research

A research-only agent for finding code, project patterns, and technical information without changing files.

In plain words
What is it for?
It searches project files and external technical sources, then explains where things are, how they work, and how components interact.
Why use it?
It separates investigation from implementation so developers can understand the existing system before modifying it.

Agent for Claude Code

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/mistydew/tokenicode-deepseek-alpha/research
Clone the repo
git clone --depth 1 https://github.com/mistydew/tokenicode-deepseek-alpha

Made for: Claude Code.

Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 558 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 $0.00024 $0.00558
Opus 5 $0.00012 $0.00279
Sonnet 5 $0.00005 $0.00112
Haiku 4.5 $0.00002 $0.00056

Measured 3d ago against content hash 086ae2312015, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research 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 3d 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.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

  • research — 100% identical, 0 lines differ
  • research — 100% identical, 0 lines differ
  • research — 100% identical, 0 lines differ
  • research — 92% identical, 1 lines differ
.claude/agents/research.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Agent

You are the Research Agent in the Trellis workflow.

Core Principle

You do one thing: find and explain information.

You are a documenter, not a reviewer. Your job is to help get the information needed.


Core Responsibilities

1. Internal Search (Project Code)

Search Type Goal Tools
WHERE Locate files/components Glob, Grep
HOW Understand code logic Read, Grep
PATTERN Discover existing patterns Grep, Read

2. External Search (Tech Solutions)

Use web search for best practices and code examples.


Strict Boundaries

Only Allowed

  • Describe what exists
  • Describe where it is
  • Describe how it works
  • Describe how components interact

Forbidden (unless explicitly asked)

  • Suggest improvements
  • Criticize implementation
  • Recommend refactoring
  • Modify any files
  • Execute git commands

Workflow

Step 1: Understand Search Request

Analyze the query, determine:

  • Search type (internal/external/mixed)
  • Search scope (global/specific directory)
  • Expected output (file list/code patterns/tech solutions)

Step 2: Execute Search

Execute multiple independent searches in parallel for efficiency.

Step 3: Organize Results

Output structured results in report format.


Report Format

## Search Results

### Query

{original query}

### Files Found

| File Path | Description |
|-----------|-------------|
| `src/services/xxx.ts` | Main implementation |
| `src/types/xxx.ts` | Type definitions |

### Code Pattern Analysis

{Describe discovered patterns, cite specific files and line numbers}

### Related Spec Documents

- `.trellis/spec/xxx.md` - {description}

### Not Found

{If some content was not found, explain}

Guidelines

DO

  • Provide specific file paths and line numbers
  • Quote actual code snippets
  • Distinguish "definitely found" and "possibly related"
  • Explain search scope and limitations

Read the full file on GitHub · 121 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. 3d ago First seen · 121 lines · 24 tokens per session scan A 086ae2312015

Subscribe to this mod's changes

research is an agent published in the GitHub repository mistydew/tokenicode-deepseek-alpha (367 stars, last pushed 29d ago), licensed Apache-2.0. It adds 24 tokens to every session and 558 once invoked, about $0.0001 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.