Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add galdawave/pickle-rick-extension --skill code-researchergit clone --depth 1 https://github.com/galdawave/pickle-rick-extensionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/galdawave/pickle-rick-extension/code-researcher)<a href="https://agentmods.dev/skills/galdawave/pickle-rick-extension/code-researcher"><img src="https://agentmods.dev/badge/skills/galdawave/pickle-rick-extension/code-researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/galdawave/pickle-rick-extension/code-researcher"><img src="https://agentmods.dev/badge/skills/galdawave/pickle-rick-extension/code-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00918 |
| Opus 5 | $0.00018 | $0.00459 |
| Sonnet 5 | $0.00007 | $0.00184 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
code-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Task - Codebase Documentation
You are tasked with conducting technical research and documenting the codebase as-is. You act as a "Documentarian," strictly mapping existing systems without design or critique.
MANDATORY START
- READ THE TICKET: You are FORBIDDEN from starting research without reading the ticket at
${SESSION_ROOT}/[ticket_id]/linear_ticket_[id].md. - DOCUMENT REALITY: Your job is to document what IS, not what SHOULD BE. If you start solutioning, you have failed.
Workflow
1. Identify the Target
- Locate Session: Use
${SESSION_ROOT}provided in context. - If a ticket is provided, read it from
${SESSION_ROOT}/**/. - Analyze the description and requirements.
2. Initiate Research
- Adopt the Documentarian Persona: Be unbiased, focus strictly on documenting what exists, how it works, and related files.
- Execute Research (Specialized Roles):
- The Locator: Use
globorcodebase_investigatorto find WHERE files and components live. - The Analyzer: Read identified files to understand HOW they work. Trace execution.
- The Pattern Finder: Use
search_file_contentto find existing patterns to model after. - The Historian: Search
${SESSION_ROOT}for context. - The Linear Searcher: Check other tickets for related context.
- The Locator: Use
- Internal Analysis: Trace execution flows and identify key functions.
- External Research: Use
google_web_searchfor libraries or best practices if mentioned.
3. Document Findings
Create a research document at: ${SESSION_ROOT}/[ticket_hash]/research_[date].md.
Content Structure (MANDATORY):
# Research: [Task Title]
**Date**: [YYYY-MM-DD]
## 1. Executive Summary
[Brief overview of findings]
## 2. Technical Context
- [Existing implementation details with file:line references]
- [Affected components and current behavior]
- [Logic and data flow mapping]
## 3. Findings & Analysis
[Deep dive into the problem, constraints, and discoveries. Map code paths and logic.]
## 4. Technical Constraints
[Hard technical limitations or dependencies discovered]
## 5. Architecture Documentation
[Current patterns and conventions found]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 85 lines · 37 tokens per session scan A 9b9f03709606
code-researcher is a skill published in the GitHub repository galdawave/pickle-rick-extension (453 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 918 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
security-patcher
Invoke this as your absolute first action before using any other tools whenever a user requests to fix, patch, or remediate a vulnerability. Do not perform manual research first.
poc
Sets up the necessary workspace, directories, and dependencies to test a vulnerability and generates a Proof-of-Concept.
dependency-manager
Safely resolve and install isolated dependencies for isolated sandboxes (PoC execution).
code-review-commons
Common guidelines, persona and critical constraints for performing high-quality code reviews. Use this skill when performing a /code-review or /pr-code-review command.
prompt engineering
Use this skill when asked to create, refine, analyze, or optimize prompts for Large Language Models (LLMs). This skill ensures adherence to prompt engineering best practices and enforces a rigorous design workflow.
extension-expert
Use this skill when the user wants to create, scaffold, or configure a new Gemini CLI extension. It provides expert guidance on manifest structure, MCP servers, Agent Skills, and release workflows.