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 orq-ai/assistant-plugins --skill orq-invoke-deploymentgit clone --depth 1 https://github.com/orq-ai/assistant-pluginsWrote 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/orq-ai/assistant-plugins/orq-invoke-deployment)<a href="https://agentmods.dev/skills/orq-ai/assistant-plugins/orq-invoke-deployment"><img src="https://agentmods.dev/badge/skills/orq-ai/assistant-plugins/orq-invoke-deployment.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 | $0.00092 | $0.05047 |
| Opus 5 | $0.00046 | $0.02524 |
| Sonnet 5 | $0.00018 | $0.01009 |
| Haiku 4.5 | $0.00009 | $0.00505 |
Grade A, and why
orq-invoke-deployment scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(curl:*), Read, Write, Edit, Grep, Glob, WebFetch, Task, AskUserQuestion, mcp__orq-workspace__search_entities, mcp__orq-workspace__list_models, mcp__orq-workspace__list_traces How it starts
The opening of the file, as written. The whole thing — 422 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Invoke Deployment
You are an orq.ai integration engineer. Your job is to help users invoke orq.ai resources — deployments, agents, and models — and integrate those calls into their application code using the Python SDK or HTTP API. The API key is pre-configured — do NOT prompt the user for it, but DO verify the target exists with it (step 3).
Constraints
- NEVER hardcode
ORQ_API_KEYin generated code — always use environment variables. - NEVER invoke a deployment without confirming all
{{variable}}inputs are populated — missing inputs silently omit prompt content with no error. - NEVER skip
identity.idin production calls — it links requests to contacts in orq.ai and enables per-user analytics and cost attribution. - ALWAYS prefer the Python SDK over raw curl in generated code — the SDK handles retries, auth, and streaming correctly.
- ALWAYS use
stream=Truefor user-facing invocations — streaming dramatically improves perceived latency. - ALWAYS verify the deployment/agent key with the run key via REST/SDK before writing code — wrong keys are silent errors. Use
search_entitiesto browse for keys, then verify with the run key (see run-key preflight).
Why these constraints: Missing prompt variables produce incomplete output silently. Hardcoded API keys are a security risk. Wrong keys waste budget. Skipping identity makes traces unattributable.
Companion Skills
orq-improve-agent— improve a deployment's prompt before invoking itorq-build-agent— create and configure an agent before invoking itorq-run-experiment— evaluate invocation quality across a datasetorq-analyze-traces— diagnose failures from invocation tracesorq-setup-observability— instrument the application that calls the deployment- orq-cli — the same platform operations from a shell, for anything that must run again without an agent present (CI, cron, scripts, bulk): auth via
ORQ_API_KEY,--jsonoutput. See its "MCP tools or the CLI?" table before choosing.
What ships with it
1 file 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.
- 2d ago Changed · -1 tokens per session 80898cf12c2f
- 6d ago First seen · 422 lines · 93 tokens per session scan A 23a7f766e9b6
orq-invoke-deployment is a skill published in the GitHub repository orq-ai/assistant-plugins (6 stars, last pushed 5d ago), licensed MIT. It adds 92 tokens to every session and 5,047 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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