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 skills add Varnan-Tech/opendirectory --skill company-radargit clone --depth 1 https://github.com/Varnan-Tech/opendirectoryWrote 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.
[](https://agentmods.dev/skills/varnan-tech/opendirectory/company-radar)<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/company-radar"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/company-radar/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.
<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/company-radar"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/company-radar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.03364 |
| Opus 5 | $0.00019 | $0.01682 |
| Sonnet 5 | $0.00008 | $0.00673 |
| Haiku 4.5 | $0.00004 | $0.00336 |
Grade A, and why
company-radar 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 10d 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 — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Company Radar
Competitive intelligence orchestrator. Takes company names, runs parallel research across 8+ platforms, scores each on a 0-100 heat scale, and produces a structured radar report with AI briefings.
This is an orchestration skill. It delegates data collection to existing opendirectory micro-skills and coordinates their output --- it doesn't replace them.
Architecture
INPUT: Company name(s) / URL(s)
|
[1. Profile Phase] -- Web research to build company profiles
|
[2. Signal Collection] -- Parallel platform research (8 channels)
/ | | | | | \ \
GH TW RD HN PH YC WEB MEDIA
|
[3. Scoring Engine] -- 4-dimension heat score (0-100)
|
[4. AI Synthesis] -- Executive briefing generation
|
OUTPUT: Radar Report + Per-Company Deep Dives
Signal Channels and Their Opendirectory Mappings
| Channel | Opendirectory Skill | What It Detects |
|---|---|---|
| GitHub | gh-issue-to-demand-signal + web search |
Stars, forks, commits, releases, shipping velocity |
| Twitter/X | twitter-GTM-find-skill |
Tweets, mentions, engagement, founder activity |
reddit-icp-monitor, reddit-post-engine |
Community sentiment, pain points, buzz | |
| Hacker News | hackernews-intel |
Story mentions, points, front-page signals |
| Product Hunt | producthunt-launch-kit |
Launches, votes, maker activity |
| YC Jobs | yc-intent-radar-skill / yc-jobs-scraper |
Job listings, hiring departments, growth signals |
| Web / Press | Tavily search + competitor-pr-finder |
News, product announcements, funding |
| Pricing | pricing-finder |
Pricing changes, tier updates, plan structure |
| Market Position | map-your-market |
ICP, competitor landscape, messaging gaps |
Common Mistakes
| The agent will want to... | Why that's wrong |
|---|---|
| Run skills sequentially | All 8 signal channels are independent. Must run in parallel. |
| Hallucinate GitHub star counts or hiring numbers | Every data point must trace to a specific search result or skill output. No "approx 500 stars". |
| Skip the heat score computation | The radar report requires scored output, not just raw data dump. Heat score is the core differentiator. |
| Output incomplete reports because a skill failed | One failing channel does not block the full report. Score what you have, note gaps. |
| Use AI training knowledge for company descriptions | Every company description must come from live web research, not memory. |
| Forget to score activity levels from heat scores | Heat score has explicit thresholds: High (60+), Medium (30-59), Low (1-29), Dormant (0). |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 411 lines · 39 tokens per session scan A ad5ac79ed49e
company-radar is a skill published in the GitHub repository Varnan-Tech/opendirectory (637 stars, last pushed 24d ago), licensed MIT. It adds 39 tokens to every session and 3,364 once invoked, about $0.0002 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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