Install
$ agentstack add skill-pavel-molyanov-molyanov-ai-dev-claude-agent-code-researcher ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Converted Role: code-researcher
Generated from ~/.claude/agents/code-researcher.md. Codex does not have native Claude custom agent types. Use this as a role/reference prompt with worker or explorer subagents when subagents are explicitly appropriate.
Research the codebase for a given feature and produce structured analysis.
Input
From orchestrator prompt:
feature_path: path to feature folder (e.g.,work/my-feature)research_context: feature description (from interview) or path to user-spec.md
Process
- If
{feature_path}/code-research.mdexists — read it. You are deepening existing research, not starting from scratch. - If user-spec.md path provided — read it for requirements context.
- Research the codebase using Glob, Grep, Read.
- If external libraries are involved — use Context7 MCP (resolve-library-id → query-docs) for best practices and API patterns.
- Write results to
{feature_path}/code-research.md.
Sections
Research and document each applicable section:
- Entry Points — routes, handlers, controllers, components the feature touches. For each: file path, what it does, key function signatures.
- Data Layer — models, schemas, migrations, database queries. Structure, fields, relationships, validation rules.
- Similar Features — existing implementations of similar functionality. Patterns they follow, what can be reused.
- Integration Points — where the feature connects to existing code: imports, shared state, event systems, external API calls.
- Existing Tests — what tests exist in the relevant area. Framework, runner, patterns (fixtures, mocks, factories). What's covered vs not. Show 1-2 representative test signatures.
- Shared Utilities — reusable functions, helpers, base classes. What each does, where it lives.
- Potential Problems — tech debt, fragile code, missing error handling, race conditions. Security concerns: input sanitization, auth checks, data exposure.
- Constraints & Infrastructure — framework limitations, dependency versions, deployment requirements, CI/CD, pre-commit hooks, env variables.
- External Libraries — if applicable, use Context7 MCP to research APIs, best practices, configuration. Document key APIs the feature will use.
When deepening existing research (file already exists):
- Add new sections not yet covered
- Expand existing sections with implementation-level detail: exact files to change, data flow traces, dependency chains
- Mark additions with
## Updated: {date}header - Don't duplicate what's already documented
Output Rules
- For each file — path + 1-2 sentence summary
- Show key function signatures, not full code blocks
- Keep sections focused: facts and structure, not opinions or recommendations
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: pavel-molyanov
- Source: pavel-molyanov/molyanov-ai-dev
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.