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Layered Summary

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vicnaum
layered-summary

Create hierarchical, bottom-up "layered summaries" by generating `AGENTS.md` files per directory in a subtree (e.g., `reth/crates/engine`). Deep directories summarize files and key APIs; parent directories roll up children. Also use to incrementally update an existing `AGENTS.md` subtree after content changes. No snippets; keep summaries navigational and checkable.

Overview

Publishervicnaum
Repositoryvics-agent-skills
Skill namelayered-summary
Stars
53
Forks
5
Bundled files
6
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by vicnaum on GitHub. Read the source before you install it.

Installation

Install the Layered Summary AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vicnaum/vics-agent-skills/tree/main/skills/layered-summary
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vicnaum/vics-agent-skills.git /tmp/vics-agent-skills
mkdir -p .claude/skills
cp -r /tmp/vics-agent-skills/skills/layered-summary .claude/skills/layered-summary
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Layered Summary in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Layered Summary on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Layered Summary is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Layered Summary (AGENTS.md)

Generate a layered set of AGENTS.md files so that:

  • Deeper directories are more detailed (files + key types/functions + local relationships).
  • Higher directories are short rollups of their direct children (architecture map).

This is designed to pair well with Cursor's nested AGENTS.md support: when you work in a folder, you automatically get its local summary plus its ancestors' higher-level context.

Hard constraints

  • Create/update only AGENTS.md files. Do not change other files.
  • Operate only inside the target root subtree.
  • No snippets/excerpts and no long quotes. Summaries must be short and checkable (paths/names).
  • Use ASCII only; avoid non-ASCII characters.
  • Delegate codebase exploration to Explore subagents (see "Subagent-first workflow"). The main agent remains the only writer of AGENTS.md.
  • Don't stop mid-run: continue until the Completion criteria is satisfied. If you are forced to pause, leave a resumable checkpoint (see Resume after interruption) and ensure parent ledgers are accurate.
  • Skip generated/vendored/third-party blobs. If present, mention them briefly (and why they exist) but don't document them exhaustively.
  • Avoid speculation. Use [unclear] / [TBD] markers when needed.

Scripts (recommended)

Use these helper scripts to make planning/scaffolding/verification deterministic and resumable.

  • All scripts support Repomix-style scoping flags:

    • --include "<glob1,glob2,...>" (positive filter)
    • -i/--ignore "<glob1,glob2,...>" (negative filter; ignore wins on conflicts)
    • Globs are comma-separated and support ** (e.g., docs/**/*.md matches docs/README.md and deeper files).
    • If you don't scope, the scripts will treat most directories with files as meaningful; use --include/--ignore to focus and avoid huge generated/vendor trees.
    • The scripts also avoid descending into huge dependency directories by default and omit them from ledgers: node_modules/, bower_components/, jspm_packages/. If there's some valid reason to include them, pass an explicit --include that targets them.
  • scripts/agents_plan.py

    • Build a bottom-up "waves" schedule for a subtree (derived only; no writes).
    • Supports --mode full and --mode update (git-based incremental planning).
  • scripts/agents_scaffold.py

    • Create-only scaffolder: creates missing DIR/AGENTS.md stubs for meaningful directories.
    • Does not touch existing AGENTS.md files. Default is dry-run; pass --write to create.
  • scripts/agents_verify.py

    • Verify invariants: every meaningful dir has AGENTS.md, one-hop ledger matches filesystem, ASCII-only.
    • With --strict: also fail on remaining [TBD] or unchecked - [ ].
  • scripts/normalize_agents_ascii.py

    • Optional ASCII normalizer for AGENTS.md (default dry-run; --write to edit).
  • scripts/export_agents_md.py

    • Optional export-only utility: copy AGENTS.md files from a subtree into a standalone folder.

Subagent-first workflow (required)

Use Explore subagents for every meaningful directory you process. Explore is read-only; it should only return analysis. The main agent must create/update AGENTS.md.

Concurrency / conflict rules

  • Scheduling is bottom-up: start from the deepest meaningful leaf directories and work upward (postorder).
  • Never run Explore on a directory until all meaningful descendants already have complete AGENTS.md. Always complete children first, then do the parent.
  • If running multiple Explore tasks in parallel, only parallelize siblings (directories that do not contain each other).
  • Prefer deterministic ordering (alphabetical) when choosing which sibling directories to process next, to keep results reproducible.

Explore subagent contract (exploring mode: very thorough)

For each directory DIR/ inside the target root:

  • Run an Explore subagent with thoroughness level very thorough scoped to DIR/.
  • The Explore subagent must:
    • Discover and validate the directory's one-hop structure (immediate subdirectories + files).
    • Identify which immediate subdirectories are meaningful vs skippable (and why).
    • Analyze local files in DIR/ (if any). "Trust children" applies only to nested folders, not the current directory's own files.
    • If immediate child AGENTS.md files exist, read them and incorporate their responsibilities into PURPOSE/RELATIONSHIPS. Treat child AGENTS.md as the source of truth for nested subfolders.
    • Do not recursively explore child subdirectories' contents where child/AGENTS.md already exists. Prefer to synthesize from child/AGENTS.md instead.
      • Exception: if something is missing/contradictory or the filesystem ledger does not match, it is OK to spot-check the child directory to resolve the discrepancy; keep spot-checks minimal and report to orchestrator why.
    • Produce a structured report that the main agent can convert into the standard AGENTS.md template.
    • Provide a short "PARENT ROLLUP" the main agent can copy into the parent's subdirectory checkbox entry.
    • Use ASCII only, avoid big snippets/excerpts, and be explicit about uncertainty.

Use this exact output structure from the Explore subagent (so the main agent can paste/transform it reliably):

text
DIRECTORY
- path: <path relative to target root>
- kind: leaf | non-leaf | aggregator-only

PURPOSE
<1-3 sentences>

PARENT ROLLUP
- <1-2 sentences or 1-3 bullets; keep it short; include up to 3 concrete pointers (subdirs/files/symbol names)>

CONTENTS (ONE HOP)
SUBDIRECTORIES
- <name>/ - process | skip (<reason>)
...

FILES
- <file> - <role (1-2 sentences)>
  - key-items: <2-10 names or config keys>
  - interactions: <optional 0-2 bullets, paths/modules only>
...

KEY APIS (NO SNIPPETS)
- types/classes/interfaces: <comma-separated names> - <optional 1-liners>
- modules/packages: <comma-separated names> - <optional 1-liners>
- functions: <comma-separated names> - <optional 1-liners>

RELATIONSHIPS
- depends-on: <paths/modules> - <why>
- used-by: <paths/modules> - <why>
- data-control-flow:
  - <3-12 bullets, high level>

LEAF-ONLY (IF LEAF)
FILES (DETAILED)
- <file>
  - role: <why it exists>
  - key-items: <3-10 names>
  - interactions: <how it connects to sibling files>
  - knobs-invariants: <important constraints/tuning>
...
END-TO-END FLOW
- <5-12 bullets>

NOTES
- <0-n bullets; include [unclear] where needed>

Target root

  • Use the user-provided root directory.
  • If none is provided, default to reth/crates/engine.

Directory eligibility (meaningful vs skippable)

This skill and the helper scripts do not try to detect “code” vs “non-code” by language/framework.

Instead, scope is controlled by --include / --ignore, and a directory is treated as meaningful (must have an AGENTS.md) when:

  • It is in-scope (not ignored; and if --include is provided, it is in the include-closure), and
  • It either contains at least one in-scope non-AGENTS.md file, or contains at least one meaningful in-scope child directory (so it can roll up children).

Directories that are out-of-scope or empty can still appear in the one-hop ledger, but must be marked as skipped with an explicit reason (e.g., out of scope, generated, vendored, binary blobs, empty).

Optional: use tree for planning & quick verification (convenience)

If tree is available, use it for a fast, human-readable scan of what exists and to spot large/unwanted subtrees early.

  • Quick overview (bounded depth):
bash
tree -a -L 4 reth/crates/engine
  • See where AGENTS.md already exists:
bash
tree -a --prune -P 'AGENTS.md' reth/crates/engine

If tree is not available, use find/directory listings instead. tree is a convenience; the ledger invariant (one-hop subdirectory checklist in every AGENTS.md) is the correctness mechanism.

The grounding mechanism (don't miss folders)

Invariant: Every AGENTS.md must contain a one-hop inventory of its immediate subdirectories (excluding always-ignored and default-pruned dependency dirs unless explicitly included), and that list must match the filesystem under those rules.

Use checkbox statuses to make progress explicit:

  • - [ ] \child/` - [TBD]` = discovered, not processed yet
  • - [x] \child/` - = processed, summary filled fromchild/AGENTS.md`
  • - [x] \child/` - (skip: )= inspected and intentionally skipped (e.g.out of scope, generated, vendored, empty`)

Rule: Before leaving a directory, refresh the one-hop list from the filesystem and ensure no ledger-eligible child directory is missing from the list.

Standard AGENTS.md template

Use this structure everywhere (omit sections that truly don't apply). Leaf directories must be more detailed than one-line-per-file (see "Leaf directories: required detail" below).

markdown
# <directory-name>

## Purpose
<1-3 sentences describing what this directory provides and why it exists.>

## Contents (one hop)
### Subdirectories
- [ ] `child-a/` - [TBD]
- [ ] `child-b/` - [TBD]

### Files
- `<important local file>` - <role (1-2 sentences)> (e.g. `README.md`, `docs.md`, `package.json`, `pyproject.toml`)
  - **Key items**: <2-6 relevant names (headings/commands/config keys), or "n/a" if purely descriptive>
- `src/<file>` - <role (1-2 sentences)>
  - **Key items**: `TypeA`, `TypeB`, `fn_x()`, `CONST_Y`
  - **Interactions** (optional): <mentions of sibling files/modules this connects to>
- `<top-level file>` - <role (1-2 sentences)> (only if relevant to this directory's responsibility)
  - **Key items**: <2-6 names>

## Key APIs (no snippets)
- **Types / Classes / Interfaces**: `Foo`, `Bar` - <1-liners>
- **Modules / Packages**: `<name>` - <1-liners> (if applicable)
- **Functions**: `qux()` - <1-liners>

## Relationships
- **Depends on**: <paths/modules> - <why>
- **Used by**: <paths/modules> - <why>
- **Data/control flow**: <3-7 bullets, high level>

## Notes
<Optional. Preserve this section across re-runs. Put [unclear] items here if needed.>

All directories: minimum per-file detail

Even for non-leaf directories, avoid "just <role>" file entries.

Minimum requirement for every listed file:

  • Role: 1-2 sentences describing why the file exists (not just "helpers").
  • Key items: 2-6 concrete names (types/functions/constants/config keys) that help a reader know what to search for.
  • Interactions: optional 1 bullet when it materially improves navigation (e.g., "feeds updates into <other file>", "spawns tasks consumed by <module>").

Leaf directories: required detail (make it "actionable")

If a directory has files but no meaningful subdirectories, treat it as a leaf and write a deeper, navigational summary:

  • Replace "Files" one-liners with per-file mini-sections.
  • For each file, include:
    • Role (1-3 sentences: why it exists)
    • Key items (3-10 names: important types/functions/constants)
    • Interactions (how it calls/feeds other local files; mention channels/tasks/state where relevant)
    • Knobs / invariants (important config flags, thresholds, safety requirements, ordering assumptions)
  • Add a short End-to-end flow for the directory (5-12 bullets) describing how the pieces work together.

Use this leaf template (still no big snippets/excerpts):

markdown
## Files (detailed)

### `<file-a>`
- **Role**: <why it exists>
- **Key items**: `TypeA`, `TypeB`, `fn_x()`, `CONST_Y`
- **Interactions**: <uses/calls/emits/consumes; point to sibling files>
- **Knobs / invariants**: <important constraints or tuning>

### `<file-b>`
- **Role**: ...
- **Key items**: ...
- **Interactions**: ...
- **Knobs / invariants**: ...

## End-to-end flow (high level)
- <step 1: where work starts, what enters>
- <step 2: how it fans out (tasks/channels), what's computed>
- <step 3: how results are joined/ordered, what is returned/emitted>

Workflow (script-driven, bottom-up)

Use scripts to avoid manual recursion bookkeeping. The agent still writes AGENTS.md, but planning/scaffolding/verification are deterministic.

Full run

  1. Plan waves (derived only, no writes)

    • python3 scripts/agents_plan.py --root <target-root>
    • Use the bottom-up waves it prints. Within a wave, you may parallelize sibling Explore runs.
  2. Create missing stubs (create-only)

    • python3 scripts/agents_scaffold.py --root <target-root> --write
    • This creates missing DIR/AGENTS.md stubs for meaningful directories and does not modify existing AGENTS.md.
  3. Process waves deepest -> shallowest

    • For each planned directory with status missing/incomplete:
      • Run Explore (very thorough) scoped to the directory (see "Explore subagent contract").
      • Update DIR/AGENTS.md from the Explore report:
        • Preserve ## Notes.
        • Ensure "Contents (one hop) -> Subdirectories" lists all immediate subdirectories (alphabetical), with correct [ ]/[x] and explicit skip reasons where applicable.
      • Bubble the child's Explore PARENT ROLLUP into the parent's checkbox entry for child/.
  4. Verify + normalize

    • python3 scripts/agents_verify.py --root <target-root> --strict
    • python3 scripts/normalize_agents_ascii.py --root <target-root> --fail-on-remaining (or --write)
    • Optional: python3 scripts/export_agents_md.py --src <target-root> --out <output-dir>

Idempotency (safe re-runs)

If an AGENTS.md already exists:

  • Preserve any content under ## Notes.
  • Refresh "Contents (one hop)" to match the filesystem (add/remove children/files), following the same ledger-eligibility rules (always-ignored + default-pruned dependency dirs omitted unless explicitly included).
  • Do not clobber existing child rollups: keep [x] + summary text for children that still exist, unless you are intentionally updating that child (or it is now missing/invalid).
  • Avoid churn: only rewrite summaries when you found clear evidence in files or child summaries.

Update mode (incremental, only run on-demand after content changes)

Use this mode when the subtree already has AGENTS.md and you want to update only what changed (plus rollups above it).

  • Plan update set (git-derived):
    • python3 scripts/agents_plan.py --root <target-root> --mode update --base-ref <ref>
    • If you omit --base-ref, it uses working tree changes (staged + unstaged + untracked).
  • Process only the planned directories (deepest -> shallowest) using the same Explore/write/bubble rules as a full run.
  • Re-run scripts/agents_verify.py --strict to ensure rollups and ledgers are consistent.

Resume after interruption

Re-run planning and continue from the deepest remaining work:

  • python3 scripts/agents_plan.py --root <target-root>
  • Continue processing directories that are still missing/incomplete, deepest waves first.
  • Use scripts/agents_verify.py --strict as the final correctness check.

Completion criteria

You're done when:

  • Every meaningful directory in the subtree has an AGENTS.md.
  • In every AGENTS.md, the "Subdirectories" list matches the filesystem (no missing children).
  • No [TBD] remains for directories that were processed; everything is either [x] summarized or [x] (skip: <reason>).
  • The target root AGENTS.md reads like an architecture overview (components + how they connect), with details pushed down to children.
  • python3 scripts/agents_verify.py --root <target-root> --strict exits 0.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Layered Summary AI skill do?

Create hierarchical, bottom-up "layered summaries" by generating `AGENTS.md` files per directory in a subtree (e.g., `reth/crates/engine`). Deep directories summarize files and key APIs; parent directories roll up children. Also use to incrementally update an existing `AGENTS.md` subtree after content changes. No snippets; keep summaries navigational and checkable.

Why use Layered Summary on TypingMind?

Because you install it once and use it with any model. Layered Summary is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Layered Summary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vicnaum/vics-agent-skills/tree/main/skills/layered-summary. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Layered Summary?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Layered Summary?

As many as you like. As long as a model supports skills, you can use Layered Summary with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Layered Summary AI skill free?

It is published on GitHub by vicnaum. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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