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-transcript-engineeringgit 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-transcript-engineering)<a href="https://agentmods.dev/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-transcript-engineering"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-transcript-engineering.svg" alt="Measured on agentmods" 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 | $0.00065 | $0.01770 |
| Opus 5 | $0.00032 | $0.00885 |
| Sonnet 5 | $0.00013 | $0.00354 |
| Haiku 4.5 | $0.00006 | $0.00177 |
Grade A, and why
orchestrate-transcript-engineering 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 6d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate: Transcript Engineering
Evidence tier: HackerRank's own published methodology ("Behind the
Scenes of HackerRank Orchestrate," hackerrank.com, June 2026) for the
rubric weights and dimensions — quoted numbers, paraphrased descriptions,
cited, not reproduced. First-hand for the pattern-detection heuristics
and the honesty boundary they carry, built and tested inside this
repository, same discipline as orchestrate_kit/judge/scoring.py.
The realization this skill is built on
HackerRank's own writeup states plainly: the AI Chat Transcript score measures how the human directed the coding agent, not what the agent produced. A transcript full of working code with no visible direction still scores low on this axis — and it's the highest-weighted rubric this skill covers (35% for Direction & Architecture Ownership alone).
That means transcript quality is a separate optimization target from code quality, and it's addressable the same way this repository addresses everything else: measure the gap, build the tool, verify it discriminates.
What this is not
Not a prediction of your real HackerRank score. No ground-truth graded
transcript exists to calibrate against — orchestrate transcript analyze scores the shape of a transcript (ownership language, named
alternatives, reported measurements, named risk mechanisms), the same
honesty boundary orchestrate interview already states for spoken
answers. A transcript claiming "I measured X" scores the same whether X
was actually measured or invented. Use it as a self-review checklist, not
a scoreboard.
Stated plainly, found by actually trying to break it, not assumed
safe: the analyzer is regex pattern-matching, which means it can be
gamed by stuffing rubric-matching phrases into a transcript with no real
engineering behind them. A repetition penalty closes the cheapest version
of that (three copies of one boilerplate sentence dropped from 86 to 50
once the penalty landed), but a determined, novel-phrasing gamer could
still beat pattern-matching that isn't checking truth, only shape. This
is not a solved problem — it's the same honesty boundary every heuristic
text analyzer in this project states (judge/scoring.py's docstring says
it explicitly too): it trains form, truth is your job, and a fluent
answer full of invented specifics scores well here and would fail a real
technical follow-up.
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.
- 6d ago First seen · 132 lines · 65 tokens per session scan A bf857de44f91
orchestrate-transcript-engineering is a skill published in the GitHub repository NITISH-R-G/hackerrank-orchestrate-skills (3 stars, last pushed 25d ago), licensed MIT. It adds 65 tokens to every session and 1,770 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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