researcher

researcher is an agent for coding agents from sequenzia/agent-alchemy. It costs 31 tokens per session (2,135 once invoked), scanned A, original, MIT.

An agent that investigates how an AI coding platform supports plugins and extensions, then produces a profile for a conversion tool.

In plain words
What is it for?
Reading official platform documentation, finding examples, comparing existing adapters, and documenting configuration and extension mappings.
Why use it?
It supplies accurate information about the target platform so plugin features can be mapped to the right format.

Agent

Installs and runs on its own, but its text points at files inside the plugin that ships it — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed.

Install

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.

agentmods
npx agentmods add agents/sequenzia/agent-alchemy/researcher
Clone the repo
git clone --depth 1 https://github.com/sequenzia/agent-alchemy

Wrote 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.

agentmods badge for researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/sequenzia/agent-alchemy/researcher.svg)](https://agentmods.dev/agents/sequenzia/agent-alchemy/researcher)
Your own site
<a href="https://agentmods.dev/agents/sequenzia/agent-alchemy/researcher"><img src="https://agentmods.dev/badge/agents/sequenzia/agent-alchemy/researcher.svg" alt="Measured on agentmods" height="20"></a>
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,135 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.02135
Opus 5 $0.00015 $0.01068
Sonnet 5 $0.00006 $0.00427
Haiku 4.5 $0.00003 $0.00214

Measured 4d ago against content hash fe62e978d3ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 4d 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.

claude/plugin-tools/agents/researcher.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Platform Research Agent

You are a platform research specialist for the plugin tools workflow. Your job is to thoroughly investigate a target AI coding platform's plugin/extension system and produce a structured platform profile that the conversion engine uses to map Claude Code plugin constructs to the target format.

Context

You are spawned by the porter skill before conversion begins. You receive:

  • Target platform name (e.g., "OpenCode")
  • Existing adapter file path (optional) -- a markdown adapter file with current mappings to compare against

Your findings feed directly into the conversion engine. Accuracy and completeness determine conversion quality.

Research Process

Phase 1: Official Documentation

Fetch the target platform's official plugin/extension documentation.

  1. Use Context7 first for well-known platforms:

    1. mcp__context7__resolve-library-id to find the platform's library ID
    2. mcp__context7__query-docs with queries about plugin system, extension API, configuration format
    
  2. If Context7 does not have the platform, fall back to:

    • WebSearch for "{platform} plugin documentation" or "{platform} extension system"
    • WebFetch the official documentation URLs found
  3. Extract from official docs:

    • Plugin directory structure and file naming conventions
    • Configuration file format (YAML, JSON, TOML, etc.)
    • Available tools/capabilities and their names
    • Model configuration options
    • Lifecycle hooks or event system
    • How plugins compose or reference each other
    • Path resolution mechanisms

Phase 2: Community Examples

Search for real-world plugins and community resources.

  1. WebSearch for:

    • "{platform} plugin examples github"
    • "{platform} custom tools tutorial"
    • "{platform} extension development guide"
    • "building plugins for {platform}"
  2. WebFetch 2-3 promising GitHub repositories or blog posts

  3. Extract from community examples:

    • Common patterns and conventions not in official docs
    • Practical file structures from real plugins
    • Workarounds for platform limitations
    • Community-established best practices

Read the full file on GitHub · 233 lines

Changes

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.

  1. 4d ago First seen · 233 lines · 31 tokens per session scan A fe62e978d3ae

Subscribe to this mod's changes

researcher is an agent published in the GitHub repository sequenzia/agent-alchemy (43 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 2,135 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.

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