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 cnfeat/top-pm-skills --skill tech-radargit clone --depth 1 https://github.com/cnfeat/top-pm-skillsWrote 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/cnfeat/top-pm-skills/tech-radar)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/tech-radar"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/tech-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/cnfeat/top-pm-skills/tech-radar"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/tech-radar.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 | $0.02955 |
| Opus 5.5 | $0.00034 | $0.01182 |
| Sonnet 5.5 | $0.00017 | $0.00591 |
| Haiku 4.5 | $0.00009 | $0.00296 |
Grade A, and why
tech-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 1mo 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 — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Radar
Produce a complete technology radar document for an engineering team. The radar gives the team a shared, explicit position on every significant technology in their stack — what to standardize on, what to experiment with, what to evaluate, and what to actively stop using. Follow the ThoughtWorks Tech Radar format: four quadrants (Techniques, Tools, Platforms, Languages & Frameworks) each with four rings (Adopt, Trial, Assess, Hold). Each technology entry ("blip") gets a ring assignment, a one-paragraph rationale, and a date. Include a decision trail showing what moved and why, and a maintenance process the team can run to keep the radar current.
Required Inputs
Ask for these if not already provided:
- Team or company name — for the document header
- Current tech stack — list every significant technology, tool, language, and platform the team currently uses
- Technologies under active evaluation — tools or frameworks the team is currently trying or considering
- Technologies to deprecate or move off — anything the team wants to stop using or is actively migrating away from
- Strategic technology bets — any technologies the company has made a deliberate bet on (e.g., "we're all-in on Kubernetes" or "migrating to event-driven architecture")
- Team context — team size, product domain, and any constraints (regulatory, compliance, vendor lock-in concerns)
If a technology is mentioned without a ring placement, use the rationale inputs to determine the appropriate ring. When uncertain between two rings, ask.
Output Format
Technology Radar: [Team / Company Name]
Edition: [Month Year] Maintained by: [Team Name / Architecture Guild / CTO Office] Review cadence: Bi-annual (every 6 months) Next review: [Month Year + 6 months]
How to Read This Radar
This radar reflects [Team / Company Name]'s current thinking on technologies we use, evaluate, and retire. Use it to make consistent technology choices, onboard new engineers, and have structured conversations about the stack.
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.
- 1mo ago First seen · 299 lines · 86 tokens per session scan A 1979e3b0b64f
tech-radar is a skill published in the GitHub repository cnfeat/top-pm-skills (55 stars, last pushed 4mo ago), licensed MIT. It adds 86 tokens to every session and 2,955 once invoked, about $0.0003 per session on Opus 5.5. 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.
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