-architecture/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
improve-codebase-architecture
description
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
disable-model-invocation
true

Improve Codebase Architecture

Surface architectural friction and propose deepening opportunities: refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.

This command is informed by the project's domain model and built on a shared design vocabulary:

  • Call the Skill tool with "codebase-design" for the architecture vocabulary (module, interface, depth, seam, adapter, leverage, locality) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion, and don't drift into "component," "service," "API," or "boundary."
  • The domain language in GLOSSARY.md gives names to good seams; ADRs in docs/adr/ record decisions this command should not re-litigate.

Process

1. Explore

Scope before you scan: YAGNI. Deepening a module pays off by making future changes to it easier, so put extra weight on the parts of the codebase that have recently changed. Decide where to look before you look:

  • If the user named a direction (a module, a subsystem, a pain point), take it, and skip the inference below.
  • Otherwise, walk back a good stretch of the commit history (git log --oneline) to find the codebase's hot spots, the files and areas that keep coming up, and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net.

Read the project's domain glossary (GLOSSARY.md) and any ADRs in the area you're touching first.

Then spawn a sub-agent to walk the codebase. Don't follow rigid heuristics; explore organically and note where you experience friction:

  • Where does understanding one concept require bouncing between many small modules?
  • Where are modules shallow, with an interface nearly as complex as the implementation?
  • Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no locality)?
  • Where do tightly-coupled modules leak across their seams?
  • Which parts of the codebase are untested, or hard to test through their current interface?

Apply the deletion test to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.

2. Present candidates as an HTML report

Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from $TMPDIR, falling back to /tmp (or %TEMP% on Windows), and write to <tmpdir>/architecture-review-<timestamp>.html so each run gets a fresh file. Open it for the user (xdg-open <path> on Linux, open <path> on macOS, start <path> on Windows) and tell them the absolute path.

The report uses Tailwind via CDN for layout and styling, and Mermaid via CDN for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals: use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a before/after visualisation. Be visual.

For each candidate, render a card with:

  • Files: which files/modules are involved
  • Problem: why the current architecture is causing friction
  • Solution: plain English description of what would change
  • Benefits: explained in terms of locality and leverage, and how tests would improve
  • Before / After diagram: side-by-side, custom-drawn, illustrating the shallowness and the deepening
  • Recommendation strength: one of Strong, Worth exploring, Speculative, rendered as a badge
Show full SKILL.md (300 more words)Show less

End the report with a Top recommendation section: which candidate you'd tackle first and why.

Use GLOSSARY.md vocabulary for the domain, and the /codebase-design vocabulary for the architecture. If GLOSSARY.md defines "Order," talk about "the Order intake module," not "the FooBarHandler," and not "the Order service."

ADR conflicts: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: "contradicts ADR-0007, but worth reopening because…"). Don't list every theoretical refactor an ADR forbids.

See HTML-REPORT.md for the full HTML scaffold, diagram patterns, and styling guidance.

Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"

3. Grilling loop

Once the user picks a candidate, call the Skill tool with "grilling" to walk the decision tree with them: constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.

Side effects happen inline as decisions crystallize; call the Skill tool with "domain-modeling" to keep the domain model current as you go:

  • Naming a deepened module after a concept not in GLOSSARY.md? Add the term to GLOSSARY.md. Create the file lazily if it doesn't exist.
  • Sharpening a fuzzy term during the conversation? Update GLOSSARY.md right there.
  • User rejects the candidate with a load-bearing reason? Offer an ADR, framed as: "Want me to record this as an ADR so future architecture reviews don't re-suggest it?" Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing; skip ephemeral reasons ("not worth it right now") and self-evident ones.
  • Want to explore alternative interfaces for the deepened module? Call the Skill tool with "codebase-design" and use its design-it-twice parallel sub-agent pattern.

© pietheinstrengholt, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in .agents/skills/improve-codebase-architecture of pietheinstrengholt/rssmonster.

  • SKILL.md
  • HTML-REPORT.md
  • agents/openai.yaml

Open the folder on GitHubat commit d2c278d

Used in 35 other repositories

We found 43 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 34 other GitHub owners. This page covers the copy in pietheinstrengholt/rssmonster, which our catalogue first saw on October 8, 2026.

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Repo Scanaffaan-m/ECC275k—~1.3kAutomated safety check: PassMIT
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Questions about Improve Codebase Architecture

What does Improve Codebase Architecture do?

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick. Improve Codebase Architecture is an agent skill from pietheinstrengholt/rssmonster. Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

How do I install Improve Codebase Architecture in Claude Code?

Run `npx skills add pietheinstrengholt/rssmonster --skill improve-codebase-architecture -a claude-code`. Or copy the skill folder (.agents/skills/improve-codebase-architecture in pietheinstrengholt/rssmonster) into .claude/skills/improve-codebase-architecture in your project. Claude Code loads it when a task matches its description.

How do I install Improve Codebase Architecture in Codex?

Run `npx skills add pietheinstrengholt/rssmonster --skill improve-codebase-architecture -a codex`. Or copy the skill folder (.agents/skills/improve-codebase-architecture in pietheinstrengholt/rssmonster) into .agents/skills/improve-codebase-architecture in your project. Codex loads it when a task matches its description.

Can I use Improve Codebase Architecture in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pietheinstrengholt/rssmonster --skill improve-codebase-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/improve-codebase-architecture, .gemini/skills/improve-codebase-architecture, .github/skills/improve-codebase-architecture and .opencode/skills/improve-codebase-architecture in your project.

What does Improve Codebase Architecture need to run?

Going by SKILL.md and its folder, Improve Codebase Architecture needs the command-line tools its instructions call (git).

Does Improve Codebase Architecture access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Improve Codebase Architecture safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Improve Codebase Architecture use?

Improve Codebase Architecture is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Improve Codebase Architecture use?

About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Improve Codebase Architecture?

Skills that share tags, products or a category with Improve Codebase Architecture: Scan (wshobson/agents, 40k stars), Presentations (asgeirtj/system_prompts_leaks, 69k stars), Repo Scan (affaan-m/ECC, 275k stars) and Repo Scan (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Improve Codebase Architecture?

pietheinstrengholt (a GitHub user) maintains it in pietheinstrengholt/rssmonster, which has 564 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 7, 2026.

Source: pietheinstrengholt/rssmonster on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.