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 LuckyOneTwoThree/pm-skill --skill user-research-behavior-analysisgit clone --depth 1 https://github.com/LuckyOneTwoThree/pm-skillWrote 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/luckyonetwothree/pm-skill/user-research-behavior-analysis)<a href="https://agentmods.dev/skills/luckyonetwothree/pm-skill/user-research-behavior-analysis"><img src="https://agentmods.dev/badge/skills/luckyonetwothree/pm-skill/user-research-behavior-analysis/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/luckyonetwothree/pm-skill/user-research-behavior-analysis"><img src="https://agentmods.dev/badge/skills/luckyonetwothree/pm-skill/user-research-behavior-analysis.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 | $0.00081 | $0.03352 |
| Opus 5 | $0.00041 | $0.01676 |
| Sonnet 5 | $0.00016 | $0.00670 |
| Haiku 4.5 | $0.00008 | $0.00335 |
Grade A, and why
user-research-behavior-analysis 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 314 lines · 81 tokens per session scan A 70de5a571b91
user-research-behavior-analysis is a skill published in the GitHub repository LuckyOneTwoThree/pm-skill (6 stars, last pushed 3mo ago), with no licence file. It adds 81 tokens to every session and 3,352 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
ab-test-design
Use before running any experiment that will inform a product decision. All six elements — hypothesis, metric, sample size, duration, stopping rule, and decision rule — must be defined before the test starts. Blocks "we'll stop when we see something" completions.
ai-feature-validation
Use before any AI feature is approved for build. Covers four AI-specific risks that standard PRD review misses: hallucination UX, trust calibration, scope creep, and reversibility. Blocks "we validated it like any other feature" completions.
feature-scoping
Use before any engineering estimate is made. Requires a written scope before an estimate, and a written estimate before a commit. Blocks "we'll scope as we go" and "just give me a rough number" completions.
metric-definition
Use before writing any implementation code for a new feature. North star metric, guardrail metrics, and diagnostic metrics must be defined — with baselines — before the build begins. Blocks "we'll figure out the metrics from the data" completions.
mvp-scope-validator
Use before writing a PRD for a new product or feature. Extracts the core hypothesis and reduces scope to the minimum needed to test it. Blocks feature lists that bundle multiple unvalidated assumptions.
prd-quality-gate
Use before committing scope, estimate, or engineering time to any feature. Requires user problem, success metric, scope boundary, and anti-goals defined before any estimate is made. Blocks "we'll define success once we see the data" completions.