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.
npx agentmods add skills/nirholas/xactions/competitor-intelligencenpx skills add nirholas/XActions --skill competitor-intelligencegit clone --depth 1 https://github.com/nirholas/XActionsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00051 | $0.00634 |
| Opus 5 | $0.00026 | $0.00317 |
| Sonnet 5 | $0.00010 | $0.00127 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
competitor-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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Intelligence
MCP-powered workflow plus browser scripts for analyzing competitor X/Twitter accounts.
MCP Tools
| Tool | Purpose |
|---|---|
x_get_profile |
Bio, follower/following counts, verified status |
x_get_tweets |
Recent posts with engagement metrics |
x_get_followers |
Follower list with bios |
x_get_following |
Following list for network analysis |
x_search_tweets |
Find mentions and replies |
x_competitor_analysis |
Automated comparison |
Browser Scripts
| Goal | Script |
|---|---|
| Side-by-side competitor comparison | src/competitorAnalysis.js |
| Compare audience overlap | src/audienceOverlap.js |
| Analyze their audience demographics | src/audienceDemographics.js |
| Find their viral tweets | src/viralTweetDetector.js |
| Benchmark your engagement | src/tweetPerformance.js |
| Track their trending topics | src/trendingTopicMonitor.js |
Analysis Workflow
- Collect profile --
x_get_profilefor target username - Pull tweets --
x_get_tweetswithlimit: 50, note frequency and themes - Calculate engagement -- Per-tweet rate:
(likes + RTs + replies) / followers - Categorize content -- Original vs reply vs retweet vs thread
- Audit audience --
x_get_followerswithlimit: 100, scan bios - Map network --
x_get_followingfor mutual connections and influencer relationships - Find overlap --
src/audienceOverlap.jsto compare your followers with theirs
Output Template
## Competitor Report: @{username}
### Profile
- Followers: {n} | Following: {n} | Ratio: {r}
- Verified: {yes/no} | Joined: {date}
### Content Strategy
- Posts/week: {n} | Top topics: {t1}, {t2}, {t3}
- Peak posting: {day} at {hour}
- Avg engagement rate: {rate}%
### Audience
- Common industries: {list}
- Follower size distribution: {breakdown}
### Network
- Notable follows: {list}
- Audience overlap with you: {percentage}%
Tips
- Run competitor analysis quarterly for trends
- Use
src/audienceOverlap.jsto find collaboration opportunities - Track competitors' viral content for content inspiration
- Mirror successful content formats, not exact content
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.
- 2d ago First seen · 74 lines · 51 tokens per session scan A c532a9f105a3
competitor-intelligence is a skill published in the GitHub repository nirholas/XActions (496 stars, last pushed 5d ago), licensed Apache-2.0. It adds 51 tokens to every session and 634 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 2026-08-30.
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