competitive-intel

competitive-intel is a skill for Claude Code, Codex from Aditya923-c/xpoz-agent-skills. It costs 54 tokens per session (3,363 once invoked), scanned A, original, MIT.

A workflow for comparing brands or products using conversations on Twitter/X, Reddit, and Instagram. It examines how often each is discussed, the tone of those discussions, their market positioning, and overlapping audiences.

In plain words
What is it for?
Use it for competitive analysis, brand comparisons, share-of-voice studies, sentiment comparisons, and finding what people say about competing products.
Why use it?
It replaces scattered social-media checking with a structured comparison of public conversations. It helps reveal differences in reputation, messaging, and audience interest.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: reads .claude/ paths; mentions Claude Code; built for openclaw.

Good fit Use it for competitive analysis, brand comparisons, share-of-voice studies, sentiment comparisons, and finding what people say about competing products.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aditya923-c/xpoz-agent-skills/competitive-intel
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 Aditya923-c/xpoz-agent-skills --skill competitive-intel
Clone the repo
git clone --depth 1 https://github.com/Aditya923-c/xpoz-agent-skills

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 competitive-intel

README.md
[![agentmods](https://agentmods.dev/badge/skills/aditya923-c/xpoz-agent-skills/competitive-intel/github.svg)](https://agentmods.dev/skills/aditya923-c/xpoz-agent-skills/competitive-intel)
Your own site
<a href="https://agentmods.dev/skills/aditya923-c/xpoz-agent-skills/competitive-intel"><img src="https://agentmods.dev/badge/skills/aditya923-c/xpoz-agent-skills/competitive-intel/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 competitive-intel

Your own site · 80×15
<a href="https://agentmods.dev/skills/aditya923-c/xpoz-agent-skills/competitive-intel"><img src="https://agentmods.dev/badge/skills/aditya923-c/xpoz-agent-skills/competitive-intel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,363 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 2 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 $0.00054 $0.03363
Opus 5 $0.00027 $0.01682
Sonnet 5 $0.00011 $0.00673
Haiku 4.5 $0.00005 $0.00336

Measured 12d ago against content hash 84817ae3e212, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

competitive-intel scanned grade A with 2 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 12d 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.

import secrets, hashlib, base64, urllib.parse, json, urllib.request, os

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

subprocess.run(['mcporter', 'config', 'remove', 'xpoz'], capture_output=True)
skills/competitive-intel/SKILL.md · 440 lines

How it starts

The opening of the file, as written. The whole thing — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Competitive Intelligence

Overview

Compare multiple brands or products side by side across Twitter/X, Reddit, and Instagram. Measure share of voice, compare sentiment, identify positioning differences, and discover competitive advantages from real social conversations.

When to Use

Activate when the user asks:

  • "Compare [BRAND A] vs [BRAND B] on social media"
  • "Share of voice: [BRAND] vs competitors"
  • "Competitive analysis for [PRODUCT]"
  • "How does [BRAND A] sentiment compare to [BRAND B]?"
  • "What are people saying about [BRAND] vs [COMPETITOR]?"

Setup & Authentication

Before fetching data, ensure Xpoz access is configured. Follow these checks in order.

Check 1: Already authenticated?

If you have MCP tools, try calling any Xpoz tool (e.g., checkAccessKeyStatus). If it works → skip to Step 1.

If you have the SDK, try:

from xpoz import XpozClient
client = XpozClient()  # reads XPOZ_API_KEY env var

If this succeeds without error → skip to Step 1.

If neither works, you need to authenticate. Choose the path that fits your environment:


Path A: MCP via mcporter (OpenClaw agents)

If mcporter is available:

mcporter call xpoz.checkAccessKeyStatus

If hasAccessKey: true → ready. If not:

mcporter config add xpoz https://mcp.xpoz.ai/mcp --auth oauth

Then authenticate — generate the OAuth URL and send it to the user:

Step 1: Generate authorization URL

import secrets, hashlib, base64, urllib.parse, json, urllib.request, os

verifier = secrets.token_urlsafe(64)
challenge = base64.urlsafe_b64encode(hashlib.sha256(verifier.encode()).digest()).rstrip(b'=').decode()
state = secrets.token_urlsafe(32)

# Dynamic client registration
reg_req = urllib.request.Request(
    'https://mcp.xpoz.ai/oauth/register',
    data=json.dumps({
        'client_name': 'Agent Skills',
        'redirect_uris': ['https://www.xpoz.ai/oauth/openclaw'],
        'grant_types': ['authorization_code'],
        'response_types': ['code'],
        'token_endpoint_auth_method': 'none',
    }).encode(),
    headers={'Content-Type': 'application/json'},
)
reg_resp = json.loads(urllib.request.urlopen(reg_req).read())

params = urllib.parse.urlencode({
    'response_type': 'code',
    'client_id': reg_resp['client_id'],
    'code_challenge': challenge,
    'code_challenge_method': 'S256',
    'redirect_uri': 'https://www.xpoz.ai/oauth/openclaw',
    'state': state,
    'scope': 'mcp:tools',
    'resource': 'https://mcp.xpoz.ai/',
})

auth_url = 'https://mcp.xpoz.ai/oauth/authorize?' + params

# Save state for token exchange
os.makedirs(os.path.expanduser('~/.cache/xpoz-oauth'), exist_ok=True)
with open(os.path.expanduser('~/.cache/xpoz-oauth/state.json'), 'w') as f:
    json.dump({'verifier': verifier, 'state': state, 'client_id': reg_resp['client_id'],
               'redirect_uri': 'https://www.xpoz.ai/oauth/openclaw'}, f)

print(auth_url)

Read the full file on GitHub · 440 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. 12d ago First seen · 440 lines · 54 tokens per session scan A 84817ae3e212

Subscribe to this mod's changes

competitive-intel is a skill published in the GitHub repository Aditya923-c/xpoz-agent-skills (5 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 3,363 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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