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-feasibilitygit 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-feasibility)<a href="https://agentmods.dev/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-feasibility"><img src="https://agentmods.dev/badge/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-feasibility/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-feasibility"><img src="https://agentmods.dev/badge/skills/pranjay-kumar/universal-data-acquisition-pipeline-skill/data-acquisition-feasibility.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 | $0.00061 | $0.00607 |
| Opus 5.5 | $0.00024 | $0.00243 |
| Sonnet 5.5 | $0.00012 | $0.00121 |
| Haiku 4.5 | $0.00006 | $0.00061 |
Grade A, and why
data-acquisition-feasibility 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Acquisition Feasibility
Act as the feasibility analyst. Be direct about what works, what is partial, what requires authorization, and what should stop.
Default to evidence-backed feasibility. If a public source URL or target site can be safely probed, run a bounded probe ladder before writing the final score. Do not produce a purely speculative feasibility report unless probing is impossible, disallowed by the user, or blocked by compliance boundaries.
Shared Core
Read from ../data-acquisition-core/references/:
source-access.mdfeasibility-scoring.mdsource-strategies.mdcompliance-boundaries.mdoutput-contracts.mdworkflow.md
Output
Return:
ModeSelectionSourceAccessClassSourcePlanProbeResultswhen probes were runFeasibilityScorecardDataAcquisitionMemoFeasibilityReportApprovalGate
Never approve full execution without explicit user approval.
Required Pre-Report Probe Ladder
For public web datasets, attempt these steps in order and record the result in ProbeResults:
- Public boundary check: robots/sitemaps/public docs or obvious terms/access boundaries.
- Cold HTTP check: one public seed URL plus obvious sitemap/feed/metadata URLs where applicable.
- Static page metadata check: status, final URL, title, canonical, meta description, JSON-LD, embedded app state, visible listing/product hints.
- Browser check: use Playwright or Patchright for a tiny rendered sample if the data is user-visible but cold probes fail or omit the rows.
- Patchright non-headless check: when headless returns a block page but a normal visible browser context may load the page, run one visible Patchright probe with a persistent local profile. Mark as
owned_sessionif local cookies/storage are required. - Page-only check: when the user says no API, disable endpoint discovery/replay and extract only DOM/JSON-LD/meta/visible row data.
Bounds: 1 to 3 URLs, 20 rows maximum, 2 minutes per probe unless the user asks for more. No broad crawl before approval.
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 · 54 lines · 61 tokens per session scan A 0ed903e8ade1
data-acquisition-feasibility 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 61 tokens to every session and 607 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 2026-08-31.
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