Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSnpx agentmods add skills/dds-solutions/ai-tadpole-os/deployment-proceduresWrote 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/dds-solutions/ai-tadpole-os/deployment-procedures)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/deployment-procedures"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/deployment-procedures/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/dds-solutions/ai-tadpole-os/deployment-procedures"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/deployment-procedures.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00581 |
| Opus 5 | $0.00015 | $0.00291 |
| Sonnet 5 | $0.00006 | $0.00116 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
deployment-procedures 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 9d 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.
What it actually says
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / deployment-procedures
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Production Deployment & State Transition Protocol
Philosophy: Never deploy unverified code. Always have an immediate, tested rollback path. Workflow Binding: Used directly during the
/deployworkflow.
🎯 Progressive Disclosure & L3 Reference Index
Read REQUIRED deployment gates below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Purpose | Trigger / When to Load |
|---|---|---|
references/rollback_and_verification_matrix.md |
Platform runbooks (Docker/PM2/K8s), migration expand-and-contract | Staging-to-production transitions & rollbacks |
🚀 1. The 5-Phase Release Pipeline
1. PREPARE ➔ Run `parity_guard.py` & unit tests; verify production build.
2. SNAPSHOT ➔ Backup persistent SQLite / database state.
3. RELEASE ➔ Execute binary update / container rollout with live log tailing.
4. VERIFY ➔ Query `/health` endpoint and inspect initial traffic telemetry.
5. CONFIRM ➔ If error rate > 0.1% or panic detected ➔ ROLLBACK IMMEDIATELY.
🛑 2. Rollback Triggers (Non-Negotiable)
Initiate an automated or manual rollback if:
- Health Check Failure: Service fails to return 200 OK within 15 seconds of boot.
- Panic / Crash Loop: Engine emits panic logs or exits with non-zero exit code.
- Database Lock Contention: SQLite WAL mode encounters database locked exceptions.
🛠️ 3. Verification Commands
# 1. Verify build and link integrity
python execution/parity_guard.py .
# 2. Verify backend compiles cleanly
cargo check --manifest-path server-rs/Cargo.toml
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.
- 9d ago First seen · 61 lines · 29 tokens per session scan A c59d6413ccdd
deployment-procedures is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 581 once invoked, about $0.0001 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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