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public-web-census

public-web-census is a skill for Codex from KayZhongyi/public-web-census. It costs 136 tokens per session (2,112 once invoked), scanned A, original, MIT.

A workflow for collecting and comparing publicly visible information from websites and social platforms as dated, traceable evidence. It treats the result as the records found within a stated scope, not a complete view of hidden or restricted data.

In plain words
What is it for?
Use it to build web and social data snapshots, maintain observation history, compare changes, and produce CSV or JSON evidence for analysis.
Why use it?
It keeps refreshes, comparisons, and validation organized so findings can be checked over time and unavailable information is visible.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex; mentions OpenCode.

not rated 1repo 2mo ago A scan 136 tokens original MIT

Good fit Use it to build web and social data snapshots, maintain observation history, compare changes, and produce CSV or JSON evidence for analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kayzhongyi/public-web-census/public-web-census
View source ↗ KayZhongyi/public-web-census kayzhongyi.github.io
Install

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.

Any agent
npx skills add KayZhongyi/public-web-census --skill public-web-census
Clone the repo
git clone --depth 1 https://github.com/KayZhongyi/public-web-census

Made for: Codex.

Wrote 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.

agentmods badge for public-web-census

README.md
[![agentmods](https://agentmods.dev/badge/skills/kayzhongyi/public-web-census/public-web-census/github.svg)](https://agentmods.dev/skills/kayzhongyi/public-web-census/public-web-census)
Your own site
<a href="https://agentmods.dev/skills/kayzhongyi/public-web-census/public-web-census"><img src="https://agentmods.dev/badge/skills/kayzhongyi/public-web-census/public-web-census/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.

agentmods 80×15 button for public-web-census

Your own site · 80×15
<a href="https://agentmods.dev/skills/kayzhongyi/public-web-census/public-web-census"><img src="https://agentmods.dev/badge/skills/kayzhongyi/public-web-census/public-web-census.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 136 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,112 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00136 $0.02112
Opus 5.5 $0.00054 $0.00845
Sonnet 5.5 $0.00027 $0.00422
Haiku 4.5 $0.00014 $0.00211

Measured 2mo ago against content hash 1461a11ca5c6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

public-web-census 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.

The scan reads SKILL.md. This mod also ships 19 executable files (scripts/apply_analysis.py, scripts/apply_customer_voice.py, scripts/collect_facebook.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

SKILL.md · 181 lines

How it starts

The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Public Web Census

Turn scattered public web signals into a refreshable evidence ledger and decision-ready outputs. Treat a census as a best-effort capture of all retrievable records inside a declared scope at a stated cutoff, never as a guarantee about hidden, deleted, personalized, or restricted content.

Keep the user-facing workflow simple

The user may be a non-technical market, presales, product, or management colleague. Accept a natural-language request and translate it into the commands below. Do not make the user choose scripts, schemas, or storage paths unless a choice materially changes the result.

On first use:

  1. Run ./public-web-census doctor.
  2. If browser collection is not ready, run ./public-web-census setup and explain only the manual Chrome steps.
  3. Never ask for a platform password. Pause while the user signs in or completes platform verification directly in Chrome.
  4. Create a versioned workspace by default when the user asks to update, monitor, compare over time, share with colleagues, or reuse the data later.
  5. Report what was collected, where the evidence lives, which scope was covered, and which fields or surfaces were unavailable.

Preserve these invariants

  • Work only with information visible through authorized, ordinary access.
  • Never bypass authentication, CAPTCHA, rate limits, robots controls, or platform safeguards.
  • Pause for human verification; never automate a challenge.
  • Keep raw observations immutable and separate from translation, classification, and conclusions.
  • Record target, source population, scope, cutoff, failures, and coverage limitations.
  • Retain stable IDs and source URLs. Never infer deletion from one missing observation.
  • Remove credentials, private URLs, personal data, and unreviewed raw corpora from shared outputs.

Read references/collection-safety.md before live collection.

Choose the operating path

Use a standard CSV/JSON bundle for a one-off investigation. Use a versioned workspace whenever the evidence will be refreshed, compared, handed to another department, or reused by another Agent.

Read the full file on GitHub · 181 lines

Files

What ships with it

44 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.

Changes

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.

  1. 2mo ago First seen · 181 lines · 136 tokens per session scan A 1461a11ca5c6

Subscribe to this mod's changes

public-web-census is a skill published in the GitHub repository KayZhongyi/public-web-census (1 stars, last pushed 2mo ago), licensed MIT. It adds 136 tokens to every session and 2,112 once invoked, about $0.0005 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 2026-08-31.

Analytics and metricsClaude CodeResearchagent-skillsbrowser-automationcodexcompetitive-intelligencecompetitor-analysis
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