What is tech-brand-recruiting-db?

A database tool for WeChat-sourced information about technology companies' recruiting, technical branding, talent programs, events, scholarships, and related opportunities. WeChat is a Chinese messaging and publishing platform.

Use it to build or maintain a recruiting and technical-branding database, inspect records, export them, or clean outdated entries while keeping source links.

It provides a structured way to collect, refresh, search, export, and remove records instead of relying on scattered WeChat search results.

tech-brand-recruiting-db — Skill for Claude Code by RongchangLi

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 RongchangLi/pocketskill --skill tech-brand-recruiting-db

Clone the repo

git clone --depth 1 https://github.com/RongchangLi/pocketskill

Made for: Claude Code.

Or install my-skill, the plugin that ships this one along with the rest of its 12 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/rongchangli/pocketskill/tech-brand-recruiting-db/github.svg)](https://agentmods.dev/skills/rongchangli/pocketskill/tech-brand-recruiting-db)

Your own site

<a href="https://agentmods.dev/skills/rongchangli/pocketskill/tech-brand-recruiting-db"><img src="https://agentmods.dev/badge/skills/rongchangli/pocketskill/tech-brand-recruiting-db/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/rongchangli/pocketskill/tech-brand-recruiting-db"><img src="https://agentmods.dev/badge/skills/rongchangli/pocketskill/tech-brand-recruiting-db.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,264 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.

Model	Per session	Once invoked
Fable 5.1	$0.00064	$0.01264
Opus 5	$0.00032	$0.00632
Sonnet 5	$0.00013	$0.00253
Haiku 4.5	$0.00006	$0.00126

Measured 9d ago against content hash fba92c336d5f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

tech-brand-recruiting-db 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/tech_brand_db.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.

plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tech Brand Recruiting DB

Instructions

Use this skill when the user wants to create, refresh, inspect, export, or clean a database of internet technology company technical branding and recruiting information, scoped to WeChat public account search results.

The skill uses the shared WeChat search tool:

plugins/my-skill/tools/wechat-search/wx_search.mjs

In a WorkBuddy/OpenClaw zip package, the same tool is bundled under:

{baseDir}/tools/wechat-search/wx_search.mjs

The bundled script is:

plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py

Required Rules

Search only within WeChat results by default. Do not use ordinary web search unless the user explicitly allows it.
Every accepted record must keep a source URL from the WeChat search result in source_url, exported as 原文溯源.
Prefer mp.weixin.qq.com links when --resolve-url succeeds; otherwise keep the Sogou Weixin URL returned by the tool.
Do not invent official links. Leave official_url empty unless the source itself provides reliable evidence.
Keep modest query volumes. The default refresh uses rolling query selection and small result counts.
Treat Sogou URLs as unstable because tokens change. Deduplicate with title, channel, publish date, and summary fingerprint.
For destructive cleanup, run dry-run first. Use --confirm only after the deletion count is understood.

The allowed-tools frontmatter means agents may run shell commands to invoke the local WeChat search tool and the database script.

Common Commands

Run from the Pocket Skill repository root, or from the WorkBuddy/OpenClaw workspace where the skill can access its {baseDir}:

conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py init
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py refresh --dry-run
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py refresh --max-queries 60 --limit-per-query 3
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py query --limit 20
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py stats
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py export --format csv --output data/tech-brand-recruiting/export.csv
conda run -n vibe-coding python plugins/my-skill/skills/my-skills/tech-brand-recruiting-db/scripts/tech_brand_db.py delete-range --from 2026-01-01 --to 2026-03-31 --field collected_at --dry-run

Read the full file on GitHub · 102 lines

Files

What ships with it

4 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.

9d ago First seen · 102 lines · 64 tokens per session scan A fba92c336d5f

Subscribe to this mod's changes

tech-brand-recruiting-db is a skill published in the GitHub repository RongchangLi/pocketskill (2 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,264 once invoked, about $0.0003 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.

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