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 tryproduck/produck-skills --skill user-alignmentgit clone --depth 1 https://github.com/tryproduck/produck-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/tryproduck/produck-skills/user-alignment)<a href="https://agentmods.dev/skills/tryproduck/produck-skills/user-alignment"><img src="https://agentmods.dev/badge/skills/tryproduck/produck-skills/user-alignment/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/tryproduck/produck-skills/user-alignment"><img src="https://agentmods.dev/badge/skills/tryproduck/produck-skills/user-alignment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 115 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00072 | $0.04623 |
| Opus 5 | $0.00036 | $0.02312 |
| Sonnet 5 | $0.00014 | $0.00925 |
| Haiku 4.5 | $0.00007 | $0.00462 |
Grade A, and why
user-alignment 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 — 560 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Alignment & Agent-Executable PRDs
Purpose: A practical guide for turning messy user requests into aligned, testable Product Requirements Documents (PRDs) that autonomous or semi-autonomous agents can execute without drifting.
Two supporting files ship with this skill:
references/prd-template.md— the full copy-paste agent-executable PRD template.references/reading-list.md— the research and reference map this guide is built on.
1. Core thesis
A good agent PRD is not just a product document. It is a shared operating contract between the user, the product owner, and the implementation agent.
It must do three jobs at once:
- Align on user intent — what the user actually wants, why it matters, and what outcome would make them say “yes, that’s it.”
- Remove ambiguity before execution — especially around scope, constraints, priorities, edge cases, and trade-offs.
- Translate intent into executable work — sequenced phases, explicit files/systems, acceptance criteria, tests, and “do not do” boundaries.
For human teams, ambiguity can be resolved in meetings. Agents often resolve ambiguity by guessing. The PRD’s job is to make guessing unnecessary.
2. Research-backed principles
2.1 Start with the user problem, not the implementation
AI/product PRDs should begin with the user pain and the cost of the status quo, not with “we will use AI/model/tool X.” The model, framework, or agent is an implementation detail unless the user explicitly constrained it.
A strong problem statement should include:
- Who is affected.
- What they are trying to accomplish.
- What blocks them today.
- Why existing/manual/deterministic solutions are insufficient.
- What measurable improvement would matter.
Bad: “Build an AI assistant for support.”
Better: “Support agents spend 8 minutes triaging each ticket, and 23% are misrouted. We need ticket classification under 2 seconds with at least 92% routing accuracy, while escalating low-confidence cases.”
What ships with it
2 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 · 560 lines · 72 tokens per session scan A 1c94a0c07f31
user-alignment is a skill published in the GitHub repository tryproduck/produck-skills (511 stars, last pushed 26d ago), licensed Apache-2.0. It adds 72 tokens to every session and 4,623 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 2026-08-30.
Other skills, from other repositories
resolve-pr-comments
Evaluate, fix, answer, and reply to GitHub pull request review comments and conversation comments. Handles both change requests (fix or skip) and reviewer questions (explain using reasoning recalled from past Claude Code transcripts). Use when the user asks to "resolve PR comments", "fix review comments", "address PR…
create-threat-model
Analyze a codebase and produce a structured threat model at .turbo/threat-model.md covering assets, trust boundaries, attack surfaces with existing mitigations, attacker stories, and calibrated severity. Use when the user asks to "create a threat model", "threat model", "threat model this codebase", "security…
update-dependencies
Upgrade project dependencies with breaking change research for major version updates. Use when the user asks to "update dependencies", "upgrade packages", "upgrade dependencies", "update deps", "upgrade deps", "update npm deps", "update Swift packages", "cargo update", "go get updates", "bundle update", or "pip…
map-codebase
Deep architecture report that fans out parallel inspections across different aspects of the codebase (structure, tech stack, APIs, patterns, data flow, dependencies, testing) and synthesizes findings into a comprehensive document at .turbo/codebase-map.md and .turbo/codebase-map.html. Use when the user asks to "map…
review-plan
Review a plan by running internal reviews and a peer review in parallel and returning combined findings. Use when the user asks to "review my plan", "check my plan", "critique my plan", or wants feedback on a plan.
changelog-rules
Shared changelog conventions and formatting rules referenced by /create-changelog and /update-changelog. Not typically invoked directly.