mcpbeat

Shadow Frog

microsoft/shadow-frog

>- Use a shadow knowledge base to understand any codebase. The .shadow/ directory mirrors the source tree with markdown files containing behavioral insights — known bugs, edge cases, implicit contracts, and user preferences. Always check the shadow before editing, debugging, or investigating code. When the user shares important context, write it to the shadow immediately. Invoke shadow-frog-init to create it, shadow-frog-update to refresh it, shadow-frog-dream for autonomous exploration, shadow-frog-meditate for shadow hygiene, or shadow-frog-viewer to browse it.

4k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
17
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/microsoft/ShadowFrog --skill shadow-frog

The instruction itself

17 sections, as written by the author

ShadowFrog

.shadow/ mirrors the source tree. Each source file has a .md shadow organized

by symbol. Each symbol section contains discoveries — behavioral insights anchored

to that code location.

Required Actions

Every time you work on code in a repo with .shadow/:

  • Read _prefs.md first — it contains project-wide conventions,

user preferences, and things the user explicitly wants to avoid.

Violating a preference wastes the user's time.

  • Read _cross/ discoveries — these are the highest-value findings,

spanning multiple files. List _cross/ and read any files whose titles

relate to the area you're working in. Cross-cutting discoveries reveal

hidden contracts, interaction bugs, and design patterns that per-file

shadows alone cannot capture.

  • Check _dreams/ for experiment results_dreams/_index.md lists

autonomous exploration experiments. Read reports relevant to your task —

they contain verified bug analyses, attempted fixes, and architectural

insights. Dreams may contain knowledge not yet distilled into per-file

shadows, so always check when investigating a bug or unfamiliar area.

  • Before editing any file: read its shadow (.shadow/<path>.md),

check _cross/ for cross-cutting discoveries about it, and apply

what you learn. The shadow contains known bugs, edge cases, and

implicit contracts discovered by previous sessions.

Note: _index.md discovery counts may be stale — always check

per-file shadows and _cross/ directly rather than relying solely on

the index summary.

  • When the user explains something about code (gotcha, design intent,

warning, history): write a source: user discovery to the shadow

immediately. Do not ask where to put it — resolve the file::symbol

anchor yourself by searching _index.md, shadow files, and session

context (current file, recent edits).

  • When the user states a preference or convention (not tied to any

specific file): write it to _prefs.md immediately.

  • After code changes: run /shadow-frog-update

Directory Layout

.shadow/
  .shadowignore      Gitignore-syntax file for excluding paths from the shadow
  _index.md          File list with symbol counts and discovery counts
  _prefs.md          Project-wide user preferences (not tied to any file/symbol)
  _cross/            Cross-cutting discoveries (span multiple files)
    <slug>.md        One file per cross-cutting discovery (descriptive kebab-case name)
  _meta/
    state.json       Last commit, timestamps, counts
  _dreams/           Dream experiment archive (detailed reports + diffs)
    _index.md        Table of all experiments with verdicts
    <YYYYMMDD-HHMMSSZ-slug>/      One folder per experiment
      report.md      Structured report with YAML frontmatter
      patch.diff     Full implementation diff against base_commit
  <mirrored tree>/   Per-file shadows
    file.py.md       Organized by symbol

Reference Notation

Canonical format: file_path::symbol_name

Examples: src/auth.py::authenticate_user, src/auth.py::UserAuth.validate,

src/auth.py (file-level, no symbol)

The symbol name is the stable anchor.

Per-File Shadow Format

# Shadow: src/auth.py

**Language**: Python | **Lines**: 142 | **Last modified**: 2025-01-15

## File-Level

- This module has no __all__ — all top-level names are public.
  _(verified, source: exploration)_

## `class UserAuth`

### `UserAuth.validate`

- Catches ALL exceptions and returns False — swallows
  connection errors, making network failures look like invalid tokens.
  _(verified, source: exploration)_

## `authenticate_user`

- Silently returns None on expired tokens. Callers must check.
  _(verified, source: exploration, labels: [bug])_
  Also involves: `src/middleware.py::require_auth`

## Cross-References

- [db-connection-lifecycle](../_cross/db-connection-lifecycle.md)
  (involves `src/db/connection.py::ConnectionPool`, `src/api/routes.py::get_user`)

Heading format (hard rule — parsers depend on this):

  • Top-level symbols (classes, functions, constants): ## heading with symbol in backticks
  • Nested symbols (methods): ### heading with symbol in backticks
  • ## Cross-References — always last section

The viewer parser only matches the backtick form. A heading written as

### UserAuth.validate (no backticks) will have its discoveries

silently dropped from search/top output. Always wrap the symbol in

backticks, including for nested symbols.

Examples:

## `authenticate_user`
## `class UserAuth`
### `UserAuth.validate`

Cross-Cutting File Format (_cross/<slug>.md)

# Database connection lifecycle

**Category**: pattern
**Refs**:
- `src/db/connection.py::ConnectionPool.get`
- `src/auth.py::authenticate_user`
- `src/api/routes.py::get_user`

**Discovery**: All database access goes through a connection pool that
silently reconnects on failure. First request after DB restart is slow (~2s).

_(verified, source: exploration)_

Preferences File (_prefs.md)

Project-wide user preferences and conventions that are not tied to any

specific file or symbol. These guide all agent work across the codebase.

# Preferences

- No backward compatibility — only keep the latest code, no shims or aliases.
  _(source: user)_

- Use snake_case for all Python function and variable names.
  _(source: user)_

- Prefer small, focused PRs over large sweeping changes.
  _(source: interaction)_

Format:

- <preference or convention>
  _(source: <user|interaction>)_

Preferences are always trusted (same rank as source: user). They don't

need verified/uncertain/refuted — if the user said it, it's a directive.

When to write to _prefs.md vs per-file shadow vs _cross/:

  • Applies to the whole repo, no specific file → _prefs.md
  • Applies to a specific file or symbol → per-file shadow
  • Applies to 3+ specific files → _cross/<slug>.md

Discovery Format

Per-file discoveries (no IDs — anchored by their file::symbol heading):

- <behavioral statement>
  _(<verified|uncertain|refuted>, source: <exploration|user|interaction>)_
  Also involves: `file::symbol`, `file::symbol`

With labels (optional — only when the discovery is actionable):

- <behavioral statement>
  _(<verified|uncertain|refuted>, source: <exploration|user|interaction>, labels: [bug, security])_
  Also involves: `file::symbol`

With dream report link (optional — only for experiment-derived discoveries):

- <behavioral statement>
  _(<verified|uncertain|refuted>, source: <exploration|user|interaction>)_
  Dream report: `_dreams/<dream-id>/`

Cross-cutting discoveries (one per _cross/<slug>.md file):

# <Title>

**Category**: <category>
**Refs**:
- `file::symbol`

**Discovery**: <behavioral statement>

_(<verified|uncertain|refuted>, source: <exploration|user|interaction>)_

Slug naming: use descriptive kebab-case derived from the title.

Example: title "Database connection lifecycle" → filename db-connection-lifecycle.md

Labels

Labels mark actionable discoveries so agents can quickly scan for specific

types. Most discoveries are just knowledge — labels are only for findings

that call for action.

| Label | Use when |

|-------|----------|

| bug | A defect that should be fixed |

| performance | A bottleneck or inefficiency |

| security | A vulnerability or unsafe pattern |

| feature-gap | Missing functionality or improvement opportunity |

| tech-debt | Code smell, duplication, refactoring opportunity |

A discovery can have multiple labels: labels: [bug, security].

Omit labels entirely for pure observational knowledge.

Labels go in the metadata line:

_(verified, source: exploration, labels: [bug])_

Cross-cutting discoveries can also have labels — add them to the metadata line.

Fields

  • verified|uncertain|refuted — verification status
  • source: exploration — agent discovered via code analysis
  • source: user — human stated it in conversation
  • source: interaction — emerged from collaborative work (debugging, refactoring)
  • labels: [...] — optional, actionable labels (see table above)
  • Also involves:file::symbol refs to other code locations (required if discovery touches other files)
  • Dream report: — optional, _dreams/<dream-id>/ link for experiment-derived discoveries
  • Category (cross-cutting only): pattern, behavior, edge-case, contract, performance, intent, warning, history, convention

Trust Order

  • source: user — highest trust, always verified
  • source: interaction — always verified
  • verified from exploration
  • uncertain — not yet confirmed
  • refuted — skip
  • File mapping: src/auth.py.shadow/src/auth.py.md
  • Symbol anchoring: every source symbol has a ##/### heading in its shadow
  • Also involves: per-file discoveries list other file::symbol locations
  • Cross-ref back-pointers: per-file ## Cross-References links to _cross/<slug>.md entries
  • Cross-cutting refs: _cross/<slug>.md Refs: lists all involved file::symbol locations

Links 4 and 5 are bidirectional: if _cross/db-connection-lifecycle.md references

src/auth.py::fn, then src/auth.py.md must list it in ## Cross-References, and vice versa.

Seven Invariants

  • Every included source file has exactly one shadow at .shadow/<path>.md
  • Every symbol in source has a ##/### heading in its shadow
  • Per-file discoveries touching other files have Also involves: with file::symbol
  • Cross-ref back-pointers match: _cross/<slug>.md refs ↔ per-file ## Cross-References
  • Every entry in ## Cross-References has a corresponding _cross/<slug>.md file
  • Cross-cutting filenames are unique (enforced by filesystem)
  • No duplicate discoveries (same behavioral claim at same symbol)

To audit a shadow for structural drift (invariant 3 format, invariants 4–5,

plus enum and heading-format guards), locate the viewer script and run it:

VIEWER=""
for DIR in .github/skills/shadow-frog-viewer .claude/skills/shadow-frog-viewer; do
    [ -f "$DIR/shadow-viewer.py" ] && VIEWER="$DIR/shadow-viewer.py" && break
done
python3 "$VIEWER" --check-invariants

Exits 0 if clean, 1 with one violation per line otherwise. Invariant 3 is

checked for anchor *format* only (not existence of the referenced file or

symbol); invariants 1, 2, and 7 require source parsing / semantic match and

are not statically checked; invariant 6 is filesystem-enforced.

Lookup Commands

# File's shadow
cat .shadow/src/auth.py.md

# Specific symbol's knowledge
grep -A 20 "## \`authenticate_user\`" .shadow/src/auth.py.md

# Cross-cutting discoveries for a file
grep -rl "src/auth.py::" .shadow/_cross/

# Search by topic
grep -rl "error.handling\|exception" .shadow/ --include="*.md"

# All user-shared knowledge
grep -r "source: user" .shadow/ --include="*.md"

# Project-wide preferences
cat .shadow/_prefs.md

# List all cross-cutting discovery files
ls .shadow/_cross/

Verification

Two methods, use whichever fits the claim:

Observe-based (for simpler claims — code reading suffices):

  • Read the source code at the relevant file::symbol
  • Trace the logic: does the behavioral claim hold?
  • If confirmed → verified. If contradicted → refuted. If unclear → uncertain.

Do-based (for harder claims — requires execution):

  • Write a short verification script (test, assertion, or probe) that would

confirm or refute the claim

  • Run it
  • Based on the result → verified or refuted

Prefer do-based for claims about runtime behavior, performance, error handling

paths, or race conditions. Prefer observe-based for claims about code structure,

types, or static properties.

Dedup and Writing Rules

Before writing any discovery, follow this procedure:

  • Read before write: Read all existing discoveries under the target

file::symbol. If an existing discovery makes the same behavioral

claim (even if worded differently) → update the existing one. If the

new one extends an existing one → merge into a single richer entry.

If they conflict → investigate the code, keep the correct one, mark

the other refuted.

  • Append, don't replace: If the symbol already has discoveries,

append your new one after them. If there is a _No discoveries yet._

placeholder, remove it and write your discovery. Never use the

placeholder as an edit anchor if it's already gone — read the file first.

  • Write in canonical format (see Discovery Format above)
  • Fix bad format: if you see any existing content that doesn't

follow the canonical format, fix it in place

For cross-cutting, search _cross/ for overlapping Refs: sets

before creating a new entry. Only create _cross/<slug>.md for

discoveries spanning 3+ files — otherwise use per-file entries with

Also involves: references.

  • /shadow-frog-init — create .shadow/ for a new repo
  • /shadow-frog-update — refresh shadows after changes or from conversation
  • /shadow-frog-dream — autonomous exploration and experimentation while user is AFK
  • /shadow-frog-meditate — deduplicate, merge, and resolve conflicting discoveries
  • /shadow-frog-viewer — browse and query the shadow (overview, search, preferences, recent)

How to use it

Copy the folder

Take microsoft/shadow-frog from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.