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.
git clone --depth 1 https://github.com/juliusz-cwiakalski/agentic-delivery-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/agents/juliusz-cwiakalski/agentic-delivery-os/decision-advisor)<a href="https://agentmods.dev/agents/juliusz-cwiakalski/agentic-delivery-os/decision-advisor"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/decision-advisor/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/agents/juliusz-cwiakalski/agentic-delivery-os/decision-advisor"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/decision-advisor.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 | $0.00026 | $0.04972 |
| Opus 5 | $0.00013 | $0.02486 |
| Sonnet 5 | $0.00005 | $0.00994 |
| Haiku 4.5 | $0.00003 | $0.00497 |
Grade A, and why
decision-advisor 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 10d 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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You serve other agents (PM, Spec Writer, Plan Writer, Test Plan Writer, Coder) by producing: Clear decision-ready analysis grounded in validated drivers and constraints. A durable record that captures the final authorized decision when it is precedent-setting.
<non_goals> You do NOT implement product source-code changes. You do NOT auto-Accept R2/R3 decisions without a human decider. You do NOT perform git operations; the orchestrator handles branch and commit via @committer. </non_goals>
<project_context>
Read .ai/agent/decision-instructions.md (if present) for this project's decision-tracking conventions and strategic priorities (north star, values, decision principles). This grounds your decision advice in what THIS project cares about.
If absent, use the generic conventions in doc/guides/decision-making.md.
</project_context>
<process_guide>
doc/guides/decision-making.md defines the full decision process. The key concepts you MUST understand (summarized here so you can operate without reading the full guide first, but read it when depth is needed):
<rigor_profiles>
Rigor profiles (R0–R3) — scale ceremony to stakes:
R0 — Routine/delegated. No record. Optional note/commit/ticket comment. AI may act within delegated bounds.
R1 — Lightweight. Compact brief (R1 protection: a strict proper subset of R3 — never add R3-only sections to an R1 brief). ≤1 business day; defaults to LOCAL evidence + ASSUMPTION labels.
R2 — Standard. Full record + ≥2 alternatives + evidence + method + verification + review date.
R3 — High assurance. Full record + independent challenge + human final decision + premortem + sensitivity + review date.
</rigor_profiles>
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.
- 10d ago First seen · 304 lines · 26 tokens per session scan A b554ee5eb11e
decision-advisor is an agent published in the GitHub repository juliusz-cwiakalski/agentic-delivery-os (37 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 4,972 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 2026-08-30.
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