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/commands/juliusz-cwiakalski/agentic-delivery-os/plan-decision)<a href="https://agentmods.dev/commands/juliusz-cwiakalski/agentic-delivery-os/plan-decision"><img src="https://agentmods.dev/badge/commands/juliusz-cwiakalski/agentic-delivery-os/plan-decision/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/commands/juliusz-cwiakalski/agentic-delivery-os/plan-decision"><img src="https://agentmods.dev/badge/commands/juliusz-cwiakalski/agentic-delivery-os/plan-decision.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 | $0.00039 | $0.07280 |
| Opus 5 | $0.00019 | $0.03640 |
| Sonnet 5 | $0.00008 | $0.01456 |
| Haiku 4.5 | $0.00004 | $0.00728 |
Grade A, and why
plan-decision 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 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.
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 — 501 lines — stays where its author put it; the contents beside it link to each section on GitHub.
- Triages the decision (record-worthiness; R0 escape hatch), classifies it on four axes (type × domain tags × archetype × conditions), selects a rigor profile (R0–R3 + emergency overlay), and assigns decision rights (DACI) — then plans at a depth scaled by rigor.
- Discovers or confirms the decision record number (e.g. 0007) by scanning existing records in doc/decisions/ for the relevant type (ADR, PDR, TDR, BDR, ODR; defaults to ADR only when type is genuinely unspecified).
- Orients itself in the current repository and high-level documentation under doc/spec/, doc/overview/, doc/changes/, and doc/contracts/.
- Systematically elicits and refines all information needed by /write-decision (context, problem framing, hard requirements (constraints), decision drivers, alternatives, trade-offs, assumptions, verification criteria, etc.), without generating the decision record file itself.
- Applies decision-making discipline (clarify problem → classify → rigor → rights → confirm drivers → explore options → decide) without exposing internal mechanics unless asked.
- Concludes with a compact, machine- and human-friendly planning summary block plus a clear recommendation to invoke
/write-decision <number>and, where relevant, to link back to related changes (workItemRef).
This command never writes files or modifies Git state; it operates purely via conversational planning and read-only repository inspection. See doc/guides/decision-making.md for the full decision process.
/plan-decision [] [free-text context]
Examples:
-
/plan-decision
→ Auto-discover next number from doc/decisions/ for the relevant type, then ask what decision we are shaping. -
/plan-decision 12
→ Treat 12 as the intended record number (normalized internally to 0012), then start refinement questions. -
/plan-decision 0042 Choose data sharding strategy for multi-tenant billing
→ Use 0042 as the number and seed initial understanding from the idea text.
Notes:
- The command always operates within the current repository only (single codebase per session).
- If multiple decision sessions are active in the same conversation, clearly separate them by record number and avoid mixing context.
All other planning inputs (context, problem framing, drivers, alternatives, trade-offs, verification criteria, etc.) must be elicited interactively from the user and/or derived from existing documentation by summarization. No unstated assumptions may be invented. $ARGUMENTS
<number_resolution>
Primary goal: determine the canonical numeric record number (zero-padded to exactly 4 digits) for this planning session, for the chosen decision type.
Resolution rules:
-
If adrNumberHint is provided:
- Validate that it is composed of digits only.
- Normalize to zeroPad4 = numberHint left-padded with zeros to length 4 (e.g. 7 → 0007; 123 → 0123).
- Treat this as the proposed record number; ask the user to confirm or override.
-
If no numberHint:
- Discover existing decision records by scanning for files matching:
doc/decisions/<TYPE>-*-*.md(where TYPE defaults to ADR only when the decision type is genuinely unspecified). - For each match, parse the numeric segment immediately after the type prefix (e.g. ADR-0001-short-title.md → 1, TDR-0042-something.md → 42).
- If no existing records of this type are found, propose
0001as the first number. - Otherwise, let maxExisting be the highest parsed number; propose candidate = maxExisting + 1.
- Normalize candidate to zeroPad4 as above.
- Present the candidate to the user as the default (e.g. "Based on existing ADRs, I propose using number 0007."); allow the user to accept or override with any other integer.
- Discover existing decision records by scanning for files matching:
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 First seen · 501 lines · 39 tokens per session scan A 21a615f3efec
plan-decision is a command published in the GitHub repository juliusz-cwiakalski/agentic-delivery-os (37 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 7,280 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 2026-09-07.
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