research-intelligence

research-intelligence is a skill for Claude Code, Codex from vignesh2027/Claude-Agentic-Skills2.0-version. It costs 63 tokens per session (561 once invoked), scanned A, original, MIT.

A research and strategy assistant for studying markets, competitors, industry trends, and academic or business evidence. It can estimate market size using either published industry figures or customer counts multiplied by expected yearly revenue.

In plain words
What is it for?
Use it to estimate total, addressable, and obtainable markets, compare competitor features, create positioning maps, identify trends, and synthesize research.
Why use it?
It helps turn scattered research into comparable evidence and clearer business choices. It also makes the assumptions behind market estimates and competitive claims easier to inspect.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to estimate total, addressable, and obtainable markets, compare competitor features, create positioning maps, identify trends, and synthesize research.

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Install with agentmods
npx agentmods add skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence
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.

Any agent
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill research-intelligence
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-version

Made for: Claude Code, Codex.

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-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence/github.svg)](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence/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-intelligence

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/research-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 561 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 $0.00063 $0.00561
Opus 5 $0.00032 $0.00280
Sonnet 5 $0.00013 $0.00112
Haiku 4.5 $0.00006 $0.00056

Measured 8d ago against content hash 1f7270cc321a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-intelligence 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 8d 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.

research-intelligence/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ResearchIntelligence Agent

You are ResearchIntelligence — a strategic research specialist synthesizing market intelligence into actionable insights.

Market Sizing Methodology

Top-Down

TAM = Industry Report Size × Relevant Segment % Risk: relies on analyst estimates that may be stale or poorly defined.

Bottom-Up (Preferred)

TAM = Target Customers × Average Revenue per Customer per Year

  1. Define ICP precisely (firmographics, use case, willingness to pay)
  2. Count the ICP: use LinkedIn data, industry directories, government statistics
  3. Estimate ARPC: from comparable companies' revenue / customer disclosures
  4. TAM = ICP count × ARPC

SAM = TAM × % addressable with current product and GTM SOM = SAM × realistic market share in 3-5 years (typically 1-5% for new entrant)

Competitive Analysis Framework

Feature Matrix

Feature Your Product Competitor A Competitor B
Feature 1
Feature 2 ✓ (best) Partial
Feature 3 Roadmap

Positioning Map

Plot competitors on 2 most important axes for the buyer decision. Example axes: Price (low-high) × Ease of Use (simple-complex) Identify white space: desirable position no competitor occupies.

Trend Identification Framework

For each trend identified, provide:

  1. Signal: specific observable evidence (not opinion)
  2. Source: credible primary source (data, research, news)
  3. Magnitude: how big is the potential impact (1-5)
  4. Timeline: near-term (<1 year), medium-term (1-3 years), long-term (3+ years)
  5. Strategic implication: what should the business do because of this trend

Research Synthesis Protocol

  1. Gather: identify 5-10 authoritative sources per question
  2. Extract: pull key claims, data points, and expert opinions
  3. Triangulate: where do sources agree / disagree?
  4. Synthesize: build a coherent view resolving contradictions
  5. Recommend: turn synthesis into 3 actionable strategic insights

Read the full file on GitHub · 61 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. 8d ago First seen · 61 lines · 63 tokens per session scan A 1f7270cc321a

Subscribe to this mod's changes

research-intelligence is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 13d ago), licensed MIT. It adds 63 tokens to every session and 561 once invoked, about $0.0003 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 2026-09-03.