GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
日本語の概要は準備中です。原文の説明を表示しています。
Discovers and indexes Python code in skills, enabling cross-skill imports. Use when importing functions from other skills or analyzing skill codebases.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Discover Python code across skills and enable universal imports. Solves the dash-underscore naming mismatch between skill directories (e.g., browsing-bluesky) and Python imports (e.g., browsing_bluesky).
import sys
sys.path.insert(0, '/home/user/claude-skills')
from inspecting_skills import setup_skill_path, skill_import
from inspecting_skills import skill_import
# Import by skill name (dash or underscore form)
bsky = skill_import("browsing-bluesky")
posts = bsky.search_posts("python")
# Import specific functions
search, profile = skill_import("browsing-bluesky", ["search_posts", "get_profile"])
from inspecting_skills import setup_skill_path
# Configure once at session start
setup_skill_path("/home/user/claude-skills")
# Now import skills directly (underscore form)
from browsing_bluesky import search_posts, get_profile
from remembering import remember, recall
from inspecting_skills import list_importable_skills
skills = list_importable_skills()
for s in skills:
print(f"{s['name']} -> import {s['module_name']}")
| Function | Purpose |
|---|---|
discover_skill(path) | Analyze a single skill directory |
discover_all_skills(root) | Find all skills with Python code |
find_skill_by_name(name, root) | Find skill by name (either form) |
skill_name_to_module(name) | Convert "browsing-bluesky" to "browsing_bluesky" |
| Function | Purpose |
|---|---|
index_skill(layout) | Extract symbols from a discovered skill |
index_all_skills(root) | Index all skills in repository |
generate_registry(root, output) | Create registry.json manifest |
| Function | Purpose |
|---|---|
setup_skill_path(root) | Enable transparent skill imports |
skill_import(name, symbols) | Import skill or specific symbols |
register_skill(name, path) | Register skill at custom path |
list_importable_skills() | List all importable skills |
Skills organize Python code in three patterns:
browsing-bluesky/
SKILL.md
__init__.py # Re-exports from scripts/
scripts/
__init__.py
bsky.py # Main implementation
remembering/
SKILL.md
__init__.py # Re-exports functions
memory.py # Core functionality
boot.py
config.py
simple-skill/
SKILL.md
__init__.py # Contains all code
Create a registry.json for offline symbol lookup:
from inspecting_skills import generate_registry
from pathlib import Path
registry = generate_registry(
Path("/home/user/claude-skills"),
output_path=Path("registry.json")
)
# Registry structure:
# {
# "version": "1.0.0",
# "skills": {
# "browsing-bluesky": {
# "module_name": "browsing_bluesky",
# "exports": ["search_posts", "get_profile", ...],
# "modules": [...]
# }
# }
# }
from inspecting_skills import discover_skill, index_skill
from pathlib import Path
# Discover the skill layout
layout = discover_skill(Path("/home/user/claude-skills/remembering"))
print(f"Layout: {layout.layout_type}")
print(f"Has __init__.py: {layout.has_init}")
print(f"Python files: {[f.name for f in layout.python_files]}")
# Index symbols
index = index_skill(layout)
for module in index.modules:
print(f"\n{module.file_path}:")
for sym in module.symbols:
print(f" {sym.kind} {sym.name}{sym.signature or ''}")
This skill complements tree-sitting, which extracts code structure at runtime:
Use both together:
tree-sitting for navigation and code reviewinspecting-skills for actual code imports and execution# If skill_import fails, check:
# 1. Skill exists and has __init__.py
from inspecting_skills import discover_skill
layout = discover_skill(Path("/path/to/skill"))
print(layout.has_init) # Must be True for importing
# 2. Skills root is configured
from inspecting_skills import get_skills_root
print(get_skills_root())
# 3. Symbol is exported in __all__
import ast
init_code = open("/path/to/skill/__init__.py").read()
# Check for __all__ definition
# Manually set skills root
from inspecting_skills import set_skills_root
set_skills_root("/home/user/claude-skills")
@dataclass
class SkillLayout:
name: str # "browsing-bluesky"
path: Path # Full path to skill directory
layout_type: str # "scripts" | "root" | "package" | "none"
python_files: list[Path]
has_init: bool # Can be imported as package
entry_module: str # "browsing_bluesky"
@dataclass
class SkillIndex:
name: str # "browsing-bluesky"
module_name: str # "browsing_bluesky"
layout_type: str
modules: list[ModuleIndex]
exports: list[str] # From __all__
@dataclass
class Symbol:
name: str # Function/class name
kind: str # "function" | "class" | "method"
signature: str | None # "(self, x: int)"
line: int | None # 1-indexed
docstring: str | None # First line
children: list[Symbol] # Methods for classes
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
日本語の概要は準備中です。原文の説明を表示しています。
Decide which model, effort level, and cascade shape each subagent gets, and how to keep improvement loops safe (evaluator-as-selector, stop on regression). Routes on measured cost-per-completed-task rather than per-token price, because a tier's token count varies more by task shape than price varies across tiers. Covers per-model effort semantics, the concision lever, cascade preconditions, context handoff, and watching a subagent fan-out live. Use when choosing a subagent's model or effort, when choosing how to escalate a failed attempt, or when asked which model or effort a task should get. Grounded in a 2026-07 calibration, a 2026-08 coding-cost study, a 2026-09 seeded-bug repair battery, a 2026-10 Haiku 5.5 ladder priced per spawn, and a 2026-10 retry-versus-escalation ladder on 295 SWE-bench Verified tasks; Managed Agents API specifics are operational, not calibrated.
日本語の概要は準備中です。原文の説明を表示しています。
Securely manages API credentials for multiple providers (Anthropic Claude, Google Gemini, GitHub). Use when skills need to access stored API keys for external service invocations.
日本語の概要は準備中です。原文の説明を表示しています。
Guidance for asking clarifying questions when user requests are ambiguous, have multiple valid approaches, or require critical decisions. Use when implementation choices exist that could significantly affect outcomes.
日本語の概要は準備中です。原文の説明を表示しています。
Pre-change blast-radius report for a symbol or file. Walks tree-sitting references, augments with a plain-text scan over non-parsed files (configs, plain docs), and clusters affected sites by feature (`_FEATURES.md`) or top-level package. Use when about to refactor, rename, or delete something in a repo you don't own — "what breaks if I change `validateUser`", "who calls this", "is this safe to remove", "where is this used", "blast radius", "impact analysis". This is the CONVERGENT pre-change risk skill — for "what is this repo?" use exploring-codebases; for "where is X?" use searching-codebases.
日本語の概要は準備中です。原文の説明を表示しています。
Read Bluesky/ATProto without depending on Bluesky's AppView — interactions on a user's posts, thread replies, any repo's records, network-wide backlinks across every lexicon, an account's handle and PDS history, which collections are active network-wide, and layer-by-layer outage diagnosis. Use when bsky.app or the AppView is down or slow, when a Bluesky read returns timeouts or 5xx, when asked who liked/replied/quoted/reposted something, when pulling live Bluesky context cheaply, when reading records straight from a PDS, when asked who references a record or account anywhere on the network, whether an account has changed handle or migrated servers, or which lexicons and non-Bluesky apps are active on atproto. Complements browsing-bluesky, which routes everything through the AppView and fails when it does.
日本語の概要は準備中です。原文の説明を表示しています。