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 Pranjay-kumar/universal-data-acquisition-pipeline-skill --skill data-acquisition-designgit clone --depth 1 https://github.com/Pranjay-kumar/universal-data-acquisition-pipeline-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/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-design)<a href="https://agentmods.dev/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-design"><img src="https://agentmods.dev/badge/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-design/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/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-design"><img src="https://agentmods.dev/badge/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-design.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 | $0.00072 | $0.00197 |
| Opus 5.5 | $0.00029 | $0.00079 |
| Sonnet 5.5 | $0.00014 | $0.00039 |
| Haiku 4.5 | $0.00007 | $0.00020 |
Grade A, and why
data-acquisition-design 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.
What it actually says
Data Acquisition Design
Act as the dataset designer for acquisition work. Convert vague goals into the smallest useful dataset.
Shared Core
Read from ../data-acquisition-core/references/:
source-access.mdoutput-contracts.mdworkflow.mdexamples.md
Output
Return:
ModeSelectionSourceAccessClasswhen access is already impliedDatasetNeedDatasetSpecDataAcquisitionMemoApprovalGate
Do not hunt endpoints unless the user asks to continue.
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 · 31 lines · 72 tokens per session scan A f0faa54fb1c2
data-acquisition-design is a skill published in the GitHub repository Pranjay-kumar/universal-data-acquisition-pipeline-skill (3 stars, last pushed 4mo ago), licensed MIT. It adds 72 tokens to every session and 197 once invoked, about $0.0003 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.
Other skills, from other repositories
tastemaker
Generate genuinely beautiful, on-brand UI instead of generic "AI slop" — use whenever the user asks to build, design, style, or improve a UI, landing page, dashboard, app screen, or component, whenever a PRD/spec needs a design pass before implementation, whenever the user pastes reference images/Pinterest/Dribbble…
fde
Keeps the engagement record for client work. Use when they name a client or stakeholder. Use when they debrief a meeting or paste notes. Use when they ask what was agreed. Use when they run a POC, change the client's codebase, prove it on their staging, go live, or need evals before a model acts. Use when they prep a…
board-memo
Draft a board or executive summary of an engagement using outcomes, risks and investment decisions. Use when the sponsor needs to brief senior leadership.
brief
Clarify a new customer brief, desired outcome, constraints and evidence gaps. Use for kickoff or a first meeting; do not repeat discovery already supplied.
business-case
Develop a business case for an initiative using costs, benefits, risks and evidence. Use when a sponsor needs budget or timeline justification.
earn-trust
Plan how to earn customer trust and appropriate access. Use when credibility, permissions or AI policy constrain the engagement.