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-schema-guardrailsgit 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-schema-guardrails)<a href="https://agentmods.dev/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-schema-guardrails"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-schema-guardrails/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-schema-guardrails"><img src="https://agentmods.dev/badge/skills/nitish-r-g/hackerrank-orchestrate-skills/orchestrate-schema-guardrails.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 | $0.00100 | $0.00663 |
| Opus 5 | $0.00050 | $0.00331 |
| Sonnet 5 | $0.00020 | $0.00133 |
| Haiku 4.5 | $0.00010 | $0.00066 |
Grade A, and why
orchestrate-schema-guardrails 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 11d 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 — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate: Schema Guardrails
Direct evidence: HackerRank's own "Getting better at Orchestrate" post names this explicitly as recommended practice — "Build guardrails around LLM outputs—validate schemas, reject unsupported labels, retry malformed responses." This is not inferred; it's stated advice from the organizers.
Why this is scored, not just good practice
Every Orchestrate challenge defines a fixed output schema (status ∈ {replied, escalated}, request_type ∈ {product_issue, feature_request, bug, invalid} for the support challenge; claim_status ∈ {supported, contradicted, not_enough_information} for the multi-modal challenge). An LLM will occasionally emit a value outside that set — a synonym, a slightly different casing, an extra field. Left unguarded, that becomes a malformed row in output.csv, which is graded mechanically against a golden dataset. A malformed row doesn't get "partial credit for being close" — it's either wrong or it breaks the grading script's parse.
The guardrail pattern
- Define the schema once, in code, not in a prompt comment. An enum/constant list the validator imports — not a string embedded in the prompt that the validator has no way to check against.
- Validate every model response against it before writing a row. Check required fields are present, enum fields are in the allowed set, and free-text fields aren't empty when required.
- On failure, retry with the failure fed back to the model — "you returned
status: closed, which isn't a valid value; valid values arerepliedorescalated" — rather than silently coercing or discarding. - Cap retries and have a defined fallback (see
orchestrate-failure-handlingfor what that fallback should be — never a silent guess).
What this looks like in review
An interviewer or code reviewer who opens your validation module should immediately see: the schema, the check, the retry, the fallback. If that logic is scattered across the codebase or absent entirely — if a bad model response can reach output.csv unfiltered — that's a concrete, checkable gap, not a matter of opinion.
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.
- 11d ago First seen · 28 lines · 100 tokens per session scan A d018dc6db0c2
orchestrate-schema-guardrails is a skill published in the GitHub repository NITISH-R-G/hackerrank-orchestrate-skills (3 stars, last pushed 29d ago), licensed MIT. It adds 100 tokens to every session and 663 once invoked, about $0.0005 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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