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 dlxeva/fde-operator-os --skill deployment-readinessgit clone --depth 1 https://github.com/dlxeva/fde-operator-osWrote 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/dlxeva/fde-operator-os/deployment-readiness)<a href="https://agentmods.dev/skills/dlxeva/fde-operator-os/deployment-readiness"><img src="https://agentmods.dev/badge/skills/dlxeva/fde-operator-os/deployment-readiness.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 | $0.00041 | $0.00652 |
| Opus 5 | $0.00020 | $0.00326 |
| Sonnet 5 | $0.00008 | $0.00130 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
deployment-readiness 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 8d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Readiness
Use this skill when the main question is:
- can this pilot enter production or a live operator workflow
- what blocks launch
- how will adoption, observability, incidents, containment, fallback, and rollback work
- why is a live deployment losing trust, quality, or operator use
Scope
Stay focused on production readiness and the earliest failed operating gate.
Primary outputs:
Production Readiness ReviewDay-2 Operations PlanGovernance And Risk OverlayField Signal Log
Supporting inputs:
POC Acceptance ContractEval PackMinimum Viable LoopReality Capture Gate
Readiness Areas
Evaluate each area separately:
- workflow and launch scope
- production ownership and support
- operator cohort and adoption
- evaluation and regression
- observability, audit, and incident response
- security, privacy, compliance, and authority
- containment, fallback, and rollback
- data, integration, capacity, and cost
- training and runbook readiness
- field-learning destination
Decision
Return one posture:
goconditional-gowith blockers, owners, and re-review triggersno-gowith evidence and re-entry conditions
For a deployment rescue, identify the earliest failed gate and return there. Do not default to a rebuild until the failing workflow, eval, ownership, or production evidence is understood.
Do Not Expand Into
- broad account strategy
- organization-wide transformation planning
- new feature ideation without a field signal and evidence
- scale planning before the current loop is stable
Completion Standard
A reviewer outside the build team can decide whether the loop should launch or continue running, who owns each risk, how failure is detected and contained, and what evidence will trigger the next review.
Output Style
- launch decision first
- evidence versus inference separated
- blockers with owner and next proof
- explicit incident, containment, fallback, and rollback paths
- operator adoption and workflow impact beside technical metrics
- field signals routed to a named destination
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.
- 8d ago First seen · 98 lines · 41 tokens per session scan A 6943843f88dd
deployment-readiness is a skill published in the GitHub repository dlxeva/fde-operator-os (11 stars, last pushed 29d ago), licensed MIT. It adds 41 tokens to every session and 652 once invoked, about $0.0002 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 2026-08-30.
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