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-ai-collaboration-transcriptgit 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-ai-collaboration-transcript)<a href="https://agentmods.dev/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-ai-collaboration-transcript"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-ai-collaboration-transcript/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-ai-collaboration-transcript"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-ai-collaboration-transcript.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 | $0.00112 | $0.01568 |
| Opus 5 | $0.00056 | $0.00784 |
| Sonnet 5 | $0.00022 | $0.00314 |
| Haiku 4.5 | $0.00011 | $0.00157 |
Grade A, and why
orchestrate-ai-collaboration-transcript 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.
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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate AI Collaboration Transcript
HackerRank's published philosophy is explicit that the target has shifted: "stop measuring whether a candidate can work without AI, and start measuring whether they can work well with it." The chat transcript signal (10% of Orchestrate's score) is the direct instrument for that — and it evaluates "planning, constraint-setting, debugging, and iteration patterns rather than the final product itself."
This is the one signal that cannot be fixed retroactively. It's a record of your actual process, not an artifact you produce at the end. Everything here is about how to prompt, applied from message one.
What a weak transcript looks like
A transcript that reads like a vending machine: terse requests, accepted output, no visible reasoning.
"write a function to classify tickets" (accepts output) "now add escalation logic" (accepts output) "fix this error" (pastes traceback, accepts fix)
Technically this could produce working code. It demonstrates nothing about planning, judgment, or debugging skill — because none of that is visible. If the transcript is graded on process, a transcript with no visible process caps out low regardless of the final code quality.
What a strong transcript looks like
The same work, with the reasoning made explicit:
"Before implementing: I want the agent to decide per-ticket whether to search the KB again with a refined query, rather than doing one fixed retrieval. Reasoning: the KB is 774 docs and a single embedding search will miss cases where the right doc uses different terminology than the ticket. Plan: retrieval as a tool the agent can call multiple times, capped at 3 calls, with the agent deciding when it has enough. Does this fit a ReAct-style loop cleanly, or is there a simpler structure for this specific case?"
This single message demonstrates: a design decision, the reasoning behind it, an explicit constraint (the cap), and an invitation for the tool to push back. That's plan visibility, and it's exactly what the philosophy piece says is being measured: "can this person plan a solution, direct an AI assistant, evaluate what it produces, and ship something that works."
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 · 72 lines · 112 tokens per session scan A f3dce4ebd9fa
orchestrate-ai-collaboration-transcript is a skill published in the GitHub repository NITISH-R-G/hackerrank-orchestrate-skills (3 stars, last pushed 28d ago), licensed MIT. It adds 112 tokens to every session and 1,568 once invoked, about $0.0006 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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