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 agentmods add skills/addit-digital/addit-harness/adrnpx skills add addit-digital/addit-harness --skill adrgit clone --depth 1 https://github.com/addit-digital/addit-harnessWrote 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/addit-digital/addit-harness/adr)<a href="https://agentmods.dev/skills/addit-digital/addit-harness/adr"><img src="https://agentmods.dev/badge/skills/addit-digital/addit-harness/adr.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 | $0.00067 | $0.01454 |
| Opus 5 | $0.00034 | $0.00727 |
| Sonnet 5 | $0.00013 | $0.00291 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
adr 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 5d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Decision Record (ADR) — MADR format
Capture a significant architectural/technical decision as a durable, structured record in MADR 4.0 format (Markdown Any Decision Records), stored in version control next to the code so future readers understand why, not just what.
Sources / further reading:
- MADR: https://adr.github.io/madr/ · https://github.com/adr/madr
- Format gallery (Nygard, MADR, etc.): https://github.com/joelparkerhenderson/architecture-decision-record
- Nygard's original: https://www.cognitect.com/blog/2011/11/15/documenting-architecture-decisions
When to write one
ADR-worthy = significant and hard to reverse: technology/framework/database choice, API or integration style, data model, architectural pattern (monolith vs services, sync vs event-driven), security approach, or a notable trade-off. Skip trivial, easily-reversed choices.
Choosing minimal vs full
- Minimal (default): smaller/medium decisions — Context & Problem, Considered Options, Decision Outcome (+ Consequences).
- Full: weighty decisions with several real alternatives — adds Decision Drivers, per-option Pros and Cons, Confirmation, and More Information.
- Honor
--full/--minimalif given; otherwise pick by decision weight.
Procedure
- Locate/initialize the store. Use
docs/adr/. If it doesn't exist, create it and adocs/adr/README.mdindex. If the repo already has an ADR location or template, follow that instead. Optionally seed the meta-ADR0001-record-architecture-decisions.md(records the decision to use ADRs). - Assign the next number. Scan
docs/adr/for the highestNNNN, increment; 4-digit zero-padded starting at0001. - Gather context. From the conversation/code extract: the problem and why now, decision drivers/forces, the alternatives considered, the chosen option, and consequences (good and bad). Ask the user only for what you can't infer — especially alternatives rejected and why, the most valuable part.
- Write
docs/adr/NNNN-kebab-case-title.mdusing the matching template below. When the decision involves architecture or flow, embed a mermaid diagram (componentgraph/flowchartand/orsequenceDiagram) in Context and Problem Statement and/or per option — ADRs live as files / on GitHub, so mermaid renders. Skip it for non-structural decisions. - Update the index
docs/adr/README.mdwith a row: number, title (link), status, date. - Report the path and a one-line summary. Don't commit unless asked.
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.
- 5d ago First seen · 172 lines · 67 tokens per session scan A 54eaa21e2917
adr is a skill published in the GitHub repository addit-digital/addit-harness (3 stars, last pushed 13d ago), licensed MIT. It adds 67 tokens to every session and 1,454 once invoked, about $0.0003 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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