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 lazysheep-z/apdr-product-design-runtime --skill decision-recordergit clone --depth 1 https://github.com/lazysheep-z/apdr-product-design-runtimeWrote 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/lazysheep-z/apdr-product-design-runtime/decision-recorder)<a href="https://agentmods.dev/skills/lazysheep-z/apdr-product-design-runtime/decision-recorder"><img src="https://agentmods.dev/badge/skills/lazysheep-z/apdr-product-design-runtime/decision-recorder/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/lazysheep-z/apdr-product-design-runtime/decision-recorder"><img src="https://agentmods.dev/badge/skills/lazysheep-z/apdr-product-design-runtime/decision-recorder.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 | $0.00616 |
| Opus 5 | $0.00013 | $0.00308 |
| Sonnet 5 | $0.00005 | $0.00123 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
apdr-decision-recorder 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 11d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Recorder (APDR)
Records key decisions at each pipeline stage using the MADR format (adr/madr 2284★).
Call this skill at the END of each pipeline stage, after writing the stage artifact.
ADR Format
Each decision record is a Markdown file saved under projects/{projectId}/decisions/:
# ADR-{NNN}: {decision title}
## Context
Why was this decision needed? What constraints or tradeoffs were considered?
## Decision
What was decided? Which option was chosen and why?
## Consequences
What does this mean going forward? What tradeoffs were accepted?
## Metadata
- Stage: {pipeline stage}
- Date: {YYYY-MM-DD}
- Artifact: {artifact type and ID}
- Author: APDR agent ({agent name})
What to Record Per Stage
| Stage | Decisions to Record |
|---|---|
| intake | Why this product/market? Why these target users? Why exclude other segments? |
| requirements_analysis | Why prioritize these JTBD? Why exclude certain requirements? Key assumptions flagged |
| prd | Why MoSCoW priorities? Feature tradeoffs. Why exclude features? Success metric choices |
| user_flows | Why this flow over alternatives? Design pattern choices. Error handling philosophy |
| information_architecture | Navigation structure decisions. Content grouping logic. Search strategy choices |
| wireframes | Layout patterns. Component placement reasoning. State handling approach |
| ui_design | Design token choices (color palette, typography, spacing). Component design decisions. Dark mode strategy |
| design_review | Issues found, fixes applied, waivers granted |
| frontend_codegen | Tech stack choices. Framework selection. State management approach. API integration patterns |
Workflow
- Identify the key decisions made in the current stage
- For each decision, write an ADR under
projects/{projectId}/decisions/ADR-{NNN}-{slug}.md - Use sequential numbering across the whole project (ADR-001, ADR-002, etc.)
- Link the ADR back to the stage's artifact in the
Metadata.Artifactfield - Reference the ADR in the stage artifact's
provenance.notes
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.
- 11d ago First seen · 68 lines · 26 tokens per session scan A 7740f4f809f8
apdr-decision-recorder is a skill published in the GitHub repository lazysheep-z/apdr-product-design-runtime (2 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 616 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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