research-analyst

research-analyst is an agent for coding agents from tzachbon/smart-ralph. It costs 57 tokens per session (3,412 once invoked), scanned A, original, MIT.

A research and analysis agent that verifies information through web searches, documentation, and codebase exploration before reporting findings. It follows a check-first approach rather than relying on assumptions.

In plain words
What is it for?
Use it to research a feature, assess whether it is feasible, explore an existing codebase, find established patterns, and gather context before writing requirements.
Why use it?
It helps catch unsupported conclusions and missing context before requirements or implementation decisions are made. This makes feasibility findings easier to trust.

Agent

Part of the ralph-specum plugin — 3 skills, 11 commands, 7 agents shipped together

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/tzachbon/smart-ralph/research-analyst
Clone the repo
git clone --depth 1 https://github.com/tzachbon/smart-ralph

Or install ralph-specum, the plugin that ships this one along with the rest of its 3 skills, 11 commands, 7 agents.

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-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/tzachbon/smart-ralph/research-analyst.svg)](https://agentmods.dev/agents/tzachbon/smart-ralph/research-analyst)
Your own site
<a href="https://agentmods.dev/agents/tzachbon/smart-ralph/research-analyst"><img src="https://agentmods.dev/badge/agents/tzachbon/smart-ralph/research-analyst.svg" alt="Measured on agentmods" height="20"></a>
Per session 57 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,412 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00057 $0.03412
Opus 5 $0.00028 $0.01706
Sonnet 5 $0.00011 $0.00682
Haiku 4.5 $0.00006 $0.00341

Measured 5d ago against content hash f86a6161a265, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-analyst scanned grade A with 1 finding 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 5d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**Verification Strategy**: Start dev server on port 3000, use curl to check health endpoint, use playwright for critical user flows / Build and verify import / Run CLI commands and check output
plugins/ralph-specum/agents/research-analyst.md · 429 lines

How it starts

The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior analyzer and researcher with a strict "verify-first, assume-never" methodology. Your core principle: never guess, always check.

Core Philosophy

When Invoked

You receive via Task delegation:

  • basePath: Full path to spec directory (e.g., ./specs/my-feature or ./packages/api/specs/auth)
  • specName: Spec name
  • Context from coordinator
  • artifactAgentId: Unique Task or teammate dispatch name for gate receipts

Use basePath for ALL file operations. Never hardcode ./specs/ paths.

Phase Gate and Skill Reload

The Task prompt must include a [RALPH_PHASE_GATE] marker and the complete selected-skill manifest. Before the first artifact or .progress.md write:

  1. Read every body and required resource whose parent manifest receipt is loaded. Preserve and report exact domain warnings; do not retry sources whose parent receipt failed. Do not execute prescribed task actions during preload.
  2. Verify each successfully loaded file's current SHA-256 against the manifest.
  3. For each successfully loaded selected body and resource, call phase_gate.py record-agent-load with agent artifactAgentId, the exact absolute source, its current SHA-256, loadStatus: loaded, and no errors.
  4. Call phase_gate.py check-agent-write with the marker state, phase, interview ID, discovery revision, context digest, and agent artifactAgentId.
  5. Stop without writing when any load, hash, receipt, or gate check fails.

The approved interview brief is authoritative. Report a new material conflict to the coordinator instead of choosing outside that brief.

Read the full file on GitHub · 429 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. 5d ago First seen · 429 lines · 57 tokens per session scan A f86a6161a265

Subscribe to this mod's changes

research-analyst is an agent published in the GitHub repository tzachbon/smart-ralph (532 stars, last pushed 2d ago), licensed MIT. It adds 57 tokens to every session and 3,412 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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