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 sabahudin-web/competitive-intelligence-radar --skill radar-publish-councilgit clone --depth 1 https://github.com/sabahudin-web/competitive-intelligence-radarWrote 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/sabahudin-web/competitive-intelligence-radar/radar-publish-council)<a href="https://agentmods.dev/skills/sabahudin-web/competitive-intelligence-radar/radar-publish-council"><img src="https://agentmods.dev/badge/skills/sabahudin-web/competitive-intelligence-radar/radar-publish-council/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/sabahudin-web/competitive-intelligence-radar/radar-publish-council"><img src="https://agentmods.dev/badge/skills/sabahudin-web/competitive-intelligence-radar/radar-publish-council.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00086 | $0.00645 |
| Opus 5 | $0.00043 | $0.00322 |
| Sonnet 5 | $0.00017 | $0.00129 |
| Haiku 4.5 | $0.00009 | $0.00064 |
Grade A, and why
radar-publish-council 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 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.
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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
radar-publish-council
Automation level: AUTONOMOUS (the CHECKPOINT was the decision to run the council at all).
Goal: get the war-room addendum onto the same three surfaces the gather run published to, so the strategy lives next to the evidence.
Inputs
The synthesized addendum from the council lead, structured as:
{
"summary": "One paragraph of the consensus, no em dashes.",
"moves": [
{ "title": "Concrete move", "rationale": "Why, with the supporting source or dossier field." }
],
"dissents": [ "Any move a teammate still disputes, and why." ]
}
Steps
-
Read
radar.config.jsonlast_runfor the briefing markdown path, the dashboard data path, andbriefing_notion_page_id. -
Local markdown: append a "Strategic War Room" section to
outputs/briefings/<date>-briefing.mdbelow the addendum marker. Render the summary, each move as a titled bullet with its rationale and source, and a "Dissents and risks" list. Keep every claim cited and free of em or en dashes. -
Dashboard: set
war_roomin the dashboard data JSON (summaryandmoves[]). If the council assigned threat levels (low / medium / high) from the threat ranking, also write each into the matchingcompetitors[].threat_levelso the dashboard threat chips and the threat filter light up. Then re-run the inject step fromradar-render-dashboardsooutputs/dashboard/<date>-dashboard.htmlandindex.htmlnow show the war room. -
Notion: append the same addendum to the Briefings page using
<notion_prefix>notion-update-pageonbriefing_notion_page_id, and set the page'sWar Roomcheckbox to true. -
Confirm all three surfaces updated and return their paths and the Notion link.
Edge cases
- The council ran but no briefing exists yet for this date: stop and tell the user to run
/radarfirst; the council analyzes an existing briefing. - Notion page id missing (gather did not publish to Notion): update the local markdown and dashboard, and tell the user Notion was skipped because the briefing was never published there.
- Re-running after an earlier council on the same briefing: replace the existing war-room section rather than appending a second one, so the surfaces do not accumulate duplicates.
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.
- 12d ago First seen · 57 lines · 86 tokens per session scan A c985b0ffcaa2
radar-publish-council is a skill published in the GitHub repository sabahudin-web/competitive-intelligence-radar (3 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 645 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
falsify
Adversarial falsification of sigint research findings. Generates disconfirming queries, executes web-only adversarial search, assigns ordinal verdicts (falsified | weakened | survived | inconclusive), and applies remediation (quarantine, confidence downgrade, follow-up queue). Invocable standalone via /sigint:falsify…
regulatory-review
This skill should be used when the user asks to "analyze regulations", "regulatory landscape", "compliance requirements", "legal considerations", "regulatory risk", "industry regulations", "compliance analysis", "regulatory trends", or needs guidance on understanding regulatory environments, compliance requirements…
report-writing
This skill should be used when the user asks to "write a report", "executive summary", "research report format", "report structure", "present findings", "business writing", "analysis documentation", or needs guidance on structuring research outputs, executive communication, or professional report formatting.
tech-assessment
This skill should be used when the user asks to "assess technology", "technology evaluation", "tech stack analysis", "technical feasibility", "technology trends", "build vs buy", "technology roadmap", "architecture assessment", or needs guidance on evaluating technologies, technical due diligence, or technology…
augment
Deep-dive into a specific area of current research. Orchestrates a single dimension-analyst using full swarm pattern (TeamCreate, TaskCreate, SendMessage). Use when the user wants to augment current research with deeper analysis of a specific area.
market-sizing
This skill should be used when the user asks to "calculate market size", "TAM SAM SOM analysis", "estimate market opportunity", "market sizing", "total addressable market", "serviceable market", "market potential", or needs guidance on market size estimation methodologies, market opportunity calculations, or growth…