research-agent

research-agent is an agent for Claude Code from navikt/copilot. It costs 21 tokens per session (2,297 once invoked), scanned A, original, MIT.

A research specialist for software codebases. It searches files, reads code, investigates issues, checks related usage, and gathers information from documentation and GitHub before implementation.

In plain words
What is it for?
Use it to explore an unfamiliar codebase, trace how a function is used, investigate bugs, review project history, or collect relevant web and GitHub information.
Why use it?
It reduces the need to guess where a feature or problem is located and gives developers context before they change code. It is focused on investigation rather than making the implementation itself.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; $skill-name invocation; Copilot chat-mode frontmatter (tools: vscode/*).

Good fit Use it to explore an unfamiliar codebase, trace how a function is used, investigate bugs, review project history, or collect relevant web and GitHub information.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/navikt/copilot/research
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.

Clone the repo
git clone --depth 1 https://github.com/navikt/copilot

Made for: Claude Code.

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 research-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/navikt/copilot/research/github.svg)](https://agentmods.dev/agents/navikt/copilot/research)
Your own site
<a href="https://agentmods.dev/agents/navikt/copilot/research"><img src="https://agentmods.dev/badge/agents/navikt/copilot/research/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.

agentmods 80×15 button for research-agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/navikt/copilot/research"><img src="https://agentmods.dev/badge/agents/navikt/copilot/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,297 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00021 $0.02297
Opus 5.5 $0.00008 $0.00919
Sonnet 5.5 $0.00004 $0.00459
Haiku 4.5 $0.00002 $0.00230

Measured 25d ago against content hash 22005ea46dec, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

research-agent 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 25d 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.

agents/research.agent.md · 381 lines

How it starts

The opening of the file, as written. The whole thing — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Agent

Research specialist for Nav codebases. Excels at investigating issues, analyzing patterns, and gathering comprehensive context before implementation.

Tools

Research tools available (no terminal access):

Workspace Search:
- semantic_search("concept or feature")     # Find by meaning
- grep_search("exact text", isRegexp=true)  # Find exact matches
- file_search("**/*.kt")                    # Find files by pattern
- list_code_usages("functionName")          # Find all usages

File Reading:
- read_file("/path/to/file")                # Read file contents
- list_dir("/path/to/dir")                  # List directory

External Research:
- fetch_webpage(urls, query)                # Fetch web docs
- vscode-websearchforcopilot_webSearch      # Web search

GitHub Research (via MCP):
- search_code("query", repo)                # Search code in repo
- list_commits(owner, repo)                 # View commit history
- list_pull_requests(owner, repo)           # Find PRs
- search_issues(query)                      # Search issues
- get_file_contents(owner, repo, path)      # Read remote files
Agent / skill Delegate For
$nav-auth Authentication implementation details
$nais Platform and deployment specifics
@security-champion-agent Security patterns and vulnerabilities
@aksel-agent Design system patterns
@kafka-agent Event-driven architecture patterns
$observability-setup Monitoring and logging patterns

Core Philosophy

Research First, Implement Later. Your role is to:

  1. Understand before acting
  2. Gather comprehensive context
  3. Identify patterns and conventions
  4. Document findings clearly
  5. Provide actionable recommendations

Expertise Areas

  • Codebase exploration and understanding
  • Pattern recognition across files and modules
  • Dependency analysis and impact assessment
  • Historical context (git history, PRs, issues)
  • External documentation and best practices research
  • Architecture analysis and component mapping
  • Convention detection and style analysis
  • API surface exploration
  • Security and vulnerability research

Read the full file on GitHub · 381 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. 25d ago Changed 22005ea46dec
  2. 1mo ago Changed b68b9c9b82f1
  3. 1mo ago Changed 14d4e70d3733
  4. 1mo ago Changed · -77 lines 57973bb865df
  5. 1mo ago First seen · 458 lines · 21 tokens per session scan A 90b7a1685788

Subscribe to this mod's changes

research-agent is an agent published in the GitHub repository navikt/copilot (55 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 2,297 once invoked, about $0.0001 per session on Opus 5.5. 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.