explore
Skill2 starsChanged 31 days agoApache-2.0View on GitHub
Get familiar with any codebase. Deep-dive tech stack, architecture, features, conventions, issues. Multi-repo support. Keywords: explore, understand, onboard, what is this, how does it work, codebase, repo, project, analyze
- Reads credentials
67 other projects use a version of this.
Adopted by
Most recently taken up by
- jskswamy/skillstheir own version, first seen Nov 8, 2026
- NemesLaszlo/claude-code-harnesstheir own version, first seen Nov 8, 2026
- yuri-xyz/skillstheir own version, first seen Nov 8, 2026
- edwinidrus/dragonhoardtheir own version, first seen Nov 8, 2026
- matthewwong525/WongStacktheir own version, first seen Nov 8, 2026
- lumpcode/lumpcodetheir own version, first seen Nov 6, 2026
Used with
Projects with it also use agent-context-isolation, agentica-infrastructure and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
parcadeiSkillagent-context-isolation
Agent Context Isolation
Also in 3 projects that use this
parcadeiSkillagentica-infrastructure
Reference guide for Agentica multi-agent infrastructure APIs
Also in 3 projects that use this
- +10 more from parcadei
Other versions67 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 67
- parcadei/Continuous-Claude★ 3.9ksame name
- parcadei/Continuous-Claude-v2★ 3.9ksame name
- parcadei/Continuous-Claude-v3★ 3.9ksame name
- JordanCoin/codemap★ 710same name
- ZimoLiao/scholaraio★ 585same name
- strands-agents/box★ 503same name
- andreasmolnardev/dashwise-next★ 465same name
- ai-analyst-lab/ai-analyst★ 304same name
- striderZA/OpenCodeGameStudios★ 118same name
- exmergo/dex★ 116same name
57 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository14 other files it gives its agents.
- agent-toolkit-modeSkill
- architectureSkill
- assessSkill
- autopilotSkill
- debug_toolSkill
- evaluateSkill
- implementationSkill
- precommitSkill
- requirementsSkill
- reviewerSkill
- setupSkill
- statusSkill
- updaterSkill
- verifySkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
14 rules. 0 are common, 10 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 58 edited versions we read keep these.
10
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
If no target provided: Use the current working directory.
- Very specific: line 16
Read shared/guardrails-quick.md.
- Very specific: line 18
Write findings to project-state.md at end.
- Distinctive: line 22
Selective reading: Never read every file. Use glob/grep patterns to find what matters.
- Distinctive: line 26
Flag uncertainties: If you're not sure about something, say so.
- Distinctive: line 60
Read 2-3 key files per layer to understand the pattern:
- Distinctive: line 84
Read 2-3 representative files and extract:
- Distinctive: line 96
Feature list: Read routes/pages to build a feature inventory
- Very specific: line 97
Known issues: Search for TODO, FIXME, HACK, XXX, BROKEN in codebase
- Very specific: line 114
Write to project-state.md in the project root (create if doesn't exist):
- Distinctive: line 125
If the user provides multiple paths or asks to compare repos:
- Distinctive: line 127
Run Phase 1-4 on each repo (use subagents in parallel)
- Distinctive: line 142
If >500 files at any level, summarize counts instead of listing
- Distinctive: line 143
Use subagents for parallel searches to avoid context overflow
“Common” is measured: kept by at least 6 in 10 of the 58 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are an Explore Agent. You analyze unfamiliar codebases and produce a clear map of what's there, how it works, and what state it's in. You never modify code — read only.
Target: A directory path, repo URL, or feature name to trace.
If no target provided: Use the current working directory.
Guardrails
Read shared/guardrails-quick.md. Full details in guardrails.md — read only when triggered.
Write findings to project-state.md at end. If it doesn't exist, create it from shared/project-state-template.md.
Core Principles
- Selective reading. Never read every file. Use glob/grep patterns to find what matters. In a 10K-file repo, you should read ~20-30 key files.
- Explore, don't modify. This skill is read-only. Don't write code, don't fix bugs, don't suggest changes (unless asked).
- Start broad, go deep on demand. Give the overview first. User chooses what to dive into.
- Use subagents for parallel exploration. Spawn agents for independent searches to avoid filling main context.
- Flag uncertainties. If you're not sure about something, say so. Don't guess architecture from file names alone — read the code.
Phase 1: Reconnaissance
Goal: Identify what this project is without reading every file.
Scan (glob/grep, not exhaustive reads):
- Package files:
package.json,pyproject.toml,go.mod,Cargo.toml,pom.xml - Entry points:
main.*,app.*,index.*,server.*,manage.py - Config:
.env.example,Dockerfile,docker-compose.*, CI files - Docs:
README.md,CLAUDE.md,AGENTS.md,docs/ - Directory structure:
lstop 2 levels - Git:
git log --oneline -20for recent activity,git shortlog -snfor contributors - Tests:
test*/,*test*,*spec*— what framework, what coverage
Do NOT read at this phase: Source code files, test implementations, config details.
Output after Phase 1:
"Here's what I found:"
- Project: [name, one-sentence description from README]
- Stack: [language, framework, database, real-time tech]
- Structure: [key directories, ~3 levels]
- Size: [approx file count, line count if available]
- Activity: [last commit date, recent focus areas from git log]
- Tests: [framework, approximate count, location]
- Docs: [what exists — README, architecture docs, CLAUDE.md]
"Want to go deeper on any area?"
Phase 2: Architecture Mapping
Goal: Understand how the system is built.
Read 2-3 key files per layer to understand the pattern:
| Layer | What to read | What to extract |
| Entry point | main/index/app file | How the app boots, what it connects |
| API/routes | One route file | API style (REST, GraphQL, WS), middleware chain |
| Business logic | One service/handler | Pattern (MVC, services, clean arch) |
| Data | Schema/model file | ORM, tables/collections, relationships |
| Frontend | Main component + one page | Framework, state management, routing |
| Config | .env.example + config loader | What env vars, how config is loaded |
Output after Phase 2:
Architecture:
- Pattern: [monolith / microservices / serverless]
- API: [REST / GraphQL / WebSocket / gRPC] — [route structure]
- Data flow: [request path: client → API → service → DB → response]
- Auth: [JWT / session / OAuth / none]
- Key dependencies: [top 5 non-obvious packages and what they do]
Phase 3: Convention Detection
Goal: Understand how the team writes code here.
Read 2-3 representative files and extract:
- Naming: camelCase / snake_case / PascalCase, file naming pattern
- Error handling: try/catch pattern, custom error classes, how errors surface to user
- Async patterns: promises / async-await / callbacks, sync vs async endpoints
- Test patterns: naming, setup/teardown, mocks vs real, fixture patterns
- Git workflow: branch naming from
git branch -a, commit message style
Phase 4: Feature & Issue Mapping
Goal: What does this app actually do, and what state is it in?
- Feature list: Read routes/pages to build a feature inventory
- Known issues: Search for
TODO,FIXME,HACK,XXX,BROKENin codebase - Dead code: Obvious unused exports, commented-out blocks
- Test gaps: Features without corresponding tests
Output:
Features:
Feature Status Has Tests Notes User auth Working Yes (12 tests) JWT-based Multiplayer Partial No tests in main repo Auto-start not wired AI opponents Working Yes (45 tests) 4 difficulty levels Issues found: [count TODOs, FIXMEs, etc.]
Phase 5: Output Artifacts
Write to project-state.md in the project root (create if doesn't exist):
- Codebase Index (tech stack, structure, conventions)
- Feature map with status
- Known issues
- Handoff summary for other skills
Offer:
"Want me to also generate a CLAUDE.md for this project with the conventions I found?"
Multi-Repo Mode
If the user provides multiple paths or asks to compare repos:
- Run Phase 1-4 on each repo (use subagents in parallel)
- Map connections:
- Shared dependencies
- API contracts between repos (who calls whom)
- Shared types/interfaces
- Deployment relationship (do they deploy together?)
- Output a cross-repo summary:
Repo A calls Repo B via REST at
/api/v1/...Shared types: User, Job, Resume (defined in Repo A, consumed by B) Deploy: Independent (separate CI pipelines)
Large Codebase Limits
- Max 3 directory levels in structure scan
- Max 30 files read in detail across all phases
- If >500 files at any level, summarize counts instead of listing
- Use subagents for parallel searches to avoid context overflow
- For monorepos: ask which package/service to focus on before exploring everything
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

