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-scoregit 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-score)<a href="https://agentmods.dev/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-score"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-score/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-score"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-score.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 | $0.00082 | $0.01353 |
| Opus 5.5 | $0.00033 | $0.00541 |
| Sonnet 5.5 | $0.00016 | $0.00271 |
| Haiku 4.5 | $0.00008 | $0.00135 |
Grade A, and why
orchestrate-score 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 yesterday.
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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Score Estimate
Read references/scoring-model.md first. It states what HackerRank published, what is missing, and what is guessed. Do not report a number without saying which part of it is estimated.
What this skill can and cannot do
- Can: estimate each section from evidence you can check, combine them with the published weights, and show which section is the weakest to fix.
- Cannot: produce HackerRank's real score. The golden datasets and the grader are not public. The kit's scorer is a heuristic and says so in its code (
orchestrate_kit/score/signals.py, DISCLAIMER).
Step 1 - Run the kit's scorer
From the repo root:
python -m orchestrate_kit score --no-history --python python
Options:
--transcript <file>to score the chat transcript export.--interview-result <file>for a JSON saved bypython -m orchestrate_kit interview --save <path>.--what-if output +5to see the weighted impact of a possible gain. It does not predict whether the gain is achievable.--auditto run the scorer's own self-test first. Run it once, so you trust the scorer before you trust its numbers.
Without the Output CSV, Interview and Transcript artifacts the report shows UNKNOWN for them. That is correct: supply the artifacts to get estimates for those sections.
--official-score <n>to record a real score you were given; the report then shows the gap.
The report shows four signal scores, the combined estimate, and the highest-leverage signal to fix. Save the output in evaluation/score_estimate.md if the challenge asks for evaluation evidence.
Step 2 - Check each section by hand
The heuristic is a starting point. Confirm each section against the evidence below.
| Section | Weight | Check |
|---|---|---|
| Output CSV | 30% | Accuracy on the sample you have labels for, per column. Justification quality per row. Safety rows handled without crashing. Use the per-column list in the current problem statement. |
| Code ZIP | 30% | Architecture is a real pipeline with clear seams. Prompts specify allowed outputs. Retries and caps exist. Secrets from env. README matches the code. |
| AI Interview | 30% | You can explain every decision in DESIGN.md, every number in CONSTANTS.md, and one measured regression. Use orchestrate-interview. |
| Chat Transcript | 10% | Plans before builds, specific instructions, real errors pasted, pushback visible. Use orchestrate-transcript rules in orchestrate. |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 85 lines · 82 tokens per session scan A 26d82544ff48
orchestrate-score is a skill published in the GitHub repository NITISH-R-G/hackerrank-orchestrate-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 82 tokens to every session and 1,353 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 2026-10-24.
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