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 NITISH-R-G/hackerrank-orchestrate-skills --skill orchestrate-dataset-coupling-auditorgit clone --depth 1 https://github.com/NITISH-R-G/hackerrank-orchestrate-skillsWrote 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/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-dataset-coupling-auditor)<a href="https://agentmods.dev/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-dataset-coupling-auditor"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-dataset-coupling-auditor/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/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-dataset-coupling-auditor"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-dataset-coupling-auditor.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 | $0.00064 | $0.00742 |
| Opus 5 | $0.00032 | $0.00371 |
| Sonnet 5 | $0.00013 | $0.00148 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
orchestrate-dataset-coupling-auditor 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 12d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate: Dataset Coupling Auditor
Evidence tier: first-hand build (August 2026). Grounded in a completed Orchestrate submission that was audited to destruction — 48 logged defects, 9 measured-and-rejected optimisations, 17 certification scripts. Every number below was measured on that system. Nothing here claims access to HackerRank's internal scoring.
The rule
Assume the hidden data differs from your sample in every way the specification does not explicitly fix. Then go looking.
The taxonomy — and the test for each
| Coupling | Test |
|---|---|
| ID format | rename every id to a different scheme; do decisions survive? |
| Timestamp format | rewrite dates day-first; does ordering survive? |
| Row order | shuffle every context file; does output survive? |
| Directory layout | rename the media folder; does resolution survive? |
| Filename ↔ content | verify by magic bytes, never extension |
| Exact wording | which lexicon terms fire on exactly one sample row? |
What this caught in a real build — three real couplings, all found late
1. ID shape. Mention detection harvested tokens matching a regex for the sample's
id convention (@u_<digits>), then compared them to the recipient. The comparison was
principled; the harvest pattern was not. Renaming ids broke 4 of 110 decisions —
two rules went silently dead. Fixed by searching for @ + the actual recipient id,
assuming no format at all.
2. Timestamp format. History was sorted with a raw string sort — chronological only for zero-padded, most-significant-first dates. The spec fixes no format. Day-first dates produced different output.
3. Copied wording. A lexicon contained price is — a copula fragment transcribed
from one sentence, firing on 1 of 537 texts. Replaced with the underlying category,
which is broader and correctly rejects a colliding domain the copied version wrongly
matched.
The tell for an overfitted lexicon
Count how many corpus rows each term matches:
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.
- 12d ago First seen · 66 lines · 64 tokens per session scan A 214277e8aaf9
orchestrate-dataset-coupling-auditor is a skill published in the GitHub repository NITISH-R-G/hackerrank-orchestrate-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 742 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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