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 last-30-days-researchgit 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/last-30-days-research)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/last-30-days-research"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/last-30-days-research/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/last-30-days-research"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/last-30-days-research.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 | $0.00097 | $0.01653 |
| Opus 5 | $0.00048 | $0.00826 |
| Sonnet 5 | $0.00019 | $0.00331 |
| Haiku 4.5 | $0.00010 | $0.00165 |
Grade A, and why
last-30-days-research 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 9d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Last 30 Days Research
The Problem
Googling gives SEO-stuffed "best of" lists written six months ago by someone who has never used the thing. Real honest takes live on Reddit threads, X replies, and niche communities — but chasing them across platforms eats your afternoon. This skill does the chase for you.
Required Inputs
| Input | Required | Notes |
|---|---|---|
| Topic | Yes | Tool, trend, feature, product, event, company — anything with a name |
| Date scope | No | Defaults to last 30 days. Can override to last 7 days or last 90 days |
| Angle | No | e.g. "focus on developer sentiment" or "looking for pricing complaints specifically" |
Output Structure
The output is a structured research report with the following sections, delivered in this exact order:
## Last 30 Days Research: [Topic]
Research window: [Date 30 days ago] → [Today's date]
---
## What People Agree On
[Consensus points that appear across multiple platforms — most reliable signal]
## Where People Disagree
[Active debates, contrasting views — include which side has more weight]
## Pain Points That Keep Coming Up
[Recurring complaints and frustrations — strongest signal of real problems]
## Positive Signals
[What people genuinely praise — not PR, but unprompted appreciation]
## Most Interesting Takes
[Contrarian, unexpected, or surprisingly insightful comments worth noting]
## Sources
[Links to the most useful threads/posts found — 5–10 links with brief labels]
## Signal Confidence
[High / Medium / Low — with a one-line rationale based on data volume and consistency]
Each section should contain substantive content, not placeholders. If a section has no findings (e.g. no positive signals found), state that explicitly rather than leaving it empty or fabricating content.
Instructions for Claude
Step 1 — Calculate the date window
Determine today's date and subtract 30 days to get the research start date. Format: YYYY-MM-DD. Use these dates explicitly in every search query.
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.
- 9d ago First seen · 159 lines · 97 tokens per session scan A 4e5de44cd818
last-30-days-research is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 3mo ago), licensed MIT. It adds 97 tokens to every session and 1,653 once invoked, about $0.0005 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 2026-09-03.
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