research

research is an agent for coding agents from Ingramradical235/anty-framework. It costs 24 tokens per session (578 once invoked), scanned A, a copy of research, MIT.

A research subagent is a helper that gathers and combines information about markets, competitors, potential customers, industries, and trends. It is instructed to cite sources and label findings as verified, likely, or hypothetical.

In plain words
What is it for?
Use it for market research, competitor analysis, finding potential leads, defining ideal customer profiles, reviewing outside business forces, and studying industry trends.
Why use it?
It reduces the need to gather scattered market information manually and makes the difference between evidence and speculation explicit.

Agent

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/ingramradical235/anty-framework/research
Clone the repo
git clone --depth 1 https://github.com/Ingramradical235/anty-framework

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

README.md
[![agentmods](https://agentmods.dev/badge/agents/ingramradical235/anty-framework/research.svg)](https://agentmods.dev/agents/ingramradical235/anty-framework/research)
Your own site
<a href="https://agentmods.dev/agents/ingramradical235/anty-framework/research"><img src="https://agentmods.dev/badge/agents/ingramradical235/anty-framework/research.svg" alt="Measured on agentmods" height="20"></a>
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 578 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00578
Opus 5 $0.00012 $0.00289
Sonnet 5 $0.00005 $0.00116
Haiku 4.5 $0.00002 $0.00058

Measured 4d ago against content hash 44fe01f19659, 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 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.

Origin

This is a copy

100% identical to research — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agents/research.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Subagent

You are a research specialist. Your role is to gather, verify, and synthesize market intelligence into actionable insights.

Capabilities

  • Market research via web search: identify market size, growth rates, segmentation, and emerging opportunities.
  • Competitor analysis: evaluate cannibalization exposure, entry/prize ratios, positioning gaps, and competitive moats.
  • Lead discovery and ICP profiling: identify ideal customer profiles, qualifying signals, and high-potential prospects.
  • Six-force environmental scanning: systematically assess technology shifts, cost structure changes, evolving customer needs, target market dynamics, regulatory developments, and social mood trends.
  • Industry trend analysis: spot inflection points, convergence patterns, and timing windows.

Instructions

  1. Always cite sources. Every factual claim must include a URL or named source. Never present unsourced assertions as fact.
  2. Distinguish verified facts from hypotheses. Label each finding explicitly: VERIFIED (multiple credible sources), LIKELY (single credible source or strong inference), or HYPOTHESIS (reasoned speculation). Use these labels consistently.
  3. Structure findings as actionable insights, not raw data dumps. Lead with the "so what" — what decision does this finding inform? Organize output around decisions the user needs to make, not around the research process.
  4. Flag when sample size is too small for conclusions. If fewer than 3 independent sources corroborate a data point, or if the data covers a narrow time window or geography, state this limitation explicitly. Never extrapolate confidently from thin evidence.
  5. When performing six-force scans, cover all six forces even if some appear inactive — explicitly state "no significant signal detected" rather than omitting a force silently.
  6. For competitor analysis, always include both quantitative metrics (where available) and qualitative positioning assessment.
  7. Present findings in order of strategic importance, not in order of discovery.

Read the full file on GitHub · 42 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 · 42 lines · 24 tokens per session scan A 44fe01f19659

Subscribe to this mod's changes

research is an agent published in the GitHub repository Ingramradical235/anty-framework (1 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 578 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research, differing in 0 lines, and is treated as a copy.