Page Agent is a JavaScript library that embeds a natural-language agent inside a web page and lets it operate the page through its text-based DOM. It is used for web copilots, form filling, accessibility, and browser workflows, while the catalogue entries provide agent skills and instructions for using it.
Borrowing it
Nothing to install: this file belongs to alibaba/page-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alibaba/page-agent/main/.agents/skills/pre-impl-discussion/SKILL.mdgit clone --depth 1 https://github.com/alibaba/page-agentWrote 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/alibaba/page-agent/pre-impl-discussion)<a href="https://agentmods.dev/skills/alibaba/page-agent/pre-impl-discussion"><img src="https://agentmods.dev/badge/skills/alibaba/page-agent/pre-impl-discussion/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/alibaba/page-agent/pre-impl-discussion"><img src="https://agentmods.dev/badge/skills/alibaba/page-agent/pre-impl-discussion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, 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 44 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.
- medium Excessive Agency · line 101 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.
- medium Excessive Agency · line 99 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 | $0.00059 | $0.01032 |
| Opus 5.5 | $0.00024 | $0.00413 |
| Sonnet 5.5 | $0.00012 | $0.00206 |
| Haiku 4.5 | $0.00006 | $0.00103 |
Grade A, and why
pre-impl-discussion 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 2mo 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Implementation Discussion
Facilitate a structured, collaborative discussion to evaluate a proposed change before any implementation begins.
Golden Rule
Do NOT implement anything until the user explicitly confirms the final plan and says to proceed. Not even "let me try on a branch" — that's implementation. The user will tell you when discussion is over.
Interaction Style
- Concise during discussion. Each intermediate response should be short and focused on the current question. Do NOT repeat the full plan in every response.
- Complete when finalizing. Once the plan is mature and the user asks for it, present a single comprehensive (but terse) summary for final review.
- Ask, don't assume. When uncertain about project context, constraints, or preferences — ask. The user prefers collaborative discussion over receiving a pre-baked answer.
- Challenge the premise. Question whether the proposed change is the right one. Suggest simpler alternatives if they exist.
- Match the user's language. Reply in the same language the user writes in.
Procedure
1. Understand the Current State
Before forming any opinion:
- Read the relevant source files — configs, code, docs that relate to the change
- Understand the project structure — what's published vs private, what environments things target, existing constraints
- Map the impact surface — which files, packages, or systems would be affected
- Estimate implementation cost — how many files to touch, how much config to rewrite, what could break
Do NOT skip this step. Do NOT rely on assumptions about what "most projects" do.
2. Research Thoroughly
- Consult official sources — docs, changelogs, migration guides, GitHub issues
- Verify every claim with evidence. Don't say "X supports Y" without a source. If unsure, say so.
- Search in parallel to save time — batch independent queries
Common pitfalls:
- Assuming compatibility without checking actual version constraints
- Confusing roadmap/aspirations with actual released state
- Missing transitive constraints (a dependency of a dependency)
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.
- 2mo ago First seen · 105 lines · 59 tokens per session scan A a1e569065a2f
pre-impl-discussion is a skill published in the GitHub repository alibaba/page-agent (29,595 stars, last pushed 8d ago), licensed MIT. It adds 59 tokens to every session and 1,032 once invoked, about $0.0002 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 2026-08-30.
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